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The Medicare prospective payment theory as applied to the management of patient care outcomes

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Title:
The Medicare prospective payment theory as applied to the management of patient care outcomes
Creator:
Aldridge, Susan Cockings
Place of Publication:
Denver, CO
Publisher:
University of Colorado Denver
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Language:
English
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ix, 166 leaves : illustrations, forms, map ; 29 cm

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Subjects / Keywords:
Older people -- Medical care ( lcsh )
Older people -- Medical care -- Case studies -- Colorado -- Denver Metropolitan Area ( lcsh )
Older people -- Medical care ( fast )
Colorado -- Denver Metropolitan Area ( fast )
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Case studies. ( fast )
bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )
Case studies ( fast )

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Bibliography:
Includes bibliographical references.
Thesis:
Submitted in partial fulfillment of the requirements for the degree, Doctor of Philosophy, Graduate School of Public Affairs
General Note:
School of Public Affairs
Statement of Responsibility:
by Susan Cockings Aldridge.

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|University of Colorado Denver
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|Auraria Library
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All applicable rights reserved by the source institution and holding location.
Resource Identifier:
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ocm28478239
Classification:
LD1190.P86 1991d .A42 ( lcc )

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Full Text
THE MEDICARE PROSPECTIVE PAYMENT THEORY AS APPLIED
TO THE MANAGEMENT OF PATIENT CARE OUTCOMES
by
Susan Cookings Aldridge
B.A., Colorado Women's College, 1977
i
M.P.A., University of Colorado at Denver, 1987
A thesis submitted to the
Faculty of the Graduate School of Public Affairs of the
University of Colorado in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy
Graduate School of Public Affairs
1991


This thesis for the Doctor of Philosophy
degree by
Susan Cookings Aldridge
has been approved for the
Graduate School of Public Affairs


:l!
Aldridge, Susan Cookings (Ph.D., Public Administration)
The Medicare Prospective Payment Theory as Applied to the Management of Patient Care
Outcomes
1 '!
Thesis directed by Associate Professor Robert Gage.
This work concerns the effect of a case manager at hospital discharge on nursing
home placement. Further, this research explored the impact that gender, marital status,
housing level at admission and health status had as predictors of nursing home
placement at hospital discharge. This research was designed to describe the critical
point of hospital discharge to develop causal hypotheses and new options for moving
Medicare patients to appropriate, least costly, least restrictive environments. Finally,
discharge planners perceptions of their hospitals services were evaluated.
The "Study concludes that: (1) housing at admission, age, marital status and
gender are predictors of hospital discharge to nursing homes; (2) hospitals vary in their
housing placements of elderly Medicare patients at discharge; (3) there were significant
differences in the level of housing independence eight weeks after hospital discharge
between patients receiving case management and those receiving typical discharge
planning practices; and (4) discharge planners perceive their hospitals services to be
less comprehensive in the areas of housing referral and housing follow-up than in any
other area. This exploratory study suggests that using a case management approach
after hospital discharge could result in a 21 percent decrease in the number of elderly
patients remaining in the nursing home eight weeks after discharge, which is a potential
annual savings of $3 million in Colorados nursing home costs.
i
The form and content of this abstract
Signed_____
its publication.


CONTENTS
FIGURES .............................................................
TABLES . ............................................................
ACKNOWLEDGEMENTS ......................................................
I
CHAPTER
1 INTRODUCTION..............................................
i Trends Impacting Health Care..........................
Trend 1: Changes in the Health Care Industry......
Trend 2: Growth in the Older Population...........
Trend 3: Escalating Medicare Care Costs........
Trend 4: Increasing Admissions to Nursing Homes . .
Implications of Trends on Future Policies.........
The Problem...........................................
Rationale for the Study...........................
Statement of the Problem..........................
Anticipated Impact of the Intervention................
Investigative Procedures..............................
Descriptive Data Collection ..........................
Subjects: Sampling Procedures and Description ....
Measures..........................................
Procedure ........................................
Case Management Intervention .........................
Subjects..........................................
Housing at Admission and Discharge................
vi
vii
ix
1
4
4
4
5
5
6
7
7
9
10
12
12
14
15
16
18
19
20


,1
CHAPTER (cont.)
Measures.............................................. 23
Design................................................ 24
Procedure ............................................ 25
Qualitative Data ......................................... 28
2 Analysis of contemporary research on
MEDICARE COST CONTAINMENT AND THE IMPACT
ON HOSPITAL DISCHARGE PLANNING AND NURSING
HOME ADMISSIONS............................................... 29
Demographic Projections................................... 29
The Medicare Program ..................................... 36
Basic Components of Medicare.......................... 36
Transitions in the Medicare Program .................. 38
Medicare Cost Containment ............................ 40
The Impact of Major Legislation on Medicare Costs .. 41
The Impact of the Growing Older Population and
Medicare Policy Changes on Nursing Home Admissions .. 46
Summary of Research Findings Regarding the Impact
of Medicare Changes on Hospital Discharge................. 55
Patient Characteristics as a Predictor of Posthospital
Care...................................................... 57
Patient Satisfaction with Discharge Planning.......... 60
The Impact of Medicare Policy Changes on
Hospital Discharge Planning .......................... 61
The Impact of the Increasing Older Population on
Future Medicare Policies and Community Services...... 68
Housing of Very Old Patients after Hospital Discharge .... 70
; Rationale for Case Management Intervention ............... 75
ii


CHAPTER (cont.)
3 RESULTS.......................................................... 81
Description of Hospital Admissions.......................... 82
Patient Characteristics ................................ 82
Predictors of Housing Placement at Discharge......... 82
Predictions of Housing Level Eight Weeks after
Discharge............................................... 87
Nursing Home Discharges................................. 88
Hospital Differences in Housing Placements.............. 90
Effects of the Case Management Intervention................. 92
Generalized Effect on Hospital Discharges............... 92
Effects of the Case Managers Direct Services........ 94
Patient Satisfaction with Hospital Discharge Services .... 97
Perceptions of Service Offered ......................... 98
Qualitative Research Phases and Results..................... 99
Invention ............................................... 101
Discovery.................................................. 103
Discovery: Discharge Planning Process ................. 103
Discovery: The Physicians Role in Discharge
Planning............................................... 105
Discovery: Family Counseling .. ..................... 106
Discovery: Insurance and Reimbursement Issues .. 108
Interpretation ............................................ 109
Interpretation: Discharge Planning Process............. 109
Interpretation: DRG Impact............................. 110
iii


CHAPTER (cont.)
Interpretation: Management Issues.................... 111
Interpretation: Resource Information on Alternative
Patient Servicing.................................... 112
Interpretation: Industry Issues...................... 113
Explanation.............................................. 114
Overview............................................. 114
Personal Visits by Discharge Planners................ 114
Scheduling........................................... 115
Physicians Role in the Discharge Planning Process . 115
Discharge Planning and Reimbursement ................ 115
Counseling of Families .............................. 116
Limited Resources ................................... 116
4 CONCLUSIONS AND IMPLICATIONS ................................ 117
Conclusions ............................................. 117
Impact of Case Management on Hospital Discharge . 118
Policies and Practices Precipitating the Research ... 119
Demographic Characteristics Which Provoke
Housing Changes..................................... 121
Issues in Measuring Housing......................... 123
Discharge Planning: A Role in Transition................ 125
Changing Models for Discharge Planning.................. 129
Research Strategies .................................... 133
Sampling ........................................... 133
Measures............................................ 135
iv


CHAPTER (cont.)
Discussion of Future Research ..................... 140
Discussion of Future Practices........................... 142
APPENDIXES
Appendix A. Discharge Abstract ................................... 146
Appendix B. Medicare Patient Authorization for Release of Information ... 147
Appendix C. Telephone Script for Two Week Follow-up ..................... 148
Appendix D. Telephone Script for Eight Week Follow-up.................... 149
Appendix E. Map of Participating Hospitals .............................. 150
Appendix F. Long Term Care Housing Continuum ........................... 151
Appendix G. Evaluation of Breadth of Services Available to Medicare
Patients Over Age 75 Discharged From This Hospital..... 153
BIBLIOGRAPHY.............................................................. 154
v


FIGURES
Figure 2.1. Annual Movement of Persons 65-74 through the Health
Care System............................................ 34
Figure 2.2. Annual Movement of Persons 75 and Over through the
Health Care System..................................... 35
Figure 2.3. Long Term Care Housing Continuum....................... 70


TABLES
Table 1.1. Research Objectives and Methods of Data Collection................. 13
Table 1.2. Hospitals Participating in the Research............................ 14
Table 1.3. Demographic Characteristics of Admissions Over Age 75 at
;5 Denver Hospitals............................................ 21
Table 1.4. Demographic Characteristics by Hospital............................ 22
Table 1.5. Housing Levels at Admission, Discharge, and Eight Week
Follow-up ..................................................... 23
Table 1.6. Multiple-Baseline Design........................................... 25
Table 2.1. Denver Metropolitan Area Forecast Absolute and Percent
Change of the Total Population: 1988-2010 ..................... 30
Table 2.2. Denver Metropolitan Area Forecast Absolute and Percent
Change of the 60+Population: 1988-2010 ........................ 31
Table 2.3. 75+Population 1988-2010............................................ 32
Table 2.4. Role of Major Factors Affecting Health Care Transitions............ 39
Table 2.5. Estimated Medicare Savings from Six Major Laws..................... 43
Table 2.6. Percentage of Elderly Hospitalized Persons Discharged
Home and Percent Discharged to a Nursing Home by
Age: 1986 ..................................................... 49
Table 2.7. Impact of Prospective Reimbursement................................ 50
Table 2.8. Source of Nursing Home Revenues (Calendar year 1988)............... 51
i'
Table 2.9. Projected Number of Nursing Home Residents in Colorado
and Percent Change by Age and Sex, 1980-2000................... 53
Table 2.10. Colorados Medicaid Expenditures for Aged Hospitalization
and Nursing Home Care: 1981-1990............................... 56
Table 2.11. Characteristics of the 111 Mountain Region Hospitals
Responding to GAO Survey on Posthospital Care.................. 64
Table 2.12. Posthospital Destination of Medicare Discharges in the
Mountain Region................................................ 65


Table 2.13. The Most Important Barrier in the Mountain Region to
Placing Medicare Patients in Home Health Care................ 66
Table 2.14. Frequency of Posthospital Contact with Medicare Patients by
Discharge Planners in the Mountain Region ................... 68
( ii
Table 2.15. Comparison of Long-Term Care Clients in Colorado and
Oregon: 1980................................................. 79
Table 2.16. Comparison of Long-Term Care Clients in Colorado and
Oregon: 1990 ................................................... 79
Table 3.1. Housing Level at Discharge by Gender and Marital Status....... 83
Table 3.2. Housing Level Eight Weeks after Discharge by Gender and
Marital Status ................................................. 85
Table 3.3. Correlations of Background Variables with Housing Type........ 85
Table 3.4. Stepwise Regression Equation Predicting Housing Level at
Discharge....................................................... 86
Table 3.5. Stepwise Regression Equation Predicting Housing Level
Eight Weeks after Hospital Discharge............................ 88
Table 3.6. Stepwise Regression Equation Predicting Housing Level of
Elderly Patients (75+) Eight Weeks after Hospital Discharge. ... 88
Table 3.7. Housing Levels at 8 Weeks: Patients Using Case Manager
versus No Case Manager.......................................... 95
Table 3.8. Discharge Planners Perceptions of Adequacy of Services to
Elderly Medicare Patients....................................... 99
Table 4.1. Professional Discipline of Discharge Planners at Participating
Hospitals...................................................... 128


ACKNOWLEDGEMENTS
For their encouragement and loving support, special thanks go to my husband
M. Gene Aldridge; my two stepsons Scott and Michael Aldridge; my mother-in-law Zora
E. Aldridge; my aunt Alice Gill; and to my dear friend Molly B. Snyder. For their patience,
constructive suggestions and thoughtful advice, my gratitude and respect go to each of
the members of my dissertation committee: Robert Gage, E. Samuel Overman, A. David
Clayden, Kathryn Denhardt, and Catherine Crawford. This research was made possible
through funding from the U.S. Department of Health and Human Services and the Denver
Regional Council of Governments. This research would not have been possible without
the valuable contributions of Dr. Sara Qualls, the Colorado Hospital Association, the
Colorado Association of Homes and Services for the Aging, the 1,040 patients, and the
five participating hospitals.
IX


CHAPTER 1
i
INTRODUCTION
Public policies provide a framework within which managers operate.
Government policies are created to address societys concern and prevent future
problems from occurring. All too frequently there is no evaluation of the extent to
which the public policies addressed the intended problem or created an unintended
spillover effect in another area. Reforms aimed at achieving one value may
prevent us from achieving another. Judith Gruber described the relationship
between public managers, or bureaucrats as she calls them, and policymakers:
In the course of making their decisions about how a program will actually
work, bureaucrats give the program shape and form. They are guided by
decisions of legislatures, but those decisions often do little more than
establish a broad domain within which bureaucrats must act. . politicians
and bureaucrats bring distinctive perspectives and competencies to policy
making (Gruber, 1987, p.6).
This research explores the impact of a public policy, describes the
operationalization of the policy, identifies the successes and problems precipitated
by the policy, suggests a hypothesis for preventing the spillover effects, and tests
the hypothesis. Although financial resources are limited for public program
evaluation, managers have an opportunity to positively impact public policies if data
is forthcoming. Carl Friedrich described the relationship as: "Public policy, to put it
flatly, is a continuous process, the formulation of which is inseparable from its
execution" (Friedrich, 1940, p.6).
The public policy which is the primary focus of this research is Medicare
prospective payment theory. Sufficient data are available to analyze the impact of


the policy and explore options which would prevent some of the negative outcomes
' )
or spillover effects from the public policy.
Through the use of exploratory research or grounded theory, managers of
publicly funded programs have an opportunity to impact legislative changes thereby
improving current public policies. Research is frequently conducted to replicate
previous studies in order to validate certain facts or theories. The complex
dynamics in the health care system and the relatively recent implementation of
Medicare prospective payment theory suggests a research approach which will
broaden opportunities for further study and policy change. Therefore, both qualita-
tive and quantitative methods are required. Glaser and Strauss (1967) described
the appropriate use of qualitative and quantitative research:
Our goal of generating theory also subsumes this establishing of empirical
generalizations, for the generalizations not only help delimit a grounded
theorys boundaries of applicability; more important, they help us broaden
the theory so that it is more generally applicable and has greater explanato-
ry and predictive power, (p. 24)
Through this exploratory research, a hypothesis will be tested and, more important-
ly, the qualitative research will generate new theories for future exploration.
The purpose of this exploratory research is two-fold. First, the intervention
of a case manager at hospital discharge will be tested to determine whether
nursing home placement can be prevented or delayed. Second, data will be
collected on older patients at hospital discharge to determine the variables which
predict nursing home placement. The first null hypothesis for this exploratory
research is that the intervention of a case manager at hospital discharge will not
have an effect on the admissions to nursing homes. The second null hypothesis is
2


that gender, marital status, housing level at hospital admission, and health status
are not predictors of nursing home placement at hospital discharge. Both qualita-
tive and quantitative data are essential for addressing these hypotheses and for
preparing recommendations which improve future Medicare policies.
Recent federal Medicare policy changes pressure hospitals to discharge
older patients earlier thereby reducing federal Medicare expenditures for hospital
stays. Although the number of patient days in the hospital was significantly
reduced as a result of these policy changes, more patients are being discharged to
nursing homes than to their own home with services or to another less costly
housing option. Discharging patients to nursing homes, when other less costly
services are appropriate, merely shifts the cost for government from the Medicare
program to Medicaid. As a public policy, prospective reimbursement successfully
reduced federal Medicare expenditures for hospital stays, however, options must
be explored to prevent a cost shift to Medicaid. Through the intervention of a case
manager, and through identifying variables which predict nursing home placement,
this research will test the extent to which nursing home placements can be prevent-
ed. Not all nursing home placements are undesirable. At some level of depen-
dence and frailty, there is no more appropriate or cost-effective option other than
24 hour per day supervised care. The intervention in this research assumes that
nursing home placement may be the most appropriate service for some patients.
However, when other services are appropriate for the patient and when the
services are both more appropriate and less costly, nursing home admission should
be prevented.


Trends Impacting Health Care
A number of environmental forces and trends have impacted the health care
industry, government policymakers, managers of publicly funded health services,
and older patients. These trends precipitated the federal Medicare policy changes,
which authorized prospective payment systems and created one spillover effect,
premature nursing home admissions, which will be addressed by this research. A
description of the four trends which led to Medicare policy changes follows with
corresponding implications.
Trend 1: Changes in the Health Care Industry
The first trend is the dramatic change in Americas health care industry.
Coile describes the health care industry in a state of" fundamental restructuring of
supply and demand, moving rapidly away from a predictable pattern of cost-based
payment to the rough and tumble of a competitive market (Evashwick & Weiss,
1987, p. 12). He cites thirteen different factors which have triggered cost contain-
ment strategies in health care: rising Medicare costs, the federal deficit, Social
Security insolvency, the 1981 to 1983 recession, 15 to 30 percent annual increases
in health care and hospital costs, lack of controls over hospital and physician
utilization, increasing out-of-pocket costs, rising co-insurance costs, malpractice, a
non-competitive fee-for-service system, rising health maintenance organization
enrollments, and a surplus of physicians.
Trend 2: Growth in the Older Population
The second trend impacting the health care industry is the growth in
Americas older population. Life expectancy has increased by 12 years since 1940
4


making the 75 and older age group the fastest growing segment of the older
: !'j
population. This growth will challenge the health care delivery system when the
post-war baby boom results in a boom to the elderly population between the years
2010 and 2030:
Trend 3: Escalating Medicare Care Costs
Third, the Medicare program is only two decades old, however, trends of
the increasing older population and escalating costs of medical care precipitated
new cost containment measures within the last decade. Hospital care was targeted
ii!
for cost containment since charges for hospital care are approximately two-thirds of
the medical care expenditures for older people. These cost containment measures,
called prospective hospital reimbursement, contain 468 "diagnosis related groups"
(DRGs) for different medical conditions. Medicare sets fees in advance for the
amount it will pay for each DRG. Since the implementation of these measures in
1983, major changes have occurred in patient care.
Trend 4: Increasing Admissions to Nursing Homes
: j;
The fourth trend impacting the health care industry is the 27 percent
I-
increase in the number of older patients discharged from hospitals to nursing
homes since the hospital prospective reimbursement policies were implemented in
:|
1983. Since patients spend their financial resources and become eligible for
Medicaid coverage in approximately 13 weeks of admission to a nursing home,
n'
Medicaid expenditures are on the rise. Hospitals are under increasing pressure to
discharge older patients earlier, however, more patients are being discharged to
|j,
nursing homes rather than to their own home with services or to another less costly

5


housing option; Discharging patients to nursing homes, when other less costly
; '! j
services are appropriate, merely shifts the cost for the government from the
Medicare program to Medicaid.
Joseph jCalifano, former Director of the U.S. Department of Health, Educa-
tion and Welfare calls this cost-shift phenomenon a government "shell game."
Government in particular has got to get its act togeth-
er, stop playing the health care cost shell game and
turn its attention to instituting some system-wide re-
forms.... there isnt much time left to get an efficient
health care delivery system. The graying of America
is forcing the issue, with a rapidly increasing number
of older citizens demanding more and more in expen-
sive high-technology hospitals and nursing homes.
Our nation cannot tolerate the shell game much lon-
ger. (Califano, 1986, pp. 166-167)
Implications of Trends on Future Policies
The implications of these four trends concern policymakers, public manag-
ers and health Care funders. This research focuses on one aspect of the health
care system which can be reformed through new interventions. In order to prevent
the "shell game" Califano describes, a closer look at the hospital discharge
planning process offers new insights into intervention options. Recent statistics
i ill
which show a rapidly increasing rate of nursing home admissions have been
interpreted to suggest that time pressure from DRGs is forcing hospitals to dis-
charge more frdil elderly to nursing homes (Swan, de la Torre & Steinhart, 1990).
This pattern is of particular concern because of the tendency for nursing home
placements to become permanent (Fitzgerald, Moore, & Dittus, 1988). Clearly, an
!l
examination of housing and nursing home placements from hospitals is needed.
6


Hospitalizations stimulate housing crises, as well as health crises, for many
elderly who will need significant personal and health assistance following hospital-
ization. Furthermore, the supportive housing needs of some elderly come to the
attention of health care professionals during a hospitalization. It is increasingly
evident that hospital professionals are in a position to recognize needs for support-
ive services for the elderly, and that the discharge process is mandated by Medi-
care to implement services and housing changes to meet those needs. At this
historical juncture, however, little is known about how much housing change occurs
as a function^ of the discharge process, which populations are most likely to require
new housing placements, and how adequately prepared discharge planners are for
this task.
The Problem
Rationale for the Study
Health care in America is in transition. As the older population increases
and costs of health care rise more rapidly than the Consumer Price Index,
government policymakers and managers must continue to seek options which will
control costs without hurting the quality of patient care. This exploratory research
was developed after consideration of:
1. The significant increase in the older population;
2. The change in Medicare hospital reimbursement
Which dramatically decreased the length of hospital
stay for older adults;
3. The corresponding increase in nursing home admissions;

7


4. The drastic increases in Medicaid expenditures; and
5. The influence which hospitals have on nursing home placement.
Although health care financing is extremely complex, the data indicate direct
correlations between these changes (U.S. General Accounting Office, 1983;
Lammers, 1984). With the advent of prospective reimbursement to hospitals,
Medicare patiehts length of stay decreased by 60 percent. Simultaneously, the
number of patents discharged from the hospital to nursing homes doubled. Of
even greater cbncern is the 300 percent increase in the number of patients
discharged to nursing homes who were still in nursing homes six months after
admission (Sagpr, Leventhal & Easterling, 1987). Patients residing in a nursing
home for six months are likely to "spend down" all of their financial resources and
!l-
go on the Medicaid program for the duration of their lives.
As a public policy, prospective reimbursement through DRGs successfully
; i
reduced Medicare expenditures by millions of dollars. Simultaneously, however,
Medicaid expenditures for nursing home care increased. In order to prevent this
cost-shift from, Medicare to Medicaid, an intervention is necessary which allows the
i-
cost savings from early discharge but prevents either premature institutionalization
to nursing homes or readmissions to the hospital.
The purpose of this exploratory research is two-fold. First, this research will
test one option for intervention which will delay or prevent the cost shift for the
government, thus saving millions of dollars annually if introduced on a national
scale. Second, this research will collect data on older patients at discharge to
determine the: variables which predict nursing home placement (e.g., gender or
8


marital status).1 Public managers and policymakers need to explore new options
which save money and simultaneously maintain the quality of patient care.
Schneider and Guralnik (1990) called for vigorous pursuit of cost containment,
while pursuing other approaches to limiting future health care costs. The investiga-
tion in this exploratory research is timely since any cost savings in federal or state
government expenditures today may prevent unnecessary expenditures in the
future when the older population booms.
Ill
Statement of the Problem
An effective intervention is necessary to reduce the documented increase in
hospital discharges to nursing homes, ensure the provision of appropriate services
for frail discharged patients, and prevent the unnecessary increase in admissions to
the Medicaid program. Branch and Jette (1982) criticized evaluators and research-
ers for determining the cost-effectiveness of programs without adequately examin-
ing the program effect on the very individuals who were at risk and targeted for the
outcome of the intervention (Shapiro & Tate, 1988). This research was developed
to propose an intervention in the form of a case manager and test the outcome of
'l
the older adults who are at risk of institutionalization. An exploratory research
' l
approach is essential in order to test the hypothesis for intervention. In order to
target individuals who are most at risk of institutionalization after discharge,
variables which predict nursing home placement will be identified through this
research.
9


The purpose of this exploratory research is to:
1. Describe the demographic characteristics of the hospitalized popula-
tion age 75 and older in 5 Denver metropolitan area hospitals;
2. ! identify the extent to which hospitalization provokes housing
Changes for older adults age 75 and older on Medicare;
3. Determine the nature and predictors of those placements;
4. : Determine the permanence of the placements;
5. , Determine the extent to which the intervention of a case manager at
discharge can prevent or delay nursing home placement at dis-
charge;
6. Determine patient satisfaction with hospital discharge planning;
7. iDescribe the discharge planning process through observation;
8. Survey hospital discharge planners regarding their comfort with the
responsibility of housing placement at discharge; and
9. Recommend further quantitative or qualitative research to follow-up
on the findings from this exploratory research.
Anticipated Impact of the Intervention
The intervention of a case manager, familiar with the full array of in-home
support services and the variety of housing alternatives, will be able to prevent
unnecessary nursing home placement for a percentage of the older adults partici-
pating in this research. Further, it is anticipated that a case manager following
older adults for!;eight weeks after discharge, will encourage the movement of
patients to less restrictive and less costly housing options as their recuperation
10


progresses. Third, it is anticipated that gender and marital status are predictors of
' 1 1
nursing home placement with unmarried women, who do not have a caregiver at
: i'
home, as the most likely individuals to enter a nursing home at hospital discharge.
Fourth, it is anticipated that variations will occur in the degree of satisfaction with
the discharge: planning process. Demographic data from this research will be of
interest in order to target the population which will receive the greatest benefit from
future policy changes. Finally, it is anticipated that hospital discharge planners are
better prepared! to make referrals for home health services or nursing home care
and less prepared to select housing alternatives.
The next section of this introductory chapter describes the methodology or
:i
'll
investigative procedures used to conduct the research. Both qualitative and
quantitative data were collected. Chapter 2 reviews the contemporary research on
lj
Medicare cost containment, the impact of Medicare prospective reimbursement on
; ,' :i
j
nursing homes and on hospital discharge planning, and a rationale for the case
.j
management intervention. Research results are presented in Chapter 3. The
;i
results include patient characteristics of the sample, predictors of housing place-
ii
i 'i
ment at hospital discharge, predictions of housing level eight weeks after dis-
charge, a comparison of hospital differences in housing placement, the effects of
case management intervention, patient satisfaction with hospital discharge planning
services, and: flip perception of discharge planners regarding their services.
, 'i
, ii
The final chapter reviews the conclusions of the research and discusses the
-'I
;i
research implications. A series of recommendations for future research and public
11


policy revisions were incorporated to influence public policy change as a result of
this research.
Hi Investigative Procedures
This research involved three components. The effects of a case manager
on the discharge practices of the hospitals were evaluated. Qualitative research
data were collected to describe the hospital discharge planning process. Descrip-
tive data were collected on persons over the age of 75 admitted to five hospitals in
metropolitan Denver. Data on patient satisfaction with discharge planning were
collected and the perceptions of hospital discharge planners regarding their
services were evaluated. The methods used are described below. Preceding each
section is an overview of the procedures used for that segment of the research.
Table 1.1 describes the research objectives, data collected and the method of data
I
collection.
Descriptive Data Collection
Five hospitals in the Denver metropolitan area participated in the study.
The 22 hospitals in the Denver metropolitan area were invited to a briefing on the
research; six! hospitals self-selected their facility for participation. Five diverse
hospitals were chosen. The hospitals are representative of large, medium and
small urban hospitals and a psychiatric hospital. The participating hospitals were
Presbyterian/St. Lukes, Mercy Hospital, St. Anthonys Central, St. Anthonys North,
and Mt. Airy. Table 1.2 shows the number of beds and the number of discharge
planners at each participating hospital.
12


Table 1.1. Research Objectives and Methods of Data Collection.
Objective Data Collected Method of Data Collection
Determine dischargejplanners per- ceptions of the quality of their post- hospital in-home and; placement ser- vices. Ratings on hospitals ability to provide the following discharge services to frail elderly: immediate housing refer- ral at discharge, housing referral 2 months after discharge, mental health, home health, family counseling and referrals for other human services. Questionnaire administered to discharge planners at each participating hospital. Six different types of service assessed. (See Appendix G).
Determine which patient variables predict nursing hbmd placement. Housing level at admission, gender, age, marital status and functional health rating. Patient discharge abstract completed upon admission at hospital (See Appen- dix A).
Compare housing levels at discharge, two weeks after discharge and eight weeks after discharge. Address at admission, discharge ad- dress and phone #, name of facility where patient is discharged, address at 2 weeks and housing level reported at end of 8 weeks. Patient discharge abstract. (See Appen- dix A).
Compare the number of hospital visits made at 2 weeks and 6 weeks after discharge controlling'for functional health. Functional health of patient, number of hospital visits cited on abstract at 2 weeks and 8 weeks. Functional health reported on patient abstract. Number of hospital visits re- ported in 2 week follow-up and 8 week follow-up conducted by telephone inter- viewer. (See Appendix C and D).
Determine the impact!the case man- ager had on housing level at dis- charge, 2 weeks after discharge and 6 weeks after discharge. List of patients seen by the case man- ager. Housing level of patients at discharge, 2 weeks after discharge and 8 weeks after discharge. Case notes taken by case manager. Housing level reported in 2 week and 8 week follow-up. (See Appendix C and D).
Describe the hospital discharge plan- ning process. Observation on-site for two days at a local hospital. Observation during data collection at the 5 participating hospitals. Extensive notes about observations. Unstructured questions.
The five participating hospitals discharge approximately 3,160 patients
monthly of which 34 percent (1,086) are Medicare discharges. The hospitals were
uncertain how many Medicare discharges were patients age 75 or older.
A brief abstract was attached to the chart of persons over age 75 admitted
to the five hospitals. The abstract, filled out by the patients discharge planner,
included information about the patients age, gender, marital status, housing at
;i!
admission, housing at discharge, and a general health rating. Two weeks after
h
13


Table 1.2. Hospitals Participating in the Research.
Total Discharaes Number of Medicare Number of Discharoe
' j'l Hospital Licensed Beds Per Month Discharaes Per Month Planners
Presbyterian/St. Lukes 465 662 224 3
Mercy 386 409 218 4
St. Anthony's Central 698 1,544 495 9
St. Anthony's North 196 435 139 3
Mt. Airy 100 110 10 5
discharge, patients were contacted by telephone to request information about the
number of doctor visits and the number of hospital visits since discharge, and their
satisfaction with the discharge process. Eight weeks after discharge another
telephone call was made to each patient to request the same information in
addition to their current housing status. Procedures used to meet the challenges of
telephone data collection with elderly persons who experience hearing difficulties
included simplified questions, slower conversations, and the use of informants.
Subjects: Sampling Procedures and Description
The population or universe is the total number of Medicare recipients age
75 and older who are admitted and discharged from hospitals in the Denver
14


metropolitan area. The sample for this research consists of all the Medicare
recipients age 75 and older who were admitted to five metropolitan Denver area
hospitals over £ix months. Data was collected over a six month period of time on
all admissions to five hospitals in the Denver region who were at least 75 years of
age and were funded by Medicare. A total of 1,089 abstracts were collected by the
hospitals for this research; 1,040 had sufficient information for inclusion in the
study.
Admissions staff in each of the five hospitals were responsible for attaching
an abstract data collection form (see Appendix A) to the chart of each patient age
75 and older on Medicare. Practices differed considerably, however. One hospital
required patients to sign an informed consent form in the admissions office before
l
an abstract could be attached to their chart to begin data collection procedures
(see Appendix B). Another hospital relied initially upon the Medical Records staff
to complete the data from the chart after the patient was discharged. In this
hospital, after several charts with abstracts were in Medical Records with no
progress toward data recording, a new policy was implemented. The department in
which the patient was treated became responsible for completing the forms, at the
request of the social service staff who were the liaisons to the project. A sufficient-
ly large number of data points were collected to assume that the data will provide a
useful profile of admittees in the targeted group age 75 and older.
Measures
The measurement instrument used in this portion of the research consisted
of a data collection form (abstract see Appendix A) which was completed in three
15


stages. The first stage was completed by a hospital staff person (the intent was for
it to be the discharge planner although some were completed by other staff as
described above). The form requested the name, address and telephone number
of the patient, age, gender, marital status, a global health rating at discharge (on a
1 to 3 scale ranging from very good to very poor), and information about discharge
housing.
The second set of questions was completed (see Appendix C) based on
information received over the telephone from the patient (or in some cases an
l!
informant) two weeks after discharge. The patient reported the number of doctor
visits and hospital visits during the two week period since discharge. Patients also
were asked to rate their satisfaction with the hospital discharge planner.
The third series of questions were also completed during a telephone call
with the patient; or informant eight weeks after discharge (see Appendix D). Again,
patients were asked to report the number of doctor visits and hospital visits during
the eight weeks since discharge. They were also asked about their current
housing arrangement and the number of times they had moved since discharge. A
j
satisfaction rating with hospital discharge services was again requested.
Procedure
Once the initial set of information was provided by the hospital on the
abstract form, a research staff member went to the hospital to collect the forms. At
two hospitals, follow-up telephone calls were required to be made at the hospital so
no personal information about the patients was removed from the premises without
patient permission. For the remaining hospitals the abstracts were brought back to
16


the office. There were some cases in which the abstract was not received from the
hospital until after the second full week had passed. In this case the two week call
was not made,! but patients were contacted at eight weeks.
Follow-up telephone calls were made in the second week after discharge.
Each caller identified herself as a representative of the hospital in which the patient
had been treated. The callers were trained in the telephone protocol, and were
chosen for their excellent communication skills with the elderly in particular. One
caller, in charge of the data collection for the first several months, had served in
geriatric social services for over ten years. The other caller was a graduate
student in a social work program with an emphasis in geriatrics.
Relying upon telephone contact to gain information made the large number
of follow-up contacts possible. Face to face visits on the large subject population
were considered impossible. Informants were used when the patient was incapa-
ble of providing the information. In some cases this was a family member or
neighbor. In nursing homes it was often a staff person who used his or her
recollection or the patient chart to answer questions about the number of doctor
and hospital visits. Gathering follow-up data from nursing home patients was
1 '1
'i
particularly challenging as the information was not readily available in a single
place (e.g., the patient chart may have been at the nurses station, or the social
worker may have maintained such records in his or her office). It was useful to rely
upon a single source within the nursing home for all data collection whenever
possible.
17


Once data collection was complete (including the two week and eight week
follow-up telephone calls), patients housing was placed into categories (e.g., own
home, own home with services, congregate housing, or nursing home.) Abstracts
were prepared for data entry by coding all information into numerical codes (e.g.,
hospitals were assigned numbers). Before submitting the abstracts to the data
enterer, all personally identifying patient data (names, phone numbers, and
addresses) were blackened with heavy markers. In cases where calls were made
from the hospital buildings, the identifying information was removed before the
abstracts were allowed to leave the hospital.
Data were entered on microcomputers using "Lotus 2.0" software. An
I
acceptable range was defined for each variable in order to minimize data entry
errors. Data were analyzed using Statistical Packages for the Social Sciences,
Form "x" (SPSSx). Subjects for whom no clear age information was documented
were removed from the sample, and missing data were left missing on a variable
by variable basis. No substitutions were used.
Case Management Intervention
During the middle two of six months of data collection (as described above)
in each hospital* a case manager was available to the discharge planning depart-
ment of the hospital. In the three hospitals which made use of the case managers
services, direct referrals by discharge planning staff appeared to be the most
frequent way of using the case manager. The case management service consisted
of assessment (of functional abilities, resources, and patient and family preferenc-
es), housing placement services (identifying appropriate types of housing, gathering
18


' li
information on availability in particular housing sites, and in some cases, facilitating
the move), and follow-up services for up to two months after discharge (assess-
ment of housing appropriateness, and facilitating a new housing placement if
appropriate.)
The data collection described above was carried out over a six month
period in each hospital. This period was divided into three phases: baseline data
collection, intervention, and post-intervention. The case management intervention
occurred during the third and fourth months of data collection in each hospital.
During these two months, a case manager was available to receive referrals for
direct intervention or on a consultative basis from the discharge planners of the
i!
hospital (including social service staff, physicians, nurses, etc.).
Subjects
All patients age 75 and older who were on Medicare at hospital discharge
were targeted for this research. All patients on whom abstracts were obtained (as
described above under the Descriptive Data Collection system) during months
three and four at each hospital were included in the "Intervention" data. In order to
ensure internal;: validity, the homogeneity of patients was compared from pre-test to
post-test (the post-intervention phase).
Of the 1,040 Medicare admissions over age 75 sampled, 62.7 percent were
female. A majority were widowed (58 percent), although 33.5 percent were
married. Consistent with national demographic trends, males were far more likely
to be married with a living spouse than females (57 percent and 18 percent
respectively). The average age of admittees was 82.2 (SD=5.4), with 30.9 percent
19


in the most frail 85 and older age range. The oldest age groups were most likely
to be female and widowed. Table 1.3 provides detailed demographic information
on the sample.
Demographic information is presented separately for each hospital in Table
1.4. As is evident, there are no differences in frequency of admissions at each
hospital by gender, or marital status (chi-squares are non-significant). The hospital
samples differ on age (as an interval variable; F=5.48; df=3.1036; p<.001) and
j:
functional heailth (F=3.84; df=3.752; p<.01), demonstrating the variability in patient
pools from which hospitals admit (age means range from 81.5 to 82.9 and function-
al health means range from 2.1 to 2.4). A functional health rating of 2 represents
patients with minor illness or disease; a rating of 3 represents significant illness or
disease. Variability in functional health from a mean score of 2.1 in one hospital to
2.4 in another hospital reflects a greater number of older patients with significant
illnesses in the hospital with a mean functional health score of 2.4.
' n
' iii
Housing at Admission and Discharge
Almost three-fourths (72 percent) of frail elderly were admitted to the hospital
from their own homes, but less than half (44 percent including 9.2 percent using in-
home services) were able to return to their own homes. (See Table 1.5). Thus,
discharge services included aid with housing placement in over one-fourth of all
frail elderly hospital admissions.
It is important to recognize that admission and discharge housing information
were collected by hospital staff who provided addresses and, where appropriate,
names of housing units, but these data were not initially recorded by the housing
20


Table 1.3. Demographic Characteristics of Admissions Over Age 75 at 5 Denver
Hospitals.
Gender N %
Male 386 37.3
Female 650 62.7
Aqe
75-79 396 38.1
80-84 323 31.0
85-89 202 19.5
90-94 95 9.1
95-99 24 2.3
100+ 0 0
Marital Status
Married 340 33.5
Widowed 589 58.0
Divorced/Separated 52 5.1
Never Married 35 3.4
Housinq Level
Own home 689 68.8
Own home with services 32 3.2
Relatives home 30 3.0
Congregate housing 48 4.8
Assisted living 9 0.9
Nursing home 194 19.4
21


Table 1.4. Demographic Characteristics by Hospital.
_________________HOSPITALS______________
1___ 2 3-4 ___5
Gender N % N % N % N %
|i Male '! 128 37.2 70 33.7 181 38.5 7 50.0
Female 216 62.8 138 66.3 289 61.5 7 50.0
Age
75-84 235 91.1 131 92.3 342 91.9 11 100
85-94 17 6.6 11 7.7 27 7.3
95 + 6 2.3 3 .8
Marital Status
Married 109 32.1 62 30.1 164 36.0 5 35.7
Unmarried 231 67.9 144 69.9 292 64.0 9 64.3
categories as used in this study. Research staff assigned the housing to catego-
ries. Because addresses of housing units which could not be identified (either on
the abstract or from lists of housing types) as some particular unit were automati-
cally assigned "own home," the category "own home" likely represents an inflated
figure.
An increased number of persons (31.7 percent compared with 20.3 percent
at admission) were released to an environment with strong supportive self-care
and/or health care services (assisted living facilities, rehabilitation or extended care
22


Table 1.5. Housing Levels at Admission, Discharge, and Eight Week Follow-up.
Admission Discharge 8 Weeks
Housina Level N % N % N %
Own home Own home with Services 689 68.6 445 44.0 218 33.9
32 3.2 93 9.2 146 22.7
Congregate 48 4.8 20 2.0 16 2.5
Relatives Home 30 3.0 62 6.1 39 6.1
Assisted Living 9 .9 9 .9 10 1.6
Rehab/Extended Care 52 5.1 1 .2
Nursing Home* 195 19.4 255 25.2 156 24.3
Hospital 5 .5 2 .3
Died 71 7.0 55 8.6
Total 1,004 100% 1,012 100% 643 100%
Includes in-patient hospice
facilities, nursing homes, or hospitals). Note that 7 percent of the sample died
while hospitalized. (This percentage may be artificially low because several
abstracts were submitted for persons who died during hospitalization without
ji
sufficient information for inclusion in the study).
Measures
The effectiveness of the intervention was evaluated by analyzing for
differences in the data collected at the two and eight week follow-up contacts,
across the phases of the project. It was expected that the case manager's
presence at the hospital would have an impact on the patients discharge plans
because of her specialty knowledge, and because she would be able to track the
patients for two months after leaving the hospital to ensure follow-through of
service referrals and, when necessary, to assist patients in moving from one type
23


of housing to another. Thus, the effectiveness of the intervention was analyzed by
1
comparing all discharges from the hospitals during the baseline and post-interven-
tion phases with the discharges during the intervention phase on the outcome vari-
ables. A more specific analysis was also conducted to determine whether patients
assisted directly by the case manager differed on the outcome variables.
;i
' ij
Design
A multiple-baseline design was used to pace the onset of data collection
i '1
and intervention procedures at the hospitals. A multiple-baseline design is a
"single subject design in which the treatment condition is successively administered
to several subjects or the same subject in several situations after baseline behav-
iors have been recorded for different periods of time" (Christensen, 1991, p. 344).
By the use of the pre-test, intervention, post-test design, behaviors exposed to the
treatment, which is a case manager, while all others remain at baseline, provides
some evidence for the effect of the intervention. "It becomes increasingly implausi-
ble that rival hypotheses would contemporaneously influence each target behavior
at the same time as the treatment was administered" (Christensen, 1991, p. 345).
The first hospital completed baseline data collection and was ready to
initiate intervention before the second hospital became involved with the project.
The schedule of, the project was established to ensure six months of data collection
in each hospital, followed by two months of follow-up data collection (by telephone).
The purpose of the multiple-baseline design (staggered timing of data collection
and intervention) was two-fold: 1) to allow the case manager to be full-time at
each hospital during its intervention phase, and 2) to control for industry-wide policy
24


changes which might coincide with one phase of the project (e.g., changes in
reimbursement procedures or discharge policy) and thus might be a confounding
cause for any differences found among the phases.
Delays in! the process of contracting with the five hospitals for their partici-
pation resulted in a shortened data collection period for the research. This neces-
sitated adjustments to the data collection periods in some hospitals, and required
the case manager to divide her time between two hospitals for a portion of the
intervention periods as shown in Table 1.6.
Table 1.6. Multiple-Baseline Design.
i Hospital 1 Hospital 2 Hospitals 3 & 4 Hospital 5
Pre-Test 4/01 8/30/88 5/01 7/31/88 7/15 8/30/88 3/21 5/07/88
Intervention ' !L 8/01 9/30/88 9/01 10/31/88
Post-Test 10/01 11/15/88 11/01 12/31/88
These modifications did not compromise the intent of the multiple-baseline
design, and the| case managers report was that the double assignments to
hospitals was pot an undue strain.
Procedure ; <;
A meeting of discharge planners from hospitals throughout the eight county
i
Denver region was called to initiate interest in the project. A letter describing the
project and requesting participation was mailed to the administrative head of the
Discharge Planning department in all 22 hospitals in the region. The scope of the
25


project was described to the attending discharge planners who were encouraged to
contact their hospitals administrator indicating their level of interest. Six hospitals
:i!
, \\
expressed interest in the project. One hospital, Rose Medical Center, was not
j
chosen since the hospital followed patients after discharge and the research results
could have been affected due to procedural differences at this hospital. Five
hospitals self-selected to represent a diversity of organizational characteristics, as
r
well as patient jCharacteristics. The participating hospitals were Mercy Hospital, Mt.
V
Airy Psychiatric Hospital, Presbyterian/St. Lukes Hospital, St. Anthonys Hospital
North and St. Anthonys Hospital Central. Agreements with each hospital were
;' ,j!
negotiated to define the parameters of participation. They included an agreement
about the hospital's responsibility to participate in data collection and intervention
for which they would receive payment of one dollar per abstract collected. A
l1
' I,
liaison was appointed from each hospital to coordinate the data collection and
intervention phase.
Much responsibility for ensuring the case management services and data
< 'i
collection fell to the hospital liaison, the case manager and the two persons making
the follow-up calls (who tracked the data). The case management intervention ar-
rangement whibh appeared to be most effective was direct referral from social
services or discharge planners (of any discipline). A direct referral allowed the
case manager to contact the patient or family on the floor of the hospital and
initiate an assessment at that time.
I'
26


The case managers activities included assessment, housing placement,
and referral for services. In addition to these discharge services, the case manag-
er was able to maintain contact with the patient and family for as long as two
i 'I
months to ensure the follow-through of the service referrals. The case manager
also re-evaluated housing needs, and facilitated additional moves to result in an
appropriate living environment for the longer term.
It is important to acknowledge the diversity in the time required by different
patients. For some clients, 20 hours of work was required to assess, track, and
implement their housing and service needs. It appears that if the case manager
had been used extensively by all hospital staff, a second case manager would
have been needed due to the amount of time required for many patients.
Following the intervention phase, hospitals continued collecting data for two
months during the post-intervention phase. During this period, the case manager
was no longer on-site to work with hospitalized patients, but was involved in
tracking the adjustment of patients with whom she initiated contact during the
intervention phase. The same case manager was consistently used throughout the
f il;
research to eliminate assessment and referral biases across case managers.
ji
In order to prevent problems with external validity, five diverse hospitals
were selected and the limited timeframe for conducting the research was manage-
able since a longer timeframe could contribute to changes in staffing or hospital
policies. The same individuals conducted follow-up throughout the research to
prevent variations in coding. To ensure homogeneity in the sample, the study was
limited to the 75 and older population. Although more detailed health status data
27


would have beriefitted the results, the research was designed to ensure as much
convenience as; possible for participation; a one dollar fee was paid to each
hospital as an ihcentive to complete the data abstracts. The hospitals were
!' I;
geographically located around the region to ensure diversity in neighborhoods,
service options, and patients. Appendix E is a map showing the locations of the
participating hospitals.
Qualitative Data
!i:
The exploratory nature of this research provides preliminary data from which
further quantitative analysis can be conducted. The qualitative research compo-
nent provides another source of data through close-up, first-hand inspection of the
discharge planning process. A number of principles surrounding qualitative
' i
I
research apply here (Van Maanen, 1982). The discharge planning process was
!| li
more dynamic and less formally structured than originally anticipated. Qualitative
research provided an opportunity for "analytic induction" or first-hand inspection in
the hospitals. Due to the hospitals' proximity and the ability to observe normal
behavior in a discharge planning environment, the data interpretation and recom-
' ii,.
mendations for further research were positively impacted.
Qualitative data were collected during the research at the five participating
hospitals. In addition, observation time was spent at another suburban hospital to
describe the hospital discharge planning process, the work environment, and to
observe opportunities which could positively impact the discharge process for older
i n'
adults. The results of the qualitative data collection are summarized in Chapter 3.
28


CHAPTER 2
ANALYSIS OF CONTEMPORARY RESEARCH ON MEDICARE
COST CONTAINMENT AND THE IMPACT ON HOSPITAL
DISCHARGE PLANNING AND NURSING HOME ADMISSIONS
This review of contemporary research and literature includes demographic
projections for; the older population in the Denver metropolitan area, a review of the
Medicare program, a discussion about major transitions in federal Medicare
policies, legislative targets for control of Medicare costs, Medicare policy and its
ii'
ii1.
: 1 1
impact on nursing home admissions and hospital discharge planning, housing very
old patients after hospital discharge, and a rationale for case management inter-
vention.
Demographic Projections
The oldef population is growing and is expected to continue to grow in the
future. The general population in the metropolitan Denver region is expected to
grow by 39.8 percent from 1988 to 2010 (Table 2.1) while the age 60 and over
!
population will grow by 80.5 percent during the same time period (Table 2.2).
i
The age 60 and older population is growing at twice the rate of the general
i
population. The':substantial growth in older adults is a national phenomenon; one
that concerns policymakers and managers who consider the corresponding health
,i
care costs. In Colorado, over half (53 percent) of the older population resides in
; jl
1'
the eight county;metropolitan region. This concentration of older adults impacts


Table 2.1. Denver Metropolitan Area Forecast Absolute and Percent Change of
the Total Population: 1988-2010.
COUNTY 1988 TOTAL POPULATION 2010 TOTAL POPULATION ABSOLUTE CHANGE PERCENT CHANGE
ADAMS 273,300 433,100 159,800 58.5%
ARAPAHOE 398,650 579,500 180,850 45.4%
BOULDER 221,650 302,000 80,350 36.3%
CLEAR CREEK : 8,500 14,000 5,500 64.7%
DENVER 508,150 573,100 64,950 12.8%
DOUGLAS 50,200 195,700 145,500 289.8%
GILPIN 3,500 6,100 2,550 71.8%
JEFFERSON 432,100 546,500 114,400 26.5%

TOTAL 1,896,100 2,650,000 753,900 39.8%
Note. Calculated from DRCOG, 1988 Population and Household Esti-
mates. (Tables 5 and 12) 1988, Denver: Denver Regional Council of
Governments and 2010 County Population Forecasts by Age. 1989,
Denver: Denver Regional Council of Governments.
Colorados Medicare, Medicaid and health care expenditures. Therefore, the eight
county metropolitan area and the fastest growing component of the older popula-
tion, those age 75 and older, are targeted for this research. The metropolitan
region includes Adams, Arapahoe, Boulder, Clear Creek, Denver, Douglas, Gilpin
and Jefferson counties.
Table 2.3 reveals the significant growth in the age 75 and older population
from 1988 to 2010. In 1988, the eight county Denver metropolitan area was home
to 66,900 adults age 75 and older. By the year 2010, this age group is expected to
! 30
I


, >1'.
i Mi.
Table 2.2. Denver Metropolitan Area Forecast Absolute and Percent Change of
the! 60+Population: 1988-2010.
COUNTY '] 1988 60+ POPULATION 2010 60+ POPULATION ABSOLUTE CHANGE PERCENT CHANGE
ADAMS 29,546 58,483 28,937 97.9%
ARAPAHOE :: 38,156 93,575 55,419 145.2%
BOULDER 21,910 48,802 26,892 122.7%
CLEAR CREEK ! 886 2,039 1,153 130.1%
DENVER 94,675 105,577 10,902 11.5%
DOUGLAS 94,675 15,272 11,951 359.9%
GILPIN ; 358 1,084 726 202.8%
JEFFERSON t 48,330 103,391 55,061 113.9%

TOTAL < 237,182 428,223 191,041 80.5%
Note. Calculated from DRCOG, 1988 Population and Household Esti-
mates. (Tables 5 and 12), 1988, Denver: Denver Regional Council
pf Governments and 2010 County Population Forecasts by Age.
1989, Denver: DRCOG.
i
r-
1
grow to 115,183 representing a 72 percent increase. This research focuses on the
age 75 and oljder population for three reasons. First, its a growing segment of the
older population. Second, the age 75 and older population is likely to experience
more than one chronic health condition requiring support services after hospital
discharge. f
Third, the population age 75 and over, only five percent of the total popula-
tion, accounts for 16 percent of the hospital discharges and 22 percent of all
hospital days (National Center for Health Statistics, 1990). Growth in the age 75
and older population will precipitate increased utilization of health care services
31


Table~2:3~7b+ Population 1'988-gOTOr
1988 60+ Population 1988 75+ Population % Of 60+ Population 2010 60+ Population 2010 75+ Population % Of 60+ Population Absolute Change 75+ Population 1988-2010 % Change 75+ Population 1988-2010
ADAMS 29,546 6,664 22.6 58,483 16,341 27.9 9,677 145.2
ARAPAHOE 38,156 8,375 21.9 93,575 23,140 24.7 14,765 176.3
BOULDER 21,910 6,735 30.7 48,802 " 11.345 23.2 " ^ 4,610 68.4
CLEAR CREEK 886 250 28.2 2,039 401 19.7 151 60.4
DENVER 94,675 32,607 34.4 105,577 33,498 31.7 891 2.7
DOUGLAS 3,321 813 24.5 15,272 2,980 19.5 2,167 266.5
GILPIN 358 126 35.2 1,084 282 26.0 156 123.8
JEFFERSON 48,330 11,330 23.4 103,391 27,196 26.3 15,866 140.0
TOTAL 237,182 66,900 28.2 428,223 115,183 26.9 48,283 72.2
Note. Calculated from DRCOG. 1988 Population and Household Estimates. (Tables 5 and 12). 1988. Denver: Denver
Regional Council of Governments and 2010 County Population Forecasts bv Age. 1989, Denver: DRCOG.


1 !'-
i!
plus increased! Medicare and Medicaid expenditures. Densen (1991) described the
11!
movement of individuals through the health services network to demonstrate the
i'
different utilization patterns for the 65 to 74 and the 75 and older age groups.
Figures 2.1 and 2.2 reflect a much higher health service utilization frequency in the
75 and older population. The difference was primarily in the utilization of hospitals
and nursing homes. Densen identifies hospitals as the major pathway to nursing
'', i;
homes. ;
In Figure 2.1, Densen follows 100,000 older adults age 65 to 74. Of the
100,000 individuals, 850 enter a nursing home from an acute care hospital and 400
- i;
l!
enter the nursing home from their own home. These admission rates increase
substantially in the age 75 and older population.
In Figure; 2.2, Densen tracks 100,000 older adults who are age 75 and
older. Of these 100,000 adults, 5,400 will enter a nursing home from an acute care
hospital and 3,100 will enter the nursing home from their own home. These figures
reflect the rationale for targeting the 75 and older population and the hospital
i'
discharge process for further research.
, i
A large portion of national health care costs is accrued by older adults in
hospitals and nursing homes. The largest proportion went to cover hospital care
with nursing home and physician care as the next two largest costs.
ij;
Older adults paid a slightly higher share ($73 billion) of the health care
costs than Medicare ($70 billion). Expenditures for the elderly were largely for
"other care" and nursing home care, with physician services ranking third in the
33


hgure 2.1. Annual Movement ot Persons 6b-74 through the Health uare bystem.
- Movement to more restrictive-intensive care setting.
----- Movement to less restictive/mtensive care setting.
Note: From Tracing the elderly through the health care system: An update (p. 6) by P.M. Densen, 1991, Rockville,
Maryland: U.S. Department of Health and Human Services.
CO
4S.


figure-2.2. Annual Movement-of-Persons-75 and Over-through the Health Care System:
----- Movement to more restrictive intensive care setting.
----- Movement to less resticdve intensive care setting.
CO
Cfl
Note: From Tracing the elderly through the health care system: An update (p. 7) by P.M. Densen, 1991, Rockville,
Maryland: U.S. Department of Health and Human Services.


Medicare program. Over $70 billion of the total health care costs of $175 billion
' 1
went for hospital care. As expected, Medicaid funds were primarily expended on
l'
elderly nursing home care ($13 billion out of $20.7 billion).
Though: the rate of increase in the Medicare program has slowed in the past
'' 'jj
few years, both Medicare and Medicaid pay a large portion of the health care costs
for older Americans. Unfortunately, the costs are shifting from Medicare to Medic-
aid and the older consumers. "Out of pocket health care costs for the elderly have
more than doubled since 1980 and more than tripled since 1977" (U.S. House of
Representatives, 1989, p.8).
11 ii
As the primary funding source for health care of the elderly, Medicare
coverage becomes increasingly important. "Medicare, which pays the majority of
health care costs for older Americans, represents the largest health care expendi-
ture for the federal government" (Schneider & Guralnik, 1990, p. 2337). The age
75 and over Medicare population at hospital discharge were targeted for this
research due to the greatest potential for impacting the high cost of nursing home
care if admission was prevented.
The Medicare Program
Basic Components of Medicare
This section describes the basic components and the financing of the
Medicare program. Authorized by Title XVIII of the federal Social Security Act,
Medicare assists elderly and disabled people with payments for their health care.
The program provides two basic forms of protection: Medicare Part A and Part B.
, '' i|
A description of each follows.
36


Medicare Part A, Hospital Insurance, financed primarily by Social Security
,,l: Hi
: 'll
payroll taxes, covers in-patient hospital services, and post-hospital care in skilled
nursing facilities. Part A covers 31.2 million enrollees, and benefits amount to
about $49 billion. About $45.6 billion (93 percent) of Part A expenditures are for in-
patient hospital services (U.S. General Accounting Office, July 1988). Eligibility for
the Part A Hospital Insurance Program is based upon Social Security or Railroad
Retirement benefits provided the individual is age 65 or older or provided the
person is disabled for over 24 months.
Medicare Part B, Supplementary Medical Insurance, a voluntary program
financed by enrollee premiums (25 percent of total costs) and federal general
revenues, covers physician services and a variety of other health care services,
such as laboratory and out-patient hospital services. In fiscal year 1986, Medicare
'i
Part B covered'30.6 million enrollees and benefits totaled abut $25.9 billion (U.S. .
General Accounting Office, July 1988). To qualify for the Part B Supplementary
Medical insurance Program, disabled persons or individuals aged 65 and older
must request coverage and pay a monthly premium. Individual fees cover about a
fourth of the program cost; the federal government pays three-fourths through
jh
general revenues. Prior to October 1983, hospitals were paid based upon complex
Medicare formulas. Medicare theories in the 1960s and 1970s primarily focused
>i
.1
on increasing patient access to services, increasing the range of providers in every
community and ensuring quality standards. Policies did not encourage hospitals to
restrain costs. The next section describes the policy changes in the Medicare
'''' ii1
program. !
37


Transitions in the Medicare Program
Although Medicare offers benefits for over 33 million older and disabled
beneficiaries; Medicare is an increasing target for federal deficit cutters. Medicare
is only one heklth care benefit but its cost to taxpayers of over $108 billion annually
keeps it at the top of government agendas.
The causes of the transitions in the health care system are multifaceted.
Table 2.4 reveals the factors causing changes in health care and the strategies
introduced to contain costs. As a major buyer of health care, the government
shifted to prospective reimbursement to control the rising costs of Medicare.
A recent article in the Journal of the American Medical Association de-
scribed the rising Medicare cost projections. As the population ages, Medicare
costs per person increase. Older adults aged 65 to 74 years annually cost
Medicare an average of $2,017; this cost increases to $3,215 for the 85 and older
age group. Schneider and Guralnik claimed "the total cost of Medicare rises
impressively during the upcoming decades, nearly doubling (in 1987 dollars) to the
: 'ji
year 2020. The greatest proportional increases are observed in the oldest age
groups," those .age 75 to 85 and older (Schneider & Guralnik, 1990, p. 2337).
Given these costs, Schneider and Guralnik predict the level of Medicare spending
in 2040 to range from $147 to $212 billion (in 1987 dollars).
j'
The Medicare program is only two decades old. However, major demo-
;if
graphic and technological changes continue to concern public policymakers. As
previously demonstrated, the older population continues to live longer and increase
38


'I
Table 2.4. Role of Major Factors Affecting Health Care Transitions.
Maior Buyers Trigger Factors Cost-Containment Strategies
Government; |! Medicare cost rise Federal deficits Social Security bankruptcy Shift to prospective payment Freeze physician fees Reduce Medicaid funds
Business 1981-83 recession Health expenses rise 15- 30% per year Use of HMOs/PPOs Form employer health coali- tions Reinstall employee front-end deductibles and co-insurance
Insurance J Hospital costs rise 15-30% per year No effective controls over hospital and M.D. use Develop HMO/PPO contracts Concentrate on administra- tive services to employers Require second opinions
1 Consumers ; iji i1 Increasing out-of-pocket costs Rising co-insurance Malpractice Enroll in HMOs Engage in fitness/weliness programs Form consumer advocacy coalitions
Integrated Health Plans 1; Fee-for-service system not cost-competitive Rising HMO enrollment Physician surplus creates labor pool Form national HMOs/PPOs Create new alliances be- tween providers and insur- ance companies Mainstream MD's join HMOs/PPOs
Note. From Overview: Environmental forces and trends (pp. 11-21) by R.C. Coile,
Jr., In Managing the Continuum of Care by C.E. Schwick & L.J. Weiss
(Eds.), 1987, Rockville, Maryland: Aspen Publishing, Inc.
i|
39


y ill
in significant numbers. Many new medical procedures are available to prolong the
H|
lives of our citizens and the price of medical care continues to escalate. This
;|i
combination 6f ifactors calls for new theories and approaches to health care for the
' ;i|
elderly. Since charges for hospital care are approximately two-thirds of the medical
!'i
care expenditures for older people, and since medical care costs continue to
increase at a more rapid rate than the Consumer Price Index, new theories were
considered to; cbntrol these escalating costs. A combination of factors precipitated
i'''
increasing Medicare costs and eventually led to the theories which promote cost
j |
containment.11 Tfhe factors which led to increasing Medicare costs were the growth
in the Medicare! eligible population, drastic increases in medical malpractice
insurance prices, increased physician charges, escalating hospital prices as a
: >j;
il
result of lower in-patient usage patterns, and increasing labor and equipment
'
prices.
' !!
Medicare Cost bontainment
Medicare cost containment has been a focus of the federal administration
for the past fifteen years. The Nixon Administration froze all health care costs for
i,
one year. In order to control rising costs in the Medicare program, President
ii
I1
Jimmy Carter proposed a mechanism which would control costs by limiting hospital
ii
, ii
expenditures. | Congress did not support the Presidents theory; however, Congress
was concernedljabout Medicare costs and requested a study on prospective reim-
:! ii'
bursement for hospitals as a theory which would result in controlled hospital costs.
The Diagnosis Related Groups (DRGs) were established. (McGuiness, 1989)
40


As a result, the Medicare program created 468 categories of illness called
ill
Diagnosis Related Groups. For the first time, hospitals were reimbursed on a fixed
fee for the diagnosis or category of illness (e.g., appendectomy) rather than the
number of hospital days or tests performed. The federal Department of Health and
r
Human Services determines the average cost of providing treatment for the
, ; il
i:
diagnosis and sets the hospital reimbursement rates. The theory was that a
prospective reimbursement system would create incentives for hospitals to shorten
the number of Ijiospital days and prescribe the minimum service for the patient. If
the hospital costs are less than the federal reimbursable rate, the hospital retains
the margin over cost. However, if the costs are greater, the hospital cannot charge
more than the fixed fee. The impact of this particular theory will be discussed
further in this chapter. Prospective reimbursement was just one of many major
federal policy changes which were enacted in the Medicare program from 1980 to
i \
I
1987. The following section describes the six major laws which the Congressional
'I!
Budget Office estimated would cumulatively reduce Medicare costs from 1981 to
1987 by $35:9 billion (U.S. General Accounting Office, July 1988).
The Impact of Major Legislation on Medicare Costs
I,
In 1988, the General Accounting Office presented a report to the Chairman
of the House of Representatives, Select Committee on Aging, regarding the effects
of federal legislation on costs to Medicare beneficiaries and the impact on federal
programs. This section summarizes the major findings of the General Accounting
I'
Office study.
!ji
I
41


The Congressional Budget Office claimed there was a slowdown in Medi-
. ;ji '
,i !l!
care Part A Hospital Insurance cost growth from 1981 through 1988 as compared
with 1970 through 1980. A decrease in the utilization of in-patient hospital services
and major legislative changes contributed to the slowdown. The Medicare Part B
Supplementary'Medical Insurance Program costs grew at the same rate during
fiscal years 1981 through 1986 as for the prior 10 year period. However, savings
from the legislative changes affecting Part B during the period were offset by higher
utilization of Part B services.
Five Of the six major laws enacted from 1980 through 1987 were expected
to result in Medicare savings; the other, the Omnibus Reconciliation Act of 1986,
was expected to increase program costs. The Omnibus Reconciliation Act (OBRA)
of 1980 was the first of the major laws enacted; the Congressional Budget Office
ii
estimated that its Medicare provisions would reduce program costs by about $2.3
billion during fiscal years 1981 through 1985. Table 2.5 contains a summary of the
1
six major laws,: the major provisions and the estimated cumulative savings project-
ed by the Congressional Budget Office (CBO) and the Health Care Financing
Administration "(HCFA). The Congressional Budget Office and Health Care
Financing Administration estimated cumulative savings for each of these six public
laws for fiscal years 1981 through 1987 at $35 billion and $28.9 billion respectively.
According to the General Accounting Office, from 1981 through 1986, the
average growth rate in cost per Medicare enrollee decreased by two percent; a
much slower growth rate than the average growth rate of 2.3 percent from 1970
1 ij.
through 1980. "Had the average annual growth rate in cost per enrollee for fiscal
42


Table-2:5. Estimated Medicare Savings frt>m Six Major Laws.
Law
Omnibus
Reconciliation
Act
Omnibus
Reconciliation
Act of 1981
Tax Equity and
Fiscal Responsibility
Act
Cumulative Savings
Date Enacted Major Provisions in Billions of Dollars
Fiscal Years 1981-87*
CBO HCFA
December 5, 1980 ~ Required that determination of Medicare reason- $2.3
able charges for physician services be based on
the date service was rendered rather than date
claim was processed. Law also made Medicare
secondary payer for people whose medical ex-
penses were covered by automobile or liability
insurance plan.
$.7
August 13, 1981 Reduced routine nursing salary cost paid to hospi- $3.2 $4.0
tals from 8.5% to a maximum of 5%. Increased
Medicare Part B deductible for subscribers from
$60 to $75 beginning in 1982.
September 3, 1982 Estimated to have the greatest impact on Medi- $23.1 $20.3
care costs. Established a target rate reimburse-
ment system for hospital services which limited
the rate of increase in Medicare payments per
case for a 3 year period beginning 10/1/82. Re-
quired employers to offer employees and spouses
age 65-69 the same health plans offered to youn-
ger workers.


Table 2.5. Continued.
Law
Deficit
Reduction Act
Consolidated
Omnibus Budget
Reconciliation
Act
Date Enacted Major Provisions
CBO HCFA
Medicare became second payer for older employ-
ees. Reduced reimbursement for radiologist/
pathologist services provided to hospital inpatients
from 100% to 80% of reasonable charges. In-
creased limits allowed for Medicare Part B premi-
ums. Eliminated the salary differential paid to
hospitals and skilled nursing facilities.
July 18, 1984 Established a reimbursement fee schedule for $6.1 $4.2
outpatient laboratory services. Froze physician
fees for a 15 month period beginning 7/1/84.
Required employer-sponsored group health plans
to cover employees spouses (65-69). Medicare
would become the secondary payer for spouses.
April 7, 1986 Reduced Medicare reimbursement to hospitals for $2.0 $1.4
the indirect costs of medical education. The pro-
spective payment rate system increases were
limited to 1%. For 1988 increases limited to in-
crease in the hospital market basket index. Ex-
panded coverage requirement for employer group
health plans to over age 69 so Medicare would
continue as secondary payer. COBRA added to
the program costs by increasing payments for
hospitals serving a disproportionate share of low-
income patients.


I able 2.5. Continued.
Law Date Enacted Major Provisions CBO HCFA
Omnibus Reconciliation Act of 1986 October 21, 1986 Extended Medicare Part B coverage of occu- pational therapy to include services provided in skilled nursing facilities. Made Medicare the secondary payeHor disabled beneficia- ries employed by large companies and who elect to be covered by the employers health insurance plans. The provisions in this Act were expected to increase program costs. $-1.0 $-1.0
Dollars in Billions TOTAL SAVINGS $35.9 billion $28.9 billion
Note. From Medicare and Medicaid: Updated effects of recent legislation on program and beneficiary costs (p. 19)
U.S. General Accounting Office/HRD 88 85, July 1988, Washington, D.C.
cn


years 1970 through 1980 continued through 1986, Medicare hospital costs would
have been about $17.3 billion more in constant 1986 dollars than they actually
were" (U.S. General Accounting Office, July 1988, p. 22). A decrease in the
number of hospital patient days controlled the growth rate in Medicare hospital
costs.
Two legislative changes, the Tax Equity and Fiscal Responsibility Act of
il1
1982 and the prospective payment system in the Social Security Amendments of
1983, gave hospitals incentives to reduce the length of Medicare patient stay. The
General Accounting Office analysis substantiates the cost savings and, thus, the
theory that prospective reimbursement to hospitals would save money in Medicare
costs. Prospective reimbursement under Medicare was viewed as so effective that
the same type of reimbursement for physicians will begin in 1992.
i The Impact of the Growing Older Population and
Medicare Policy Changes on Nursing Home Admissions
According to new estimates by the federal agency for health care policy and
research, 43 percent of all Americans who turn age 65 in 1990 (929,000 persons
nationally) will use a nursing home at least once before they die. Projections
indicate that over half the women and almost one-third of the men who reach age
65 in 1990 will use nursing homes. Increasing life expectancy will lead to a
gradual rise in the risk of nursing home use (from approximately 43 percent in 1990
!i i1
to 44 percent in 2020). By 2020, there will be 1.7 million Americans aged 65 who
eventually will enter a nursing home (Murtaugh, Kemper & Spillane, 1990). The
expected growth in demand for nursing home care has implications for government
46


policymakers concerned with supply and financing of long term care services. For
, i, | ::i
nearly a decade, public policymakers and analysts have studied the costs of
nursing home care.
In 1983, the General Accounting Office completed a report for the Subcom-
I'
mittee on Health and the Environment for the U.S. House of Representatives. The
v
report entitled Medicaid and Nursing Home Care: Cost Increases and the Need for
Services are Creating Problems for the States and The Elderly provided information
on the characteristics of nursing home residents, reimbursement policies, expendi-
tures and variations by state. Since the Social Security Amendments of 1983
(Public Law 98^21, Section 601), which created the prospective reimbursement
system for hospitals, was successful in reducing Medicare expenditures, this
theoretical review will consider the potential impact the legislation has had on the
patients, on other federal programs such as Medicaid, and on changes in the
hospital discharge planning process.
Public policymakers anticipated that the new hospital reimbursement system
would provide sufficient incentives and disincentives to decrease the number of
medically unnecessary hospital stays. In anticipation of other spillover effects in
the health care1 system, the General Accounting Office identified a few of the
1 1;
potential problems. "The DRG payment method may cause problems for patients if
they are discharged by hospitals too quickly to nursing homes which cannot
provide the levpl of care they require. Because of the DRG incentives, nursing
homes expect that the demand for their services will increase as hospitals seek
47


placement for convalescent Medicare patients" (U.S. General Accounting Office,
1983, p. 119). |
Shaughnessy and Kramer (1990) studied the patients problems to evaluate
the effects of Medicares prospective payment system and concluded that from
l
1982 to 1986 the needs of the patients in long-term care increased substantially.
'ii
This trend was Attributed to earlier hospital discharge to long-term care systems
and MedicaidS' policy of deinstitutionalization. Given the increased need for patient
care, Shaughnessy and Kramer called for a better system of reimbursing for long-
term care and ensuring its quality.
Hospitalized elderly are at high risk for poor post-discharge outcomes
because of decreased ability to adapt to physical and emotional stress (Johnson &
Fethke, 1985; Naylor, 1990).
...a key contributor to the institutionalization of persons aged 75 or more, in
combination with age and living in retirement housing, is a hospital admis-
sion. (This latter factor alone raises their chance of institutionalization within
7 yearsifrom 40% to 53%). It appears especially important to ensure that
such persons have their medical, physical, and mental functioning problems
thoroughly assessed and addressed prior to discharge and that special
attention be paid in planning their discharge so that arrangements are made
for follow-up care or support and for regular reassessments of their health
and social circumstances, if required. (Shapiro & Tate, 1988, p. 243)
Although this age cohort usually needs more assistance after discharge for a larger
period of time than the general population, this group is the least likely to have the
support systenj needed to assist them (Johnson & Fethke, 1985; Naylor, 1990).
Densen (1991) analyzed the percent of elderly hospitalized persons dis-
charged home and the percent discharged to a nursing home in Table 2.6. Older
adults enter nursing homes more frequently from hospitals than any other source.
48


Table 2.6. Percentage of Elderly Hospitalized Persons Discharged
Hohie and Percent Discharged to a Nursing Home by Age: 1986*.
Discharge Destination 65 & Over 65-74 75 & Over
Home ! 77.5 85.7 69.2
Informal Care 70.2 80.0 60.7
Home Carej Program 7.3 5.7 8.5
Nursing Home 10.2 3.9 15.9
Includes those discharged with and without referrals to a home care program.
Note. prom Tracing the elderly through the health care system: An update
(p. 9) by P.M. Densen, 1991, Rockville, Maryland: U.S. Department
of Health and Human Services.
About 4 percerit of the hospitalized 65 to 74 age group is discharged to a nursing
home while 16 percent of the 75 and older hospitalized elderly are discharged to a
nursing home. jiThe discharge location is of concern as is the length of stay in the
nursing home.
Ill
Pennsylvania hospital data from 1983, 1984 and 1985, the timeframe just
after implementation of the Medicare prospective payment system, revealed a
decline in Medicares average length of hospital stay by more than 20 percent
between 1983 and 1985. During the same time, Pennsylvania experienced a 36
percent increase in transfers to nursing homes, home health agencies, rehabilita-
tion centers an 19 percent of the discharged Medicare patients in Pennsylvania were transferred to
v,
49


a post-hospital, subacute care setting. Of these, approximately 40 percent went to
skilled nursing facilities" (Morrisey, Sloan & Valvona, 1988, p. 686).
A 1987 Journal of the American Medical Association report on discharge
l
data of patientsi hospitalized for falls and hip fractures revealed the magnitude of
the problem predicted by the U.S. General Accounting Office. The extraordinary
' f
growth in the nursing home admissions after the prospective reimbursement
payment system (after Medicare DRGs were implemented) is shown in Table 2.7.
" ij
Table 2.7. Impact of Prospective Reimbursement.
I' Pre-Prospective Reimbursement Post-Prospective Reimbursement
Length of Stay 16.3 days 10.3 days
# of Patient Sessions 9.7 4.9
Patients Discharged to Nursing Homes 21% 48%
Patients Still in Nursing Homes After Six Months 13% 39%
Note. From Journal or the American Medical Association (pp. 1762-66) by M.A.
Sager, E.A. Leventhal & D.V. Easterling, 1987, Chicago, Illinois: American
Medical (Association.
After prospective reimbursement, the number of patients discharged to
nursing homes doubled and the number of patients remaining in nursing homes six
i
months after hospital discharge tripled. Since the cost of monthly nursing home
care starts at $2,000 per month and since the average length of nursing home stay
50
;|i


is 2 to 5 years (U.S. General Accounting Office, 1983), its relatively easy to under-
: :i!
stand that older patients spend their resources within about 13 weeks (Estes,
1990). The various payment sources for nursing home care in 1988 are shown in
Table 2.8.
Table 2.8. Source of Nursing Home Revenues (Calendar year 1988).
Private Payments 51%
Medicaid 41.4%
Other 6%
i Medicare 1.6%
Note. From Congressional Research Services, cited in Nursing homes: Admis-
sion problems for Medicaid recipients and attempts to solve them (p. 11) by
U.S. Government Accounting Office, September, 1990, Washington, D.C.
Medicare paid less than two percent of the cost of nursing home care in
!i
1986. Fifty-one percent of the cost was paid by older patients. After patients
spend their financial resources down to about $2,000, the federal and state govern-
ments share the financial responsibility to ensure that Medicaid provides nursing
home care to patients who need it but are unable to pay for the care. Medicaid
and other government sources, except Medicare, paid 41.4 percent of the cost of
nursing home care which translates into 20 percent of the shared cost (of 41.4
percent) incurred by the federal government and 20 percent of the cost covered by
the state. The increasing older population combined with the 41.4 percent Medic-
aid payment rate precipitates concern about the growth in nursing home costs.
51


, II1
' ''I
Table 2.9 projects the growth in Colorados nursing home population to double in
i ''I
size from 1980 :to 2000. The 1980 nursing home population of 12,873 will grow to
24,306 by the year 2000. This growth will undoubtedly impact Colorados Medicaid
expenditures. :
Two redent studies described the payment source of the nursing home
population at admission.
Historically, about 40 percent of elderly nursing home residents enter as
Medicaid recipients, about 50 percent as private payers, and the remaining
10 percent under private insurance, Medicare, or other public programs.
Some of those who enter a nursing home as private payers, however,
subsequently become Medicaid eligible . about two-thirds of nursing
home residents are receiving Medicaid assistance at any point (U.S. Gener-
al Accounting Office, 1990, p. 10).
Another study (Liu, Doty & Menton, 1990) claimed that 11 percent of those entering
a nursing home as a private payer spent their resources and became eligible for
Medicaid during their nursing home stay.
As the demographics shift toward an increasingly older population, Medicaid
expenditures are projected to grow, further straining state and federal Medicaid
budgets. Medicaid was initially intended as an acute-care program for the poor,
however, Medicaid has become the principal public program financing long-term
i
nursing home care for the elderly and disabled. Although not foreseen when
, in
!|
Medicaid was enacted in 1965, spending for nursing home care is one of the
jl'
largest components of Medicaid spending. Approximately $14.3 billion of the total
$48.7 billion in federal and state Medicaid spending went for nursing home care in
i
fiscal year 1988 (U.S. General Accounting Office, 1990, p. 11). In 1988, nursing
:l,
home care represented 30 percent of the federal and state Medicaid costs.
52


Table 2.9. Projected Number of Nursing Home Residents in Colorado and
Percent Change by Age and Sex, 1980-2000.
Number of Nursing Home Residents Percent Change
Total ;; 1980 1990 2000 1980-1990 1990-2000 1980-2000
Age 65 & Over 12,873 17,946 24,306 39.40 35.44 88.81
65-74 2,359 3,026 3,385 28.24 11.88 43.48
75 -84 5,095 6,986 9,068 37.11 29.8 77.96
85 & Over 5,419 7,934 11,854 46.42 49.40 118.75

Males 1980 1990 2000 1980-1990 1990-2000 1980-2000
Age 65 & Over 3,355 4,276 5,449 27.48 27.42 62.44
65 -74 || 1,022 1,313 1,489 28.51 13.40 45.73
75 84 1,211 1,627 2,116 34.3 30.11 74.73
85 & Over ; 1,121 1,336 1,843 19.18 37.93 64.38
r
Females 1980 1990 2000 1980-1990 1990-2000 1980-2000
Age 65 & Over 9,519 13,669 18,857 43.60 37.95 98.11
65-74 ij 1,337 1,712 1,896 28.04 10.71 41.76
75-84 3,884 5,359 6,951 37.98 29.70 78.97
85 & Over ' 4,297 6,598 10,010 53.53 51.72 132.94
Note. From Colorado Health Care Association, 1989, Denver, Colorado, unpub-
lished data.
A recent report in the Journal of the American Medical Association con-
firmed concerns that by the time current baby boomers reach retirement age, their
aggregate health care costs could exceed the nations current annual deficit.
"Approximately 40% of current nursing home costs are reimbursed by the govern-
ment through Medicaid. If this program continues and the number of nursing home
ir
i
53


residents risesito almost 6 million, the cost to the government could be as high as
$56 billion (ih 1985 dollars)" (Schneider & Guralnik, 1990, p. 2338). In a related
article, Carroll jEstes described the impoverishing effect of our current federal
policies:
We are; impoverishing people by all the bad decisions that make
Medicaid our foremost program for long term care, and then primarily
in institutions. It should have been a national thunderclap when
Congressional researchers announced a few years ago that most
older persons who must privately pay out of pocket for nursing home
serviced spend down their resources so rapidly that they become
eligible; for Medicaid coverage within approximately 13 weeks of
admission to a nursing home. (Estes, 1990, pp. 4-5)
Medicare expenditures for hospitalization have been controlled by prospec-
tive reimburseirient policies, however, the nursing home admissions are increasing,
patients are staying longer, and the longer these patients remain in a nursing
home, the more likely they will require Medicaid coverage. Medicaid expenditures
have been increasing substantially. Since Medicaid is a federal/state cost-shared
program, the federal costs may decrease by moving patients from Medicare to
Medicaid but then the state costs increase. In Colorado alone, the 1988 to 1989
Medicaid budget was over-expended by $100 million. In 1978, Colorado devoted
60.5 percent of its total Medicaid expenditures on nursing home care (Health Care
Financing Administration, 1979, Table E). "Medicaid expenditures for nursing home
care are already of major concern to the States and the Federal Government
because they have increased at a high rate in the past. Virtually, all the States
have problems financing this program" (U.S. General Accounting Office, 1983, p.
)
54


Another! phenomenon in the Medicare program may increase patient spend-
down and force premature utilization of the Medicaid program. As the deductibles
and subscriberjifees for Medicare increase, and as more older people pay for
services not covered by Medicare, there will be an increasing number of older
i
people needing the Medicaid program. More middle-class older persons will
"spend-down" and become medically indigent (Feldstein, 1988). The literature
clearly ties the'demographics of the older population to the increasing Medicare
costs and corresponding Medicaid costs as a result of nursing home placement.
Table 2.10 reflects the growth in Colorados Medicaid expenditures from 1981 to
1990. In 1990 the aged recipients represented 14 percent of the total Medicaid
recipients in Colorado and the cost of nursing home care represented 26 percent of
the states total! Medicaid expenditures.
States confronted with budget shortfalls are examining their ever growing
Medicaid budgets. "New Jersey is projecting an $87 million deficit for its $2.1
billion Medicaid program by the end of the year.. .[due to] rising Medicaid costs on
higher inpatient hospital and nursing home care costs" (Older American Report.
1991, p. 19). South Carolina faced a $60 million Medicaid shortfall by June, 1991.
States continue to seek opportunities for decreasing the spiraling Medicaid costs
for institutional care.
Nummary of Research Findings Regarding the Impact of
Medicare Changes on Hospital Discharge
A large iportion of national health care costs is accrued by older adults in
ii
hospitals and nursing homes. Prospective reimbursement slowed the rate of
|
Medicare increases but the costs in Medicaid escalated as a result of increasing
55


Table 2.10. Colorado's Medicaid Expenditures for Aged Hospitalization and
jNursing Home Care: 1981-1990.
YEAR TOTAL RECIPIENTS AGED RECIPIENTS TOTAL EXPENDITURES AGED HOSPITAL EXPENDITURES AGED NURSING HOME EXPENDITURES
1981 145,5.14 31,263 $215,712,006 $5,222,396 $67,788,936
1982 143,656 30,954 244,562,711 6,513,189 72,195,642
1983 147,644 31,408 255,303,361 6,015,322 77,001,278
1984 155,426 31,960 290,171,047 6,292,278 82,082,354
1985 147,309 31,715 315,797,062 5,091,656 86,424,686
1986 149,030 33,209 300,313,127 695,127 89,940,836
1987 165,333 35,415 372,182,233 7,583,349 99,167,998
1988 211,387 32,406 464,311,557 3,677,854 119,690,780
1989 218.Q67 32,497 451,909,848 2,509,278 119,048,253
1990 239,878 33,544 $515,696,297 $2,282,610 $132,613,837
Note. Colorado Department of Social Services, Medicaid Division, unpublished file
data, February, 1991.
nursing home admissions and extended lengths of stay. Older adults are entering
nursing homes more frequently from hospitals than any other source. After DRG's
were utilized for reimbursement, more older adults were discharged from hospitals
to nursing homes, with longer lengths of stay in the nursing home. Approximately
40 percent of nursing home costs are covered by Medicaid; an increase in admis-
sions leads to 'spending down resources and an increased need for Medicaid
coverage. Colorado's Medicaid expenditures for elderly nursing home residents
' ill
increased from $67 million in 1981 to $132 million in 1990. Most states are having
56


difficulty paying: their share of the growing Medicaid budgets. In 1988 and 1989
and again in 1990-1991, Colorados Medicaid budget was over expended by $100
million.
' !!
The projected growth in the number of nursing home residents in Colorado
increases concern about future Medicaid expenditures. From 1990 to 2000, the
i,
number of Colorados nursing home residents age 75 to 84 is expected to increase
by 29.8 percent and the 85 and older population is expected to increase by 49
percent. New interventions are needed which will ensure that Medicare patients
- .ij
receive the appropriate level of care and prevent premature institutionalization.
Patient Characteristics as a Predictor of Posthospital Care
Over the past twenty years researchers have attempted to assess the
factors which cause institutionalization. A number of variables are associated with
institutionalization. Advanced age has been cited as a factor (Brock and OSulliv-
an, 1985; Cohen, Tell, & Wallack, 1986; Greenberg & Ginn, 1979; Shapiro & Tate,
1985). Certain diagnostic conditions, particularly those with a diagnosis including
mental illness, are more frequently nursing home residents (Shapiro & Tate, 1985;
Weissert & Cready, 1989). Gender, race, nursing home bed supply, and climate
I
are also associated with institutionalization (Unger & Weissert, 1988). Shapiro and
Tate (1988) identified nine significant factors for the prediction of long-term institu-
tionalization: age, living in retirement housing, recent hospital admission, spouse at
"i
home, fair or poor self-rated health, female, problem remembering names, more
than one problem with activities of daily living, and steadiness in state of mind.
' 'I'
Lack of availability of informal support, living alone or having limited contact with
57


Ij
relatives has been associated with institutionalization (Brock & OSullivan, 1985;
;.jj
Greenberg & Ginn, 1979; Shapiro & Tate, 1985; Weissert & Cready, 1989).
Weissert & Cready (1989) found strong associations of the following variables with
institutional residency: age, marital status, poverty, dependency level, and certain
' ;ij
diagnoses (mental disorder, cancer, anemia, kidney trouble, digestive disease,
nervous system disease, diabetes, and circulatory disease). The inability to do
basic tasks for oneself, such as bathing, feeding, toileting, was researched and
cited as a predictor of nursing home placement by Cohen, Tell, and Wallack
(1986), Greenberg and Ginn (1979), Shapiro and Tate (1985). After prospective
reimbursementiwas initiated, new variables were identified. Meiners and Coffey
(1985) identified four DRGs most commonly referred from the hospital to nursing
homes. The DRGs included strokes, heart failure and shock, major joint proce-
dures and hip and femur procedures, and pneumonia.
Morrisey et al. (1988) analyzed the early effects of the Medicare prospective
payment system on the likelihood of hospitals discharging Medicare patients to
i;
nursing homes or home health care. Their analysis reflected the probability of
hospital transfer increasing for all DRGs and posthospital destinations. However,
i1
patients with stroke, penumonia, and major joint and hip procedure were more
likely to be transferred to skilled nursing facilities. Morrisey et al. viewed the
probability of transfer and the probability of length of stay prior to transfer as a
function of "thei'introduction of the prospective payment system as well as the
health status arid demographic characteristics of the patient; the destination of
transfer, i.e., skilled nursing facility, intermediate care facility, or home health
I"
58


agency; the characteristics of the hospital, and the characteristics of the communi-
" 1
ty" (Morrisey et al. 1988). Their research found significant differences in length of
stay and transfers by gender, race, age (75 and older), the presence of a second-
ary diagnosis, by characteristics of the hospital and characteristics of the communi-
ty. Hospital characteristics included ownership, teaching role, and the size of the
institution. Community factors related to the availability of subacute care or other
hospitals. This; research and others did not find a consistent pattern between
!
severity of illness and either transfer probability or hospital length of stay (Morrisey
et al. 1988).: Patient diagnosis does not appear to be a good predictor of resource
' i
use in nursing'homes (Cotterill, 1986).
There is no clear evidence that financial status or poverty level is strongly
associated with institutionalization. Numerous studies found no association. Two
studies found a positive association between individuals receiving Medicaid or
public assistance and institutionalization. Greenberg and Ginn (1979) found that
recently institutionalized older adults in Minnesota were more likely to have higher
incomes (Cohen, Tell, & Wallack, 1986; McCoy & Edwards, 1981).
Weissert (1985) claimed that although older age increases the risk of
nursing home placement, the probability of an institutionalization remains low
unless age is accompanied by dependency, high-risk diagnosis, and the absence
or loss of a Spbuse. Two other studies (Greenberg & Ginn, 1979; Shapiro & Tate,
i1
1985) found females to be more at risk of institutionalization than males. Another
study (Leibson, Naessens, Krishan, Campion & Ballard, 1990) demonstrated that
, ii
significant increases in mortality and nursing home transfers occurred after the
59


introduction of the Medicare prospective payment system, largely due to patient
age, gender, disease severity and complexity.
Sufficient evidence exists from other research to more closely examine the
nature and predictors of nursing home placements, if variables such as age,
in
|l
gender, or marital status are predictors of institutionalization, the creation of
multivariate models could estimate older patients risk of institutionalization. Limited
resources, targeted to these high risk populations, would serve as a cost-effective
approach to prevent premature institutionalization.
Patient Satisfaction with Discharge Planning
Since the Medicare prospective payment system (DRGs) was introduced,
I
researchers have reported on the discharge of "sicker" patients, decreasing
hospital stays, increasing hospital readmissions, increasing outpatient visits,
premature discharge, and increasing admissions to nursing homes (Coe, Wilkinson,
& Patterson, 1986; Congdon, 1989; Fitzgerald, Moore, & Dittus, 1988; McGovern &
Newborn, 1986). Frequently, however, the financial implications of the prospective
s'
payment systeijh have overshadowed the vulnerability of the older patients who are
discharged. Data on older patients experience and satisfaction with the discharge
planning process is nearly nonexistent. In order to improve the discharge process
and improve patient outcomes, the perspective of elderly patients is critical
;;j
(Congdon, 1989). This research includes follow up questions at two week and
eight week intervals after discharge to assess patient satisfaction with discharge
planning.
60


The Impact of Medicare Policy Changes on Hospital Discharge Planning
Health Gare Financing Administration data cited in the previous section
substantiates the cost savings of the prospective reimbursement system through
fewer Medicare' hospital days. One of the spillover effects of prospective reim-
, .I-
bursement was an increase in nursing home admissions.
The Medicare prospective reimbursement system has also impacted the
hospital discharge planning process. Discharge planning and finding appropriate
post-hospital care will be discussed in this section.
Recognizing that Medicare patients were discharged from hospitals "quicker
i 'i'
and sicker," Cdngress developed the patients rights to discharge planning. The
i'
purpose of these rights was to ensure that patients received a smooth and timely
transition to the most appropriate post-hospital care. Also, patients could request a
:i'
review of any proposed termination of Medicare-covered hospitalization.
On October 22, 1987, the federal discharge planning legislation (U.S.PL 99-
r
509,1986) went into effect; hospitals participating in the Medicare program were
i
required to provide discharge planning. Medicare in-patients must be given a
notice explaining that they have a right to a discharge plan and to discharge
i <
planning services.
The federal statute 42 U.S.C. § 1395 X (ee), provides for the follow-
ing: ;
f
(1) the hospital must identify at an early stage those patients who in the
absence of adequate discharge planning are likely to suffer adverse
health consequences on discharge;
(2) the hospital must provide a discharge planning evaluation on a
timely basis for patients identified under subparagraph (1) and for
other patients on request;
Hi
il'
61


(3) j 'the discharge planning evaluation must include an assessment of a
patients likely need for appropriate post-hospital services and of the
availability of those services;
t
(4) on the request of a patients physician, the hospital must arrange for
the development and initial implementation of a discharge plan for
the patient; and
(5) both the evaluation and the plan must be developed by or under the
supervision of a registered professional nurse, social worker or other
appropriately qualified personnel. (Paulson, 1990, p. 5)
These pew discharge planning requirements are an important step toward
identifying and planning for the assistance which Medicare patients will need after
hospital discharge. Patients who are leaving the hospital "quicker and sicker"
1;
require more support at discharge to facilitate recuperation and simultaneously
prevent readmission to the hospital.
Hospital discharge planning has received increased attention since imple-
mentation of prospective reimbursement. First, patients waiting in hospitals for
appropriate post-hospital care have become a greater focus of attention since fees
are fixed by diagnosis rather than number of days at the hospital (U.S. General
Accounting Office, 1987). Second, new requirements for Quality Assurance
encourage hospitals to provide effective and timely discharge planning as a
:ji
service. Hospitals, faced with a growing elderly patient census and the realities of
i
the DRG prospective reimbursement system, must select appropriate services and
housing for these patients upon discharge while the timeframe from physician
notification of discharge to actual discharge ranges from a few hours to a few days.
At discharge, hospital discharge planners recommend services in nursing
homes, in other housing arrangements, or at home. In order to prevent the most

62


costly, most restrictive care referrals to nursing homes, some form of intervention is
necessary which will: 1) provide the assistance needed by the patients to stabilize
their medical condition; and, 2) prevent readmissions to the hospital. In 1986, the
U.S. House of .Representatives Select Committee on Aging requested a study by
the U.S. General Accounting Office (GAO). The survey of a nationally representa-
tive sample of hospital discharge planners obtained information on their experienc-
es regarding access by Medicare patients to post-hospital care (U.S. General
Accounting Office, January, 1987). The survey assessed the role of the new
prospective payment system (DRGs) and other factors in arranging access to care
i |j;
after hospital discharge for the elderly. This GAO study was the first national study
to examine problems facing Medicare patients whose need for post-hospital care
had been determined by hospital professionals. Most of the hospital discharge
,i
planners responding to the survey faced a number of important problems in gaining
access to appropriate post-hospital care. This national survey of 866 hospitals
jj;
included 111 hospitals in the mountain region. Table 2.11 presents the characteris-
tics of the mountain region hospitals participating in the GAO study.
The G^O study reflected a number of potential trends or events that could
affect access to post-hospital care. The introduction of the Medicare prospective
payment system was seen as contributing greatly to the access difficulties. Other
: 1 ii:
factors affecting access to post-hospital care were the increasing numbers of
Medicare patients, increased use of complex medical equipment and other "high-
tech" services in post-hospital care, state certificate-of-need regulation of nursing
home beds, and changes in the number of certified skilled nursing facility beds.
I;
63


Table 2.11. Characteristics of the 111 Mountain Region Hospitals Responding to
GAO Survey on Posthospital Care.
Bedsize Control
Range Percentage Types Percentage
<100 38.7% Nonfederal government 23.4%
100-299 34.2% Private not-for-profit 67.6%
300+ 27% For-profit 9.0%
Note. From Post hospital care: Discharge planners report
increasing difficulty in placing Medicare patients (p. 24) U.S.
j General Accounting Office, January 1987, Washington, D.C.
Implementation of the Medicare prospective payment system was consistently
singled out by hospital discharge planners as a major factor making placement of
Medicare patients after hospitalization more difficult. While growth in the number of
home health agencies was regarded as facilitating post-hospital placements,
discharge planners in each region of the U.S. cited Medicare program rules and
i
regulations as, the most important barrier to home health placement.
The discharge planners were asked the post-hospital destination of their
Medicare patients after receiving discharge planning. "Nationally, discharge
planners reported that only about 37 percent of a hospitals discharges were
discharged to their homes without further care" (U.S. General Accounting Office,
1987, p. 30). Table 2.12 summarizes the destinations at discharge from the
hospitals in thei mountain region of the country (including Colorado). Fifteen
percent of the Medicare discharges were either to skilled nursing facilities or
intermediate care facilities.
64


Table 2.12. Posthospital Destination of Medicare Discharges in the Mountain
Region.
Without i With Home Skilled Intermediate Group Living Rehab
Further Care , Health Care Nursing Facilities Care Facilities Facilities Centers
50% J 18% 10% 5% 0% 1%
Note. From Post hospital care: Discharge planners report increasing difficulty in
placing Medicare patients (p. 30) U.S. General Accounting Office, January
1987, Washington, D.C.
In order| to impact the number of discharges to skilled and intermediate care
facilities, its important to know the perceived barriers to placing Medicare patients
in home career adult congregate living facilities. Nationally, the two most impor-
tant barriers to arranging home health care for Medicare beneficiaries cited by
hospital discharge planners were: (1) Medicare program rules and regulations, and
i' !!!
(2) lack of availability of noninstitutional posthospital care services. Table 2.13
reflects the perceptions of hospital discharge planners from the mountain region of
the United States regarding barriers to placing Medicare patient in home health
care.
The types of post-hospital services to which the discharge planners referred
: j:
their patients included: chore service, homemaker service, extended observation,
' r
custodial care and chronic care. Over 17 percent of the planners raised problems
regarding the lack of available home care services for their patients. In the
:r
mountain region, discharge planners described the availability of home health care
as adequate, the availability of homemaker services as marginal, and the availabili-
ty of adult congregate living facilities as inadequate (U.S. General Accounting
I
Office, 1987). These barriers at discharge increase the number of nursing home
65


Table 2.13. The Most Important Barrier in the Mountain Region
to Placing Medicare Patients in Home Health Care1
Number of Hospitals Responding Program Rules and Regulations Supply of Home Health Care Social or Legal Situation Need for Complex Skilled Care Chronic Care Problems Other Facilities
Medicare Medicaid
111 61% 0 17% 5% 4% 5% 8%
1As reported by the hospital discharge planners.
Note. From Post hospital care: Discharge planners report increasing
difficulty placing Medicare patients (p. 12) U.S. General Accounting
'Office, January 1987, Washington, D.C.
referrals. Alternative housing options such as adult congregate housing or home
care services are less costly than nursing home care if the patient does not require
24 hour per day supervision. Although costs of home health care vary depending
III
upon the health training of the individual caregiver, a few hours of home health
care could easily exceed the Medicaid cost of nursing home care ($32 per day in
Colorado). Services must be carefully packaged to protect the patient during
recuperation from their hospital stay while ensuring reasonable costs and service
dependability.
Other community services which the hospital discharge planners cited as
needed but not available in sufficient quantities are: meals on wheels, home
visitors, adult day care, transportation, board and care homes or alternative living
arrangements.; If the services are available, frequently there are waiting lists,
preventing immediate access to services.
The qualitative aspects of this research demonstrated the pressure on
discharge planners, the limited time available, and the need to quickly obtain
66


available servibes for which the patient is eligible. Naylor (1990) and other experts
have rated thfeiquality of discharge planning for the elderly as very poor (Fink, Siu,
Brook, Park, &!:Solomon, 1987). Historically, discharge planning has not been
considered apriority in the health care system and, therefore, suffers from delayed
j'
assessments, poor documentation, and fragmented implementation (Naylor, 1990;
U.S. Department of Health and Human Services, 1988). Recent research on
hospitalized elderly concluded that only 20 percent received discharge planning
from the sociai/.service department despite the fact that 85 percent of the patients
were defined as high-risk patients in need of discharge planning (Johnson &
Fethke, 1985; Naylor, 1990). In order to impact the discharges of older patients,
improved documentation and consistency in discharge planning services is essen-
tial.
Another aspect of discharge planning is the follow-up care after discharge.
Two important findings were cited in the U.S. General Accounting Office study on
posthospital Ca're. Hospital discharge planners were asked about the frequency of
their contact and type of posthospital contact with Medicare patients. Table 2.14
reveals that only 17 percent of the Medicare patients discharged in the mountain
region are contacted after discharge by the hospital most of the time or almost
always.
When asked about the type or method of posthospital contact with Medicare
! i!
patients, hospital discharge planners in the mountain region, who were making
follow-up contact, reported patient visits (19%), telephone contacts (60%), and
(68%) contacts
with providers (U.S. General Accounting Office, 1987).
67


II
iii
Table 2.14. Frequency of Posthospital Contact with Medicare Patients by
Discharge Planners in the Mountain Region.
h ill
___________________jl_____________________________________________________________________________
Number of: Hospitals i' ; Seldom ji If Ever Sometimes About Half The Time Most of The Time Almost Always
111 ! '! 13% 54% 15% 13% 4%
Note. From Post hospital care: Discharge planners report increasing
difficulty in placing Medicare patients (p. 26) U.S. General Account-
ing Office, January 1987, Washington, D.C.
' i 1
As the population of frail older adults increases, the demand for housing
options and community services will also increase. The financial ramifications of
utilizing nursing homes instead of less restrictive, less costly services were de-
scribed in the previous section. Discharge planning at the hospital becomes a
iij
critical decision point for preventing premature nursing home institutionalization.
I1 The Impact of the Increasing Older Population on
: Future Medicare Policies and Community Services
A number of recent books and articles deal with the increasing older
population and, its impact on public policy. Medicare payments for personal health
care rose by over 15 percent annually between 1970 and 1985 (Waldo, Levit &
Lazenby, 1986), while the number of enrollees was growing by only about 2
percent per year (Health Care Financing Administration, 1984). Policy analysts and
researchers like Stephen Zuckerman have called for new theories, research and
policies which "create incentives to control both quantities and development of the
nations policies for long term care." One intervention option was proposed by
Vladeck (1980) who encouraged the U.S. to move its policies toward increased
utilization of congregate care housing and avoid new nursing home construction.
68


In particular, he Suggested utilizing a portion of the excess hospital beds (at less
reimbursement) for individuals who are not appropriate for nursing home place-
1 1,1
ment. !!
I:
ij
Lawton and Hoover (1981) have contributed work on housing policy
. n'
ii'
analysis which shows the close ties between housing and long-term care policies.
First the older population is diverse and requires a wide variety of health, housing
and long term care policy approaches. Secondly, present long term care policies
are escalating costs and are not meeting the needs of vulnerable elderly (White,
! ii;-
;i<
1984). Third, inbreasing numbers of frail older adults makes public policies for the
most frail, poor or at risk of institutionalization critical in the next decade.
' i! n!
The older population is increasing and the service delivery system is in
transition. Constant changes (i.e., a continuing expansion of alternatives) are
' !,
occurring in the senior housing continuum and in-home services precipitating a
challenge to maintain accurate resource files. Without accurate data about options,
hospital discharge planners refer clients to more expensive nursing home care.
The domain of elder housing which ranges from independent living at home
i;
through a variety of supported environments to nursing home care, has become
sophisticated, offering various levels of service in order to meet older persons
|'
needs. A description of the long term care housing continuum is contained in
Appendix F. Differences, both minor and major, exist between facilities throughout
the metropolitan'Denver area-a statement that surely can be made of any other
location in the UlS. Detailed knowledge about these differences is essential if
referral patterns from hospitals are to be changed.
69


Housing of Very Old Patients after Hospital Discharge
Due tp the aging of the hospital patient population, hospital staff must guide
an increasingly frail elderly population into appropriate supportive services and
housing following hospitalization. These patients require particular care in the
I "I
discharge planning process because their frailty places them at risk for medical
complications, and places their caregivers at risk for excessive burden. Additional
pressure is placed on discharge planners by the prospective payment system
(DRGs), which has shortened hospital stays for Medicare patients (Guterman &
Dobson, 1986). Therefore, discharge planners must act quickly and efficiently in
developing comprehensive discharge plans which will ensure the safety of frail
patients when they leave the hospital (Coulton, 1988).
The focus of this research is but one major discharge decision for frail
jr
elderly: housing placement. Housing options range from independent living at
home with no care through a full continuum of housing options to the most depen-
dent housing option which is nursing home care. Figure 2.3 shows the long term
care housing continuum which ranges from the least dependent housing option
(living at home with no services) to the most dependent housing option (nursing
home care).:
Figure 2.3. Long Term Care Housing Continuum.
Least Dependent Most Dependent
Own Home Own Home Independent Congregate Assisted
No Services <-> With Services < 1 1 ill > Living < -> Senior Housing < > Uving < > Nursing Home
70


Appendix F provides a detailed description of each component in the
housing continuum and services offered under each housing type.
' 'l!
Changes in functional health represent a major reason why older persons
move to more supportive housing, but elderly tend not to prepare for health-
induced housing changes prior to a health crisis (Kulys, 1984). Thus, hospitaliza-
tion often serves las juncture point for health care professionals to examine more
closely older persons functional health, which in turn stimulates re-evaluation of
V
housing appropriateness. An older person may be hospitalized because of a slow
decline of health which culminates in a health crisis, an acute exacerbation of a
chronic illness, or a new illness. In any of these circumstances, the hospitalization
can reflect the need for housing to be reevaluated. While observing older persons
in hospitals, professionals may recognize that the patient needs more support than
11 'i1
is available in their pre-admission housing. Of course, hospital staff may also note
cases in which older persons received unneeded support in their pre-admission
housing. Systematic assessments of patients as part of the discharge process
ii
have not been normative (Victor & Vetter, 1988) but are effective means of
identifying the services needed upon discharge (Williams, Hill, Fairbanks, & Knox,
, ni
1973).
Discharge planners have the task of arranging professional support services
to follow the patient for a period after a hospitalization. At times, however, support-
ive services in an independent housing environment are insufficient to provide the
environmental prosthesis needed to maintain the patient at his or her highest level
of functioning. Injsuch cases, the patient may be discharged to a new type of
housing, likely one offering additional support.
71


Hospital discharge planning is conducted by a wide variety of professionals
who have piijy limited awareness of the specific housing options available in the
community, the differences among them in financial and supportive service charac-
l:
i
teristics, or the availability of units (beds) within them at a given moment in time.
Unfortunately, in most hospitals, specific information about housing options is not
readily available in an easily accessible format. In contrast to home health servic-
es, which are generally arranged by an agency which offers the full array of
relevant services, there is no centralized housing referral and placement service in
most cities which can maintain detailed or even up-to-date vacancy information on
all housing units in the region. Given the time pressure to plan the discharge,
accessible comprehensive housing information can be a key factor in providing
appropriate referrals for patients at discharge.
. ||'
Further complicating the housing referral component of the discharge
process is the fact that most discharge planners are unable to follow patients once
i'
they leave the hospital to determine the appropriateness of the housing placement
in the ensuing weeks of rehabilitation (Coulton, 1988). Elderly patients may then
fear that placement in a highly supportive environment (such as a nursing home)
may become: permanent regardless of their potential to live in more independent
housing after a few days or weeks of recovery. Hospital staff, on the other hand,
fear placing patients in an environment with insufficient support where they may
relapse, with additional suffering as a result. Patients who have no family mem-
bers to provide post-hospital care have a greater need for alternative housing
in
which offers assistance. Hospital staff also fear the financial consequences of re-
hospitalization of patients during the DRG payment-exempt period following
72


ll
discharge in which the hospital will receive no Medicare reimbursement for read-
mission. Thusi patients can be pressuring discharge planners toward independent
;ij
placements (typically their own homes) while medical professionals are encourag-
ing placements in more supportive (and restrictive) environments.
II;
Recent statistics which show a rapidly increasing rate of nursing home
admissions have1 been interpreted to suggest that time pressure from DRGs is
forcing hospitals ;to discharge more frail elderly to nursing homes. This pattern is of
particular concern because of the tendency for nursing home placements to
become permanent (Fitzgerald, Moore, & Dittus, 1988).
I iir
Recently,two new federal approaches were proposed to encourage
hospitals to pay fnore attention to the importance of the discharge planning role. In
1988, new peer review organization guidelines were initiated to target review of
Medicare patients readmitted to acute care hospitals within 30 days. The screens
enable peer review organizations to monitor subsequent care charts from skilled
nursing facilities,j home health agencies, and doctors' offices, and to consider
recommending a reimbursement penalty on hospitals or physicians responsible for
premature discharge. "The purposes of the new screen ... are adding quality
assurance to physician review of hospital Medicare bills and providing incentives
ii
for hospitals to pay more attention to post-discharge care" (Weiner, 1990, p. 4).
Federal ipolicymakers are taking a look at the broader role which hospitals
1,
'I I
play. A 1990 federal budget proposal, developed by the Office of Management and
Budget, would have consolidated Medicare hospital reimbursement and post-
hospital skilled nursing care or home health care reimbursement under a single
DRG payment. "Under about 50 DRG categories, hospitals would have been
,' ii!
73


responsible for direct provision or subcontracting of post-hospital care, in return for
a small fixed I'percentage DRG rate increase" (Weiner, 1990, p. 4). U.S. Secretary
of Health and Human Services, Dr. Louis Sullivan, opposed the proposal but the
proposal represented a financial incentive for hospitals to improve their hospital
discharge planning role and prevent premature discharges that increase nursing
home stays. ^
Clearly, an examination of nursing home placements from hospitals is
needed. What patient characteristics tend to predict nursing home placement at
; 1
hospital discharge? This research will collect data on causal factors.
In summary, hospitalizations stimulate housing crises, as well as health
crises for many elderly who will need significant personal and health care assis-
tance following the hospitalization. Furthermore, the supportive housing needs of
some elderly first come to the attention of health care professionals during a
hospitalization. It is increasingly evident that hospital professionals are in a
i.
position to recognize needs for supportive services for the elderly, and that the
discharge process is mandated to implement services and housing changes to
meet those needs. At this point, however, little is known about how much housing
change occurs as a function of the discharge process, which populations are most
likely to require new housing placements, and how adequately prepared discharge
planners are for this task.
The research describes the demographic characteristics of the age 75 and
, }:
older population at hospital discharge, identifies the extent to which hospitalization
74


provokes housing changes, determines the nature and predictors of those place-
ments, the permanence of the placements, and surveys hospital discharge plan-
ners regarding thleir capacity to refer patients to housing placement at discharge.
This research also determines the extent to which the intervention of a case
manager can prevent or delay nursing home placement at hospital discharge. The
following section reviews the literature which led to proposing case management as
an appropriate intervention for this research.
!' Rationale for Case Management Intervention
At the time of discharge, older people are vulnerable because they are
limited to their farhily resources and the services obtained by the hospital discharge
planners. Older persons over age 75 who live alone and have sufficient health
problems to be hospitalized will most likely need post-hospital care from their family
and community resources. Family involvement must be encouraged. "Practitioners
I.
also have a special obligation to be knowledgeable about community resources
and to refer at-risk elderly people to resource personnel who may be in a better
position to assess the home and family needs than professionals primarily working
, ,i.
in their offices" (Shapiro & Tate, 1988, p. 244).
; 'i'
Although any number of interventions could be tested to prevent premature
institutionalization: to nursing homes, a case management approach initiated at
discharge would have the greatest opportunity for success. The ability to predict
post-hospital placement will provide a foundation for developing the new policy
i J1
options, which are required to build on family support systems to ensure appropri-
ate referrals and cost containment at discharge. Further, a case management
l
75


intervention has been proposed in the literature as a viable option to prevent
premature institutionalization.
Case management is also referred to as service coordination, care coordi-
nation or service management. According to Evashwick and Weiss (1987) the
basic steps of case management include "client identification, assessment, care
planning, service arrangement, monitoring and follow-up.. The role of the case
manager is to facilitate access by clients to the various services constituting the
continuum." In a description of the future trends in health care, Coile described the
health care continuum as the "factory of the future." All efforts will be made to
speed up the through-put on a case management approach, reducing inpatient
length of stay and increasing efficient use of all resources in the continuum of care
(Coile, 1987). Case management services have been developed in most states
since 1981, however, these services were initially established to divert existing
nursing home patients to other environments rather than prevent nursing home
admissions. For the most part, case management services are not available at
hospital discharge.
The high costs of health care and the growth in the older population has
precipitated a number of publications regarding patterns of medical utilization and
suggested interventions. A U.S. Department of Health and Human Services
research project titled "Consistently High and Low Elderly Users of Medical Care"
was conducted in Portland (U.S. Department of Health and Human Services, 1988).
Evidence suggested that "mental health and other supportive services, particularly
for older populations with specific physical problems, can result in more appropriate
use of the medical care system and possibly decrease overall utilization and costs"
76


(U.S. Department of Health and Human Services, 1988, p. 8). The report went on
to state that elderly high users of medical care "may be at greater risk for admis-
sion to nursing homes and might therefore benefit from interventions such as case
management" (U.S. Department of Health and Human Services, 1988, p. 9). In a
recent article, Estes called for a publicly financed long-term care system and
described case management services as an integral component in the future long
term care system (Estes, 1990).
The fragmented complex service delivery system creates a demand for
institutional care. According to Feldstein, the economic market response to the
i
high cost of searching for services and the uncertainty about available services has
been case management.
The case manager improves efficiency on the demand side by
helping dlderly people and their families understand what services
can be purchased to deal with a disability, how services can substi-
tute for or complement other services, where or how services can be
found, how to combine formal services with informal care, and how
better to use informal care. To the extent that the case manager is
familiar with the probable course of the disability, future consumption
of services can be predicted. The net result of case management is
that noninstitutional care for an older person can become, and be
perceived as being, more feasible than was previously the case.
Unfortunately, case management is not yet widely available, and
where it does exist, most people do not know of its availability.
Hopefully, base management as a market response to high search
costs will develop more rapidly in coming years. (Feldstein, 1988,
p. 567)
The Omnibus Reconciliation Act of 1981 removed a provision which
Medicaid recipients previously had for "free choice" of a provider. As a trade-off to
save federal matching dollars the Reagan Administration gave the states greater
flexibility to manage their Medicaid programs (Feldstein, 1988). States initiated
new systems, such as case management, for delivering services to Medicaid
77


/
clients. More than 24 states currently use some form of case management system
for their Medicaid population (George Washington University, 1985).
Richard Ladd, Oregons State Long Term Care Director, frequently com-
pares Colorado and Oregon (Kane, Wong, & King, 1990). Both states are compa-
rable demographically and geographically. About 10 years ago both states had a
Medicaid nursing home population of about 8,500 people. Colorado had about
2,500 Medicaid recipients in home care programs; Oregon had a Medicaid home
care population of about 4,000. (See Table 2.15.) Oregon made a number of
changes in its; long term care system.
One of these changes was to institute case management services at
hospital discharge. Table 2.16 reflects the change in long term care clients
between Colorado and Oregon in 1990. Although the two states were similar ten
years ago, in 1990 Colorado served approximately 12,000 Medicaid clients in
nursing homes and between 5,000 6,000 Medicaid recipients in the community.
Oregon served 7.500 Medicaid recipients in nursing homes, a thousand fewer than
ten years ago.1 Further, Oregon is serving 13,000 Medicaid recipients in the
community. Oregon is serving 2,000 to 3,000 more people at a cost of $20 million
a year less than Colorado. Although no data is available to determine the extent to
which case managers at hospital discharge contribute to the $20 million per year
savings or to the increase in individuals served at home, the numbers are suffi-
ciently staggering to warrant further research.
Sufficient evidence exists in the literature to propose case management
services as an intervention to prevent premature admissions to nursing homes.
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Table 2.15. Comparison of Long-Term Care Clients in Colorado and Oregon:
1980.
r Colorado Oreaon
Nursing Home Population on 8,500 8,500
Medicaid
Home Care Population 2.500 4.000
Total 11,000 12,500
Note. From "Funding for Long-Term Care and Case Management," (pp. 123-124)
by R. Ladd in Kane et al., Case Management: What Is It Anyway?. 1990,
Minneapolis, Minnesota: University of Minnesota.
Table 2.16. Comparison of Long-Term Care Clients in Colorado and Oregon:
1990
Colorado Oreaon
Nursing Home Population on 12,000 7,500
Medicaid
Home Care Population 5,000 13,000
Total 17,000 20,500
Note. From "Funding for Long-Term Care and Case Management," (pp. 123-124)
by R. Ladd in Kane et al., Case Management: What Is It Anyway?. 1990,
Minneapolis, Minnesota: University of Minnesota.
Although much of the literature promotes the use of case management for cost-
containment reasons, Califano suggests that case management with care in the
home is more humane.
... where people can be self-sufficient and stay at home with some
care, is the solution we should seek for most of our elderly, not the
institutional nursing home. The reasons are not simply financial;
indeed, the most important ones are humane. Most people would
much prefer to live in their homes and function independently than to
endure the lethargy of institutionalized way stations on the road to
death. (Califano, 1986, p. 174)
79


If case management services are deemed to have such a positive impact,
why is the availability of these services so limited? As previously cited, over 24
states now offer Medicaid funded case management services for adult Medicaid
patients who are already in nursing homes or are determined eligible for nursing
home placement. No other reimbursement through Medicare or Medicaid is
available to prevent institutional placement or prevent older adults from admission
to the Medicaid program after theyve spent their resources on nursing home care.
On a private pay basis, a few insurance companies are piloting long term
care insurance which includes case management. A number of large national
corporations recently started offering elder care services to their employees -- one
of the elder care services is case management. These progressive insurance
companies and employers are small in numbers. Case management agencies in
the Denver region which specialized in for-pay services to high income families
were unable to generate a sufficient client base to stay in business. As case
management services become well known, and as the reimbursement sources for
this service increase, more older adults and their families will seek the services of a
case manager. Can a case manager, at the critical point in time when decisions
are made about institutionalization, prevent or delay referrals for premature
institutionalization? If the investment of Medicare reimbursement for case manage-
ment services at hospital discharge was able to prevent the costly shift of patients
into the Medicaid program, millions of public dollars expended on unnecessary
institutional care could be saved.
80


CHAPTER 3
RESULTS
The purpose of this exploratory research was to: (1) determine the extent
to which the intervention of a case manager at discharge can prevent or delay
nursing home placement; (2) describe the demographic characteristics of the
hospitalized population age 75 and older in 5 Denver metropolitan area hospitals;
(3) identify the extent to which hospitalization provokes housing changes for older
adults age 75 and Older on Medicare; (4) determine the nature and predictors of
those placements; (5) determine the permanence of the placements; (6) determine
patient satisfactibn with hospital discharge planning; (7) describe the discharge
planning process through observation; (8) survey hospital discharge planners
regarding their comfort with the responsibility of housing placement at discharge;
and (9) recommend further quantitative or qualitative research to follow-up on the
findings from this exploratory research.
The results of this exploratory research will be presented in three major
sections. First, the indicators of housing placement will be discussed. Descriptive
information regarding hospital discharges from the five participating hospitals will be
examined. Second, the effects of the case manager intervention will be evaluated.
Finally, current and proposed models regarding the hospital discharge process will
be presented.


Description of Hospital Admissions
Patient Characteristics
This research sampled 1,040 Medicare admissions of persons over age 75 to
five hospitals. Patient characteristics of the sample were identified, and rated to
the type of housing to which these frail elderly respondents were discharged. The
average age of this sample was 82; over half of the respondents were widowed.
Predictors of Housing Placement at Discharge
Not surprisingly, frail elderly admitted from independent environments were
most likely to return to independent environments. However, other factors influ-
enced the types of housing to which respondents were discharged. Age, marital
status and gender all influenced the degree of independence in discharge housing.
Likely marital status was the major factor in planning of discharge housing (age
and gender are systematically linked to marital status because older persons and
women are more likely to be widowed). Generally, married persons were more
likely to be able to return to their own homes, perhaps due to the support available
in the home. Men in this cohort were far more likely to be married and, therefore,
to have a caretaker in the home; they were much more likely to be discharged to
their home. Women were far more likely to be unmarried or widowed, and thus to
be discharged to long-term care despite being admitted from their own homes. By
using regression equations, it was possible to predict the degree of independence
in discharge housing with information on housing at admission, marital status, age,
and gender.


As is evident in Table 3.1, married males were the most likely group to
return to their own home from a hospital stay. Unmarried males were no more
likely than unmarried females to be discharged to home (with or without services).
Unmarried persons were far more likely to be discharged to nursing homes than
married persons (approximately 14 percent of married and 29 percent of unmar-
ried), a pattern similar to effects of marital status on admissions from nursing
i
homes (10 percent of married and 24 percent of unmarried).
Table 3.1. Housing Level at Discharge by Gender and Marital Status1.
Married Unmarried
Males Females Males Females
Housing Levels : N %2 _N_ %_ N % N_ %_
Home-no services 139 64.1 54 47.8 64 41.6 179 35.6
Home-wilh services 22 10.1 17 15.0 6 3.9 48 9.5
Congregate 1 .5 1 .9 3 1.9 15 3.0
Relative's Home 4 1.8 4 3.5 12 7.8 41 8.2
Assisted Living 0 - 1 .9 4 2.6 4 .8
Rehabilitation Extended Care 5 2.3 8 7.1 6 3.9 32 6.4
Nursing Home/Hospice 30 13.8 18 15.9 40 26.0 158 31.4
Hospital 0 - 2 1.8 1 .6 2 .4
Died 16 7.4 8 7.1 18 11.7 24 4.8
Includes patients for whom data were available on all three variables, N=987.
8Column percentages add to 100%.
In order to evaluate the significance of marital status and gender on
discharge placement, housing levels were collapsed into four levels (without
services, supportive housing, nursing care, and hospital) and submitted to a chi-
square analysis by gender and marital status. Although the chi-squares for
83


housing at admission were not significant, indicating no differential effects of
gender and marital status on housing type at admission, the chi-squares were
significant for housing level at discharge. Among married persons, men were
i 1
significantly more likely to return to their own home at discharge (69 percent), while
women were more likely to be in supportive housing (22 percent), nursing care (25
percent), or the hospital (2 percent) (chi-square = 12.54; df=3; p<.0001). As
described above, married persons were far more likely to be discharged to inde-
pendent housing and far less likely to be discharged to nursing homes than
unmarried persons (chi-square=47.85; df=2; p<.0001). There were no significant
differences among unmarried men and women as to their housing level at dis-
charge.
Housing levels were ranked from most independent to most dependent and
assigned a value to create an ordinal variable on which correlational data analyses
could be performed. The housing levels listed in Table 3.2 were assigned values
from 1 (own home without services) to 8 (hospital). This variable representing
housing dependence (higher values reflect more dependence) was then correlated
with background variables of the patients. (See Table 3.3.) Housing levels at
admission and at discharge both correlated positively with age, health, gender, and
marital status. The direction of the correlations indicated that older women rated in
poor health at discharge were most likely to have been in dependent housing at
admission as well as at discharge.
84


Table 3.2. Housing Level Eight Weeks after Discharge by Gender and Marital
Status1.
Married Unmarried
Males Females Males Females
Housing Levels N %2 JL % N % JL %
Home-no services 79 60.3 34 41.5 20 24.4 82 24.5
Home-with services 25 19.1 23 28.0 17 20.7 79 23.6
Congregate . 1 .8 2 2.4 2 2.4 11 3.3
Relatives Home 1 .8 2 2.4 7 8.5 29 8.7
Assisted Living 1 .8 1 1.2 4 4.9 4 1.2
Rehabilitation Extended Care 1 .3
Nursing Home/Hospice : 9 6.9 12 14.6 26 31.7 103 30.7
Hospital ' 1 .8 1 1.2
Died 14 10.7 7 8.5 6 7.3 26 7.8
includes patients for whom data were available on all three variables, N=630.
2Column percentages add to 100%.
Table 3.3. Correlations of Background Variables with Housing Type.
(Sample Sizes are Noted for Each Correlation)
Housing at Marital Housing at
Admission Age Health Gender Status Discharge
Age .19
(1004)
Health1 .25 .13
(744) (756)
Gender2 .15 i .08* .02
(1000) (1036) (752)
Marital .11 .09 .06 .22
Status3 (1004) (1040) (756) (1036)
Housing at .62 .23 .40** .11" .15
Discharge (999) (1012) (749) (1008) (1012)
Housing at .68 .29** .43** .12 .15 .76
8 Weeks (639) (643) (455) (640) (643) (641)
*p less than .01
**p greater than .001
1 Health ratings made by discharge staff 1= very good, 2 = moderate, 3 = very poor.
2Male = 1, Female = 2.
3Married = 1, Unmarried = 2.
85


A regression equation predicting housing level at discharge was construct-
ed. Stepwise procedures using the background variables (housing at admission,
age, gender, marital status, and health) yielded an equation accounting for 54
percent of the variance. Results of this analysis are presented in Table 3.4 which
shows the step at which each variable entered. Stepwise procedures take the best
predictor at each step from the pool of available variables.
Table 3.4. Stepwise Regression Equation Predicting Housing Level at Discharge.
Step Patient Variables Beta F R2 Chanqe
1 Housing at Admission .6935 413.18 .4809 .4809
2 Age .1890 236.44 .5152 .0343
3 Health .1641 173.62 .5398 .0246
4 Gender .0678 132.30 .5443 .0045
In predicting discharge housing dependence, level of housing dependence
at admission was the most powerful predictor, accounting for 48 percent of the
variance in the dependent variable. Age, health, and gender all added significantly
to the ability of housing at admission to predict housing at discharge, although
together they accounted for only another 6 percent of the variance. The order of
i
entry of these variables indicates, for example, that even once the effects of
admission housing, age and health are accounted for, gender still was a significant
predictor of discharge housing. Because the variance shared between gender and
the other predictors (age, health and housing at admission) was already in the
equation, the additional .5 percent of the variance which gender accounts for is
86


"unique variance"; (see R2 Change column in Table 3.4), or effects of gender that
go beyond its shared effects with age, health and admission housing. Although
significant, this is a miniscule amount of variance which lacks substantive impor-
tance. The direction of effects for these variables indicates that patients dis-
charged to dependent housing were more likely to have come from dependent
housing, and to be older, female, and rated as in poorer health at discharge. It is
important to note that due to correlations among the predictor variables, it is not
meaningful to compare directly the Beta weights of the predictor variables in order
to determine the relative importance of each predictor.
A second predictor equation was built using demographic characteristics
alone, omitting housing level at admission as a predictor. Once again, health, age,
and gender were the significant predictors (marital status was not significant), but
the three accounted for only 24 percent of the variance. When admission housing
information is not available, much power will be lost in predicting discharge
1 i :
housing. Nonetheless, it is striking that age, gender, and an extremely simple
health measure afford this much predictability.
Predictions of Housing Level Eight Weeks after Discharge
Housing level at the eight week follow-up was correlated strongly with
housing level at discharge as well as with several background variables (see Table
3.5). Regression equations predicting housing at eight week follow-up were
constructed using stepwise procedures. The same variables predicted housing
level at eight weeks and housing level at discharge. Table 3.6 presents the results
of the first equation, which included housing level at admission, health, and age as
predictors and accounted for 52 percent of the variance. The second equation
87


Table 3.5. Stepwise Regression Equation Predicting Housing Level Eight Weeks
after Hospital Discharge.
Step Patient variables Beta ' F R2 R2 Change
1 Housing at Admission .6588 341.95 .4340 .4340
2 Health .2664 222.08 .4995 .0655
3 Age f .1542 161.72 .5221 .0226
Table 3.6. Stepwise Regression Equation Predicting Housing Level
of Elderly Patients (75+) Eight Weeks after Hospital Discharge.
Step Patient Variables Beta F R2 R2 Change
1 Housing at Admission .5585 341.95 .4340 .4340
2 Health .2515 222.08 .4995 .0655
3 Age .1542 161.72 .5221 .0226
predicting housing level at eight week follow-up omitted the admission housing
variable to determine the amount of variance accounted for by demographic
characteristics alone. Age, health, and gender provided the best set of predictor
variables which accounted for 24 percent of the variance.
Nursing Home Discharges
in comparison with patients from other types of housing, patients admitted
from, and discharged to, nursing homes were older, and in poorer health. Unmar-
ried persons, most of whom were women, were far more likely to be discharged to
88


Full Text

PAGE 1

MEDICARE PROSPECTIVE PAYMENT THEORY AS APPLIED TO THE MANAGEMENT OF PATIENT CARE OUTCOMES by Susan Cockings Aldridge B.A., Colorado Women's College, 197_7 M.P.A., University of Colorado at Denver, 1987 A thesis submitted to the Faculty of the Graduate School of Public Affairs of the University of Colorado in partial fulfillment of the requirements for the degree of Doctor of Philosophy Graduate School of Public Affairs 1991

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This thesis for the Doctor of Philosophy degree by Susan Cockings Aldridge has been approved for the Graduate School of Public Affairs E. Samuel Overman A. David Clayoen

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II ,' "' '' :I I I Aldridge, Cockings (Ph.D., Public Administration) The Prospective Payment Theory as Applied to the Management of Patient Care Outcomes ji ,' ', '1: Thesis directed by Associate Professor Robert Gage. This:work concerns the effect of a case manager at hospital discharge on nursing ,, home Further, this research explored the impact that gender, marital status, li housing level at admission and health status had as predictors of nursing home placement at hospital discharge. This research was designed to describe the critical point of discharge to develop causal hypotheses and new options for moving Medir;;are to appropriate, least costly, least restrictive environments. Finally, LJI : discharge perceptions of their hospitals' services were evaluated. The :study concludes that: {1) housing at admission, age, marital status and ,, gender are predictors of hospital discharge to nursing homes; (2) hospitals vary in their housing of elderly Medicare patients at discharge; (3) there were significant differences, ip the level of housing independence eight weeks after discharge between patients receiving case management and those receiving typical discharge planning and (4) discharge planners perceive their hospitals' services to be :I less comprehensive in the areas of housing referral and housing follow-up than in any other area. This exploratory study suggests that using a case management approach after hospital' discharge could result in a 21 percent decrease in the number of elderly ': :! patients remaining in the nursing home eight weeks after discharge, which is a potential annual savings of $3 million in Colorado's nursing home costs. The form and content of this abstract ar

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CONTENTS FIGURES ................................................... vi TABLES .................................................... vii ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . . ix CHAPTER 1 INTRODUCTION . . . . . . . . . . . . . . . . . 1 Trends Impacting Health Care . . . . . . . . . . . 4 Trend 1: Changes in the Health Care Industry . . . 4 Trend 2: Growth in the Older Population . . . . . 4 Trend 3: Escalating Medicare Care Costs . . . . . 5 Trend 4: Increasing Admissions to Nursing Homes . 5 Implications of Trends on Future Policies . . . . . 6 The Problem . . . . . . . . . . . . . . . . . 7 Rationale for the Study . . . . . . . . . . . . 7 Statement of the Problem . . . . . . . . . . . 9 Anticipated Impact of the Intervention . . . . . . . . 1 0 Investigative Procedures . . . . . . . . . . . . 12 Descriptive Data Collection . . . . . . . . . . . 12 Subjects: Sampling Procedures and Description . . 14 Measures . . . . . . . . . . . . . . . . 15 Procedure . . . . . . . . . . . . . . . . 16 Case Management Intervention . . . . . . . . . . 18 Subjects . . . . . . . . . . . . . . . . . 19 Housing at Admission and Discharge . . . . . . 20

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':i CHAPTER (cont.) Measures . . . . . . . . . . . . . . . . 23 Design . . . . . . . . . . . . . . . . . 24 Procedure . . . . . . . . . . . . . . . . 25 Qualitative Data . . . . . . . . . . . . . . . 28 2 ANALYSIS OF CONTEMPORARY RESEARCH ON MEDICARE COST CONTAINMENT AND THE IMPACT ON HOSPITAL DISCHARGE PLANNING AND NURSING HOME ADMISSIONS . . . . . . . . . . . . . . . 29 Demographic Projections . . . . . . . . . . . . 29 The Medicare Program . . . . . . . . . . . . . 36 Basic Components of Medicare . . . . . . . . 36 Transitions in the Medicare Program . . . . . . 38 Medicare Cost Containment . . . . . . . . . 40 The Impact of Major Legislation on Medicare Costs 41 The Impact of the Growing Older Population and Medicare Policy Changes on Nursing Home Admissions 46 Summary of Research Findings Regarding the Impact of Medicare Changes on Hospital Discharge . . . . . 55 Patient Characteristics as a Predictor of Posthospital Care........................................ 57 Patient Satisfaction with Discharge Planning . . . . 60 The Impact of Medicare Policy Changes on Hospital Discharge Planning . . . . . . . . . 61 The Impact of the Increasing Older Population on Future Medicare Policies and Community Services 68 Housing of Very Old Patients after Hospital Discharge . . 70 Rationale for Case Management Intervention . . . . . 75 ii

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CHAPTER (cont.) 3 'RESULTS . . . . . . . . . . . . . . . . . . . 81 Description of Hospital Admissions . . . . . . . . . 82 Patient Characteristics . . . . . . . . . . . 82 Predictors of Housing Placement at Discharge . . . 82 Predictions of Housing Level Eight Weeks after Discharge . . . . . . . . . . . . . . . . 87 Nursing Home Discharges . . . . . . . . . . 88 Hospital Differences in Housing Placements . . . . 90 Effects of the Case Management Intervention . . . . . 92 Generalized Effect on Hospital Discharges . . . . 92 Effects of the Case Manager's Direct Services . . . 94 Patient Satisfaction with Hospital Discharge Services . . 97 Perceptions of Service Offered . . . . . . . . 98 Qualitative Research Phases and Results . . . . . . 99 Invention 101 Discovery 103 Discovery: Discharge Planning Process . . . . 103 Discovery: The Physician's Role in Discharge Planning . . . . . . . . . . . . . . . . 1 05 Discovery: Family Counseling . . . . . . . . 1 06 Discovery: Insurance and Reimbursement Issues . 108 Interpretation . . . . . . . . . . . . . . . . 1 09 Interpretation: Discharge Planning Process . . . 109 Interpretation: DRG Impact . . . . . . . . . 11 0 iii

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,, CHAPTER (cont.) Interpretation: Management Issues . . . . . . 111 Interpretation: Resource Information on Alternative Patient Servicing . . . . . . . . . . . . . 112 Interpretation: Industry Issues . . . . . . . . 113 Explanation . . . . . . . . . . . . . . . . . 114 Overview . . . . . . . . . . . . . . . . 114 Personal Visits by Discharge Planners . . . . . 114 Scheduling . . . . . . . . . . . . . . . 115 Physician's Role in the Discharge Planning Process 115 Discharge Planning and Reimbursement . . . . 115 Counseling of Families . . . . . . . . . . . 116 Limited Resources . . . . . . . . . . . . 116 4 CONCLUSIONS AND IMPLICATIONS . . . . . . . . 117 Conclusions . . . . . . . . . . . . . . . . 117 Impact of Case Management on Hospital Discharge 118 Policies and Practices Precipitating the Research . 119 Demographic Characteristics Which Provoke Housing Changes . . . . . . . . . . . . . 121 Issues in Measuring Housing . . . . . . . . . 123 Discharge Planning: A Role in Transition . . . . . . 125 Changing Models for Discharge Planning . . . . . . 129 Research Strategies . . . . . . . . . . . . . 133 Sampling . . . . . . . . . . . . . . . . 133 Measures . . . . . . . . . . . . . . . . 135 iv

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,, CHAPTER (cont.) Discussion of Future Research ................... 140 Discussion of Future Practices . . . . . . . . . . 142 APPENDIXES Appendix A. Discharge Abstract . . . . . . . . . . . . . . . 146 Appendix B. Medicare Patient Authorization for Release of Information . 147 Appendix C. Telephone Script for Two Week Follow-up . . . . . . . 148 Appendix D. Telephone Script for Eight Week Follow-up . . . . . . . 149 Appendix E. Map of Participating Hospitals . . . . . . . . . . . 150 Appendix F. Long Term Care Housing Continuum . . . . . . . . . 151 Appendix G. Evaluation of Breadth of Services Available to Medicare Patients Over Age 75 Discharged From This Hospital. . . . 153 BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . 154 v

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FIGURES Figure 2.1. Annual Movement of Persons 65-74 through the Health Care System. . . . . . . . . . . . . . . . . . . 34 Figure 2.2. Annual Movement of Persons 75 and Over through the Health Care System. . . . . . . . . . . . . . . . 35 Figure 2.3. Term Care Housing Continuum. . . . . . . . . . 70

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TABLES Table 1.1. Research Objectives and Methods of Data Collection. . . . . 13 Table 1.2. Hospitals Participating in the Research. . . . . . . . . . 14 Table 1.3. :Demographic Characteristics of Admissions Over Age 75 at .;5 Denver Hospitals. . . . . . . . . . . . . . . . . 21 Table 1.4. Demographic Characteristics by Hospital. . . . . . . . . 22 Table 1.5. Housing Levels at Admission, Discharge, and Eight Week Follow-up . . . . . . . . . . . . . . . . . . . . 23 Table 1.6. Multiple-Baseline Design. . . . . . . . . . . . . . . 25 Table 2.1. Denver Metropolitan Area Forecast Absolute and Percent Change of the Total Population: 1988-2010 . . . . . . . . 30 Table 2.2. Denver Metropolitan Area Forecast Absolute and Percent Change of the 60+ Population: 1988-2010 . . . . . . . . 31 Table 2.3. >75+ Population 1988-201 0. . . . . . . . . . . . . . 32 Table 2.4. Role of Major Factors Affecting Health Care Transitions. . . . 39 Table 2.5. Estimated Medicare Savings from Six Major Laws. . . . . . 43 Table 2.6. Percentage of Elderly Hospitalized Persons Discharged Home and Percent Discharged to a Nursing Home by Age: 1986 ........ .... . . . . . . . . . . . . . 49 Table 2.7. Impact of Prospective Reimbursement. . . . . . . . . . 50 Table 2.8. $ource of Nursing Home Revenues (Calendar year 1988). . . 51 Table 2.9. Projected Number of Nursing Home Residents in Colorado and Percent Change by Age and Sex, 1980-2000. . . . . . 53 Table 2.1 0. Colorado's Medicaid Expenditures for Aged Hospitalization and Nursing Home Care: 1981-1990..................... 56 Table 2.11. Characteristics of the 111 Mountain Region Hospitals Responding to GAO Survey on Posthospital Care. . . . . . 64 Table 2.12. .Posthospital Destination of Medicare Discharges in the Mountain Region. . . . . . . . . . . . . . . . . . 65 'i

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:. '; Table 2.13. }he Most Important Barrier in the Mountain Region to PJacing Medicare Patients in Home Health Care . . . . . . 66 Table 2.14. Frequency of Posthospital Contact with Medicare Patients by Di,scharge Planners in the Mountain Region . . . . . . . 68 !I Table 2.15. of LongTerm Care Clients in Colorado and Oregon: 1980. . . . . . . . . . . . . . . . . . . 79 ", Table 2.16. Qomparison of LongTerm Care Clients in Colorado and Oregon: 1990 . . . . . . . . . . . . . . . . . . 79 I Table 3.1. Housing Level at Discharge by Gender and Marital Status . . 83 ',, Table 3.2. H<;>Using Level Eight Weeks after Discharge by Gender and Marital Status . . . . . . . . . . . . . . . . . . 85 I Table 3.3. Correlations of Background Variables with Housing Type . . . 85 Table 3.4. S,tepwise Regression Equation Predicting Housing Level at Discharge . . . . . . . . . . . . . . . . . . . . 86 Table 3.5. Regression Equation Predicting Housing Level Eight Weeks after Hospital Discharge. . . . . . . . . . 88 Table 3.6. Stepwise Regression Equation Predicting Housing Level of Elderly Patients (75+) Eight Weeks after Hospital Discharge. 88 Table 3.7. Housing Levels at 8 Weeks: Patients Using Case Manager versus No Case Manager. . . . . . . . . . . . . . . 95 Table 3.8. Discharge Planners' Perceptions of Adequacy of Services to Elderly Medicare Patients . . . . . . . . . . . . . . 99 Table 4.1. Professional Discipline of Discharge Planners at Participating Hospitals. . . . . . . . . . . . . . . . . . . . 128 "' viii

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ACKNOWLEDGEMENTS For their encouragement and loving support, special thanks go to my husband M. Gene Aldridge; my two stepsons Scott and Michael Aldridge; my mother-in-law Zora E. Aldridge; my aunt Alice Gill; and to my dear friend Molly B. Snyder. For their patience, constructive suggestions and thoughtful advice, my gratitude and respect go to each of the members of my dissertation committee: Robert Gage, E. Samuel Overman, A. David Clayden, Kathryn Denhardt, and Catherine Crawford. This research was made possible through funding from the U.S. Department of Health and Human Services and the Denver Regional Council of Governments. This research would not have been possible without the valuable .contributions of Dr. Sara Qualls, the Colorado Hospital Association, the Colorado Association of Homes and Services for the Aging, the 1,040 patients, and the five participating hospitals. ix

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CHAPTER 1 INTRODUCTION Public policies provide a framework within which managers operate. Government poiicies are created to address society's concern and prevent future problems from occurring. All too frequently there is no evaluation of the extent to which the public policies addressed the intended problem or created an unintended spillover effect .in another area. Reforms aimed at achieving one value may prevent us frorri achieving another. Judith Gruber described the relationship between public managers, or bureaucrats as she calls them, and policymakers: In the course of making their decisions about how a program will actually work, bureaucrats give the program shape and form. They are guided by decisions of legislatures, but those decisions often do little more than a broad domain within which bureaucrats must act ... politicians and bureaucrats bring distinctive perspectives and competencies to policy making (Gruber, 1987, p.6). This explores the impact of a public policy, describes the ope rationalization of the policy, identifies the successes and problems precipitated ', by the policy, suggests a hypothesis for preventing the spillover effects, and tests the hypothesis. :Although financial resources are limited for public program evaluation, managers have an opportunity to positively impact public policies if data is forthcoming. Carl Friedrich described the relationship as: "Public policy, to put it flatly, is a process, the formulation of which is inseparable from its execution" (Friedrich, 1940, p.6). The public policy which is the primary focus of this research is Medicare prospective theory. Sufficient data are available to analyze the impact of

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the policy and explore options which would prevent some of the negative outcomes I :1 or spillover effects from the public policy. Through the use of exploratory research or grounded theory, managers of publicly funded, programs have an opportunity to impact legislative changes thereby improving current public policies. Research is frequently conducted to replicate previous studies in order to validate certain facts or theories. The complex dynamics in the health care system and the relatively recent implementation of Medicare prospective payment theory suggests a research approach which will broaden opportunities for further study and policy change. Therefore, both qualitative and quantitative methods are required. Glaser and Strauss (1967) described the appropriate use of qualitative and quantitative research: Our gpal: of generating theory also subsumes this establishing of empirical generalizations, for the generalizations not only help delimit a grounded theory's boundaries of applicability; more important, they help us broaden the theory so that it is more generally applicable and has greater explanatory and predictive power. (p. 24) Through this exploratory research, a hypothesis will be tested and, more important-, ly, the qualitative research will generate new theories for future exploration. The purpose of this exploratory research is two-fold. First, the intervention of a case manager at hospital discharge will be tested to determine whether nursing home placement can be prevented or delayed. Second, data will be collected on older patients at hospital discharge to determine the variables which predict nursing home placement. The first null hypothesis for this exploratory research is that the intervention of a case manager at hospital discharge will not have an effect on the admissions to nursing homes. The second null hypothesis is 2

PAGE 15

that gender, marital status, housing level at hospital admission, and health status are not predictors of nursing home placement at hospital discharge. Both qualita tive and quantitative data are essential for addressing these hypotheses and for preparing recommendations which improve future Medicare policies. Recent federal Medicare policy changes pressure hospitals to discharge older patients earlier thereby reducing federal Medicare expenditures for hospital stays. Although the number of patient days in the hospital was significantly reduced as a of these policy changes, more patients are being discharged to nursing homes than to their own home with services or to another Jess costly housing option. Discharging patients to nursing homes, when other less costly services are appropriate, merely shifts the cost for government from the Medicare program to Medicaid. As a public policy, prospective reimbursement successfully reduced federal Medicare expenditures for hospital stays, however, options must .. be explored to prevent a cost shift to Medicaid. Through the intervention of a case manager, and through identifying variables which predict nursing home placement, I this research will test the extent to which nursing home placements can be prevented. Not all nursing home placements are undesirable. At some level of depen, dence and frailzy, there is no more appropriate or cost-effective option other than 24 hour per day supervised care. The intervention in this research assumes that nursing home placement may be the most appropriate service for some patients. However, when other services are appropriate for the patient and when the services are both more appropriate and less costly, nursing home admission should be prevented. 3

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Trends Impacting Health Care A number of environmental forces and trends have impacted the health care industry, government policymakers, managers of publicly funded health services, and older patients. These trends precipitated the federal Medicare policy changes, which authorize,d prospective payment systems and created one spillover effect, premature nursing home admissions, which will be addressed by this research. A description of the tour trends which led to Medicare policy changes follows with corresponding implications. Trend 1: Changes in the Health Care Industry The first trend is the dramatic change in America's health care industry. Coile describes the health care industry in a state of" fundamental restructuring of supply and demand, moving rapidly away from a predictable pattern of cost-based '' payment to the rough and tumble of a competitive market" (Evashwick & Weiss, 1987, p. 12). He cites thirteen different factors which have triggered cost containment strategies ip health care: rising Medicare costs, the federal deficit, Social Security insolvency, the 1981 to 1983 recession, 15 to 30 percent annual increases in health care and hospital costs, lack of controls over hospital and physician utilization, increasing out-of-pocket costs, rising co-insurance costs, malpractice, a non-competitive fee-tor-service system, rising health maintenance organization enrollments, and' a surplus of physicians. Trend 2: Growth in the Older Population The second trend impacting the health care industry is the growth in America's older population. Ute expectancy has increased by 12 years since 1940 4

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'li ,, I II, i :,: making the 75 older age group the fastest growing segment of the older "I .'1 population. This growth will challenge the health care delivery system when the '' post-war baby poem results in a boom to the elderly population between the years ' I I ,ol 201 0 and Trend 3: Esca.!'ating Medicare Care Costs Third, the Medicare program is only two decades old, however, trends of 1: the increasing dlder population and escalating costs of medical care precipitated new cost contai:nment measures within the last decade. Hospital care was targeted I' : II, for cost containment since charges for hospital care are approximately two-thirds of the medical expenditures for older people. These cost containment measures, :1] called prospective hospital reimbursement, contain 468 "diagnosis related groups" I, (DRG's) for medical conditions. Medicare sets fees in advance for the amount it will pay for each DRG. Since the implementation of these measures in ', 1983, major have occurred in patient care. Trend 4: Increasing Admissions to Nursing Homes .. 1: The fourth trend impacting the health care industry is the 27 percent I increase in the number of older patients discharged from hospitals to nursing ':1 homes since the. hospital prospective reimbursement policies were implemented in il 1983. Since patients spend their financial resources and become eligible for .:'! Medicaid coverage in approximately 13 weeks of admission to a nursing home, ' II Medicaid expenditures are on the rise. Hospitals are under increasing pressure to discharge older patients earlier, however, more patients are being discharged to 'il: nursing homes rather than to their own home with services or to another less costly 5

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' :I ,: housing Discharging patients to nursing homes, when other less costly ':,1: :11' services are :appropriate, merely shifts the cost for the government from the Medicare to Medicaid. Joseph ;Califano, former Director of the U.S. Department of Health, Educa. ;, I, II '' tion and calls this cost-shift phenomenon a government "shell game." I Government in particular has got to get its act togeth ck stop playing the health care cost shell game and ',,!I' turn its attention to instituting some system-wide reforms .... there isn't much time left to get an efficient health care delivery system. The graying of America is forcing the issue, with a rapidly increasing number 9f older citizens demanding more and more in expen. high-technology hospitals and nursing homes. Our nation cannot tolerate the shell game much lon ger. (Califano, 1986, pp.166-167) Implications of Trends on Future Policies :; :!: The implications of these four trends concern policymakers, public managers and health 9are funders. This research focuses on one aspect of the health care system wrl'ich can be reformed through new interventions. In order to prevent the "shell game" Califano describes, a closer look at the hospital discharge planning offers new insights into intervention options. Recent statistics ,II I 111 which show a ::rapidly increasing rate of nursing home admissions have been interpreted to syggest that time pressure from DRG's is forcing hospitals to dis,, ! charge more elderly to nursing homes (Swan, de Ia Torre & Steinhart, 1990). :: This pattern is qf particular concern because of the tendency for nursing home placements to b:ecome permanent (Fitzgerald, Moore, & Dittus, 1988). Clearly, an II ', :i examination of and nursing home placements from hospitals is needed. '', i: ,, :;i .i! ,, 6 __________________________

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',, '' Hospitalizations stimulate housing crises, as well as health crises, for many elderly who will need significant personal and health assistance following hospital- li ization. Furthermore, the supportive housing needs of some elderly come to the attention of health care professionals during a hospitalization. It is increasingly evident that hospital professionals are in a position to recognize needs for support ive services for .. the elderly, and that the discharge process is mandated by Medicare to implement services and housing changes to meet those needs. At this historical juncture, however, little is known about how much housing change occurs as a function of the discharge process, which' populations are most likely to require new housing placements, and how adequately prepared discharge planners are for this task. The Problem I I" 'I Rationale for the Study Health care in America is in transition. As the older population increases and costs of health care rise more rapidly than the Consumer Price Index, government policymakers and managers must continue to seek options which will 'I control costs without hurting the quality of patient care. This exploratory research was developed after consideration of: 1. The significant increase in the older population; 2. The change in Medicare hospital reimbursement Which dramatically decreased the length of hospital stay for older adults; 3. The corresponding increase in nursing home admissions; I' 11 I 'II, I 'I, 7

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''' 4. ; .The drastic increases in Medicaid expenditures; and : ' ' 5. The influence which hospitals have on nursing home placement. ., '" Althoug,h health care financing is extremely complex, the data indicate direct correlations these changes (U.S. General Accounting Office, 1983; Lammers, 1984;). With the advent of prospective reimbursement to hospitals, .,, Medicare length of stay decreased by 60 percent. Simultaneously, the I' number of discharged from the hospital to nursing homes doubled. Of even greate( cdncern is the 300 percent increase in the number of patients discharged to homes who were still in nursing homes six months after admission Leventhal & Easterling, 1987). Patients residing in a nursing home for six rl,9nths are likely to "spend down" all of their financial resources and !I go on the Medi9aid program for the duration of their lives. As a policy, prospective reimbursement through DRG's successfully I reduced Medicare expenditures by millions of dollars. Simultaneously, however, Medicaid expenditures for nursing home care increased. In order to prevent this cost-shift from. to Medicaid, an intervention is necessary which allows the '1: cost savings from early discharge but prevents either premature institutionalization ' I to nursing or readmissions to the hospital. '., The purpose of this exploratory research is two-fold. First, this research will test one option for intervention which will delay or prevent the cost shift for the government, saving millions of dollars annually if introduced on a national .,, p scale. Second; :this research will collect data on older patients at discharge to determine the: variables which predict nursing home placement (e.g., gender or 8 :, :i

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I ', marital status).' Public managers and policymakers need to explore new options which save mo:ney and simultaneously maintain the quality of patient care. Schneider arid Guralnik (1990) called for vigorous pursuit of cost containment, ,' while pursuing other approaches to limiting future health care costs. The investigation in this exploratory research is timely since any cost savings in federal or state government expenditures today may prevent unnecessary expenditures in the future when the older population booms. ,' ,I Statement of tHe Problem An effective intervention is necessary to reduce the documented increase in hospital discharges to nursing homes, ensure the provision of appropriate services for frail discharged patients, and prevent the unnecessary increase in admissions to the Branch and Jette (1982) criticized evaluators and researchers for determining the cost-effectiveness of programs without adequately examining the program effect on the very individuals who were at risk and targeted for the outcome of the.intervention (Shapiro & Tate, 1988). This research was developed to propose an ir;1tervention in the form of a case manager and test the outcome of ,! 'I the older who are at risk of institutionalization. An exploratory research I approach is ess,ential in order to test the hypothesis for intervention. In order to target individuals who are most at risk of institutionalization after discharge, variables which .predict nursing home placement will be identified through this research. : '"i 9

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': '' t I': The purpose of this exploratory research is to: .: 1. the demographic characteristics of the hospitalized popula-I I: : tion age 75 and older in 5 Denver metropolitan area hospitals; '. '' 2. :.:Identify the extent to which hospitalization provokes housing :,changes for older adults age 75 and older on Medicare; '' 3. Determine the nature and predictors of those placements; 4. : petermine the permanence of the placements; 5. Oetermine the extent to which the intervention of a case manager at 1: can prevent or delay nursing home placement at dis, 9harge; 6. [)etermine patient satisfaction with hospital discharge planning; 7. :Gescribe the discharge planning process through observation; 8. S!Jrvey hospital discharge planners regarding their comfort with the ,, responsibility of housing placement at discharge; and I 9. Recommend further quantitative or qualitative research to follow-up c:m the findings from this exploratory research. :' Anticipated Impact of the Intervention The of a case manager, familiar with the full array of in-home '' support servipes and the variety of housing alternatives, will be able to prevent llj home placement for a percentage of the older adults partici pating in this re$earch. Further, it is anticipated that a case manager following I, older adults for::eight weeks after discharge, will encourage the movement of ,,,, I' patients to less;,restrictive and less costly housing options as their recuperation 10

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'I I I i 1 ii ,I :r I progresses. it is anticipated that gender and marital status are predictors of '' :1 'I nursing with unmarried women, who do not have a caregiver at :1 home, as the;rriost likely individuals to enter a nursing home at hospital discharge . !j I''] Fourth, it is anticipated that variations will occur in the degree of satisfaction with the discharge: Jlanning process. Demographic data from this research will be of 'I ri interest in order to target the population which will receive the greatest benefit from I ':j future policy ch:Fnges. Finally, it is anticipated that hospital discharge planners are :1 better preparedi to make referrals for home health services or nursing home care ,, ,i 'I and less prepared to select housing alternatives. '' :! The section of this introductory chapter describes the methodology or ,, !l investigative procedures used to conduct the research. Both qualitative and :1 quantitative data were collected. Chapter 2 reviews the contemporary research on I .'1 Medicare cost the impact of Medicare prospective reimbursement on ':1 I nursing homes find on hospital discharge planning, and a rationale for the case ,d I management intervention. Research results are presented in Chapter 3. The ,, il results include patient characteristics of the sample, predictors of housing placeii I' lj ment at hospital discharge, predictions of housing level eight weeks after dis., charge, a comparison of hospital differences in housing placement, the effects of ;I case intervention, patient satisfaction with hospital discharge planning '::: services, and:.thk perception of discharge planners regarding their services. ,: I ,, ,, The final chapter reviews the conclusions of the research and discusses the I I research A series of recommendations for future research and public 'I :[ 11

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policy revisions were incorporated to influence public policy change as a result of this research. . Investigative Procedures This involved three components. The effects of a case manager II II on the discharge practices of the hospitals were evaluated. Qualitative research data were collected to describe the hospital discharge planning process. Descriptive data were collected on persons over the age o! 75 admitted to five hospitals in metropolitan :D:enver. Data on patient satisfaction with discharge planning were collected and the perceptions of hospital discharge planners regarding their services were .evaluated. The methods used are described below. Preceding each section is an of the procedures used for that segment of the research. i Table 1.1 the research objectives, data collected and the method of data I I collection. Descriptive Data Collection Five hospitals in the Denver metropolitan area participated in the study. The 22 hospitals in the Denver metropolitan area were invited to a briefing on the research; six.' Hospitals self-selected their facility for participation. Five diverse hospitals were chosen. The hospitals are representative of large, medium and small urban hospitals and a psychiatric hospital. The participating hospitals were Presbyterian/St. Lukes, Mercy Hospital, St. Anthony's Central, St. Anthony's North, and Mt. Airy. Table 1.2 shows the number of beds and the number of discharge planners at each participating hospital. '" I i! 12

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'I: I' ,'1 Table 1.1. Research Objectives and Methods of Data Collection. 11: Objective : i Determine discharge)planners' per ceptions of the qua!iiy of their post hospital in-home placement ser vices. 11., 'I' Determine which variables predict nursing ho(ne placement. Data Collected Method of Data Collection Ratings on hospital's ability to provide Questionnaire administered to discharge the following discharge services to planners at each participating hospital. frail elderly: immediate housing referSix different types of service assessed. ral at discharge, housing referral 2 (See Appendix G). months after discharge, mental health, home health, family counseling and referrals for other human services. Housing level at admission, gender, age, marital status and functional heaHh rating. Patient discharge abstract completed upon admission at hospital (See Appen dix A). Compare housing at discharge, Address at admission, discharge ad-Patient discharge abstract. (See Appen-two weeks after djsctiarge and eight dress and phone #, name of dix A). weeks after discharge. where patient is discharged, address at 2 weeks and housing level reported I : at end of 8 weeks. Compare the of hospital visits Functional health of patient, number of Functional health reported on patient made at 2 weeks 8 weeks after hospital visits cited on abstract at 2 abstract. Number of hospital visits re-discharge controlling:for functional weeks and 8 weeks. ported in 2 week follow-up and 8 week heaHh. follow-up conducted by telephone inter-: viewer. (See Appendix C and D). Determine the the case man ager had on housing llevel at dis-.' il charge, 2 weeks discharge and 8 weeks after Describe the hosi)ital discharge plan-ning process. . 1', :. List of patients seen by the case man-Case notes taken by case manager. ager. Housing level of patients at Housing level reported in 2 week and 8 discharge, 2 weeks after discharge week follow-up. (See Appendix C and and 8 weeks after discharge. D). Observation on-site for two days at a local hospital. Observation during data collection at -the 5 participating hospitals. Extensive notes about observations. Unstructured questions. The fiveparticipating hospitals discharge approximately 3,160 patients monthly of whiqh 34 percent (1,086) are Medicare discharges. The hospitals were II: uncertain how many Medicare discharges were patients age 75 or older. :. ':1 A brief abstract was attached to the chart of persons over age 75 admitted " 1.:. ,ji, to the five hospitals. The abstract, filled out by the patient's discharge planner, '' '' included information about the patient's age, gender, marital status, housing at admission, housing at discharge, and a general health rating. Two weeks after I '1;1 1:, '' 13

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Table 1.2. Hospitals Participating in the Research. 'ij' T olaf Discharges Number of Medicare Number of Discharge ' 'I Hospital Licensed Beds Per Month Discharges Per Month Planners Presbyterian/St. Luke's 465 662 224 3 Mercy 386 409 218 4 St. Anthony's Central 698 1,544 495 9 'i St. Anthony's North 196 435 139 3 MI. Airy 100 110 10 5 discharge, patients were contacted by telephone to request information about the number of doctor visits and the number of hospital visits since discharge, and their satisfaction with the discharge process. Eight weeks after discharge another telephone call. was made to each patient to request the same information in I addition to their. current housing status. Procedures used to meet the challenges of telephone data collection with elderly persons who experience hearing difficulties included simplified questions, slower conversations, and the use of informants. Subjects: Sampling Procedures and Description The population or universe is the total number of Medicare recipients age 75 and older who are admitted and discharged from hospitals in the Denver 14

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I,: metropolitan .area. The sample for this research consists of all the Medicare recipients 75 and older who were admitted to five metropolitan Denver area hospitals over months. Data was collected over a six month period of time on I 'I all admissions to five hospitals in the Denver region who were at least 75 years of . age and were funded by Medicare. A total of 1,089 abstracts were collected by the hospitals for. this research; 1 ,040 had sufficient information for inclusion in the study. Admissions' staff in each of the five hospitals were responsible for attaching an abstract data collection form (see Appendix A) to the chart of each patient age 75 and older on Medicare. Practices differed considerably, however. One hospital required patients to sign an informed consent form in the admissions office before an abstract cpyld be attached to their chart to begin data collection procedures , I! (see Appendix.B). Another hospital relied initially upon the Medical Records staff 'I ,, to complete data from the chart after the patient was discharged. In this hospital, after .several charts with abstracts were in Medical Records with no progress toward data recording, a new policy was implemented. The department in ,, which the patient was treated became responsible for completing the forms, at the request of the social service staff who were the liaisons to the project. A sufficiently large number of data points were collected to assume that the data will provide a useful profile of admittees in the targeted group age 75 and older. Measures The measurement instrument used in this portion of the research consisted of a data collection form (abstract-see Appendix A} which was completed in three 15

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'' j, .'' stages. The first stage was completed by a hospital staff person (the intent was for it to be the discharge planner although some were completed by other staff as described abo\ie). The form requested the name, address and telephone number I.: of the patient, age, gender, marital status, a global health rating at discharge (on a 1 to 3 scale ranging from very good to very poor), and information about discharge housing. The second set of questions was completed (see Appendix C) based on information over the telephone from the patient (or in some cases an '1: informant) two weeks after discharge. The patient reported the number of doctor visits and hospital visits during the two week period since discharge. Patients also ' were asked to rate their satisfaction with the hospital discharge planner. The third series of questions were also completed during a telephone call I with the patient: or informant eight weeks after discharge (see Appendix D). Again, : patients were asked to report the number of doctor visits and hospital visits during the eight since discharge. They were also asked about their current housing and the number of times they had moved since discharge. A satisfaction with hospital discharge services was again requested . I ,! Procedure : Once the initial set of information was provided by the hospital on the abstract form, a research staff member went to the hospital to collect the forms. At two hospitals, follow-up telephone calls were required to be made at the hospital so no personal information about the patients was removed from the premises without patient permission. For the remaining hospitals the abstracts were brought back to 16

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the office. There were some cases in which the abstract was not received from the hospital untii the second full week had passed. In this case the two week call was not out patients were contacted at eight weeks. telephone calls were made in the second week after discharge. Each caller identified herself as a representative of the hospital in which the patient had been treated. The callers were trained in the telephone protocol, and were chosen for their excellent communication skills with the elderly in particular. One caller, in charge of the data collection for the first several months, had served in ,'II geriatric social :services for over ten years. The other caller was a graduate student in a social work program with an emphasis in geriatrics. Relying,upon telephone contact to gain information made the large number of follow-up contacts possible. Face to face visits on the large subject population were considereq impossible. Informants were used when the patient was incapable of providing the information. In some cases this was a family member or neighbor. In nursing homes it was often a staff person who used his or her recollection or the patient chart to answer questions about the number of doctor and hospital Gathering follow-up data from nursing home patients was 'I 'I particularly as the information was not readily available in a single place (e.g., the patient chart may have been at the nurses' station, or the social worker may have maintained such records in his or her office). It was useful to rely upon a single source within the nursing home for all data collection whenever j I possible. 17

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'' ;i I. II Once data collection was complete (including the two week and eight week follow-up calls), patients' housing was placed into categories (e.g., own I home, own with services, congregate housing, or nursing home.) Abstracts were prepared for data entry by coding all information into numerical codes (e.g., hospitals were assigned numbers). Before submitting the abstracts to the data enterer, all personally identifying patient data (names, phone numbers, and addresses) were blackened with heavy markers. In cases where calls were made from the hospital buildings, the identifying information was removed before the I abstracts were allowed to leave the hospital. Data were entered on microcomputers using "Lotus 2.0" software. An acceptable range was defined for each variable in order to minimize data entry errors. Data analyzed using Statistical Packages for the Social Sciences, Form "x" (SPSSx). Subjects for whom no clear age information was documented were removed from the sample, and missing data were left missing on a variable by variable basis. No substitutions were used. Case Management Intervention During the middle two of six months of data collection (as described above) in each hospital, a case manager was available to the discharge planning department of the hospital. In the three hospitals which made use of the case manager's services, direct referrals by discharge planning staff appeared to be the most frequent way of.I.Jsing the case manager. The case management service consisted of assessment.(of functional abilities, resources, and patient and family preferences), housing placement services (identifying appropriate types of housing, gathering 18

PAGE 31

:! information on availability in particular housing sites, and in some cases, facilitating the move), and follow-up services for up to two months after discharge (assess ment of appropriateness, and facilitating a new housing placement if appropriate.) The data collection described above was carried out over a six month ,!i period in each hospital. This period was divided into three phases: baseline data collection, interVention, and post-intervention. The case management intervention occurred during the third and fourth months of data collection in each hospital. During these months, a case manager was available to receive referrals for i direct interve'rlti,pn or on a consultative basis from the discharge planners of the !r hospital (including social service staff, physicians, nurses, etc.). Subjects 'I II All patients age 75 and older who were on Medicare at hospital discharge were targeted for this research. All patients on whom abstracts were obtained (as described abov,e under the Descriptive Data Collection system) during months three and four. at each hospital were included in the "Intervention" data. In order to ensure interna'l:;validity, the homogeneity of patients was compared from pre-test to post-test (the post-intervention phase). Of the 1 ,040 Medicare admissions over age 75 sampled, 62.7 percent were female. A majority were widowed (58 percent), although 33.5 percent were married. Consistent with national demographic trends, males were far more likely to be married with a living spouse than females (57 percent and 18 percent respectively) .. The average age of admittees was 82.2 (SD=5.4), with 30.9 percent 19

PAGE 32

in the most frail 85 and older age range. The oldest age groups were most likely to be female widowed. Table 1.3 provides detailed demographic information on the sample'. : , 'I Demographic information is presented separately for each hospital in Table 1.4. As is there are no differences in frequency of admissions at each hospital by gender, or marital status (chi-squares are non-significant). The hospital samples differ .oh age (as an interval variable; F=5.48; df=3.1 036; p<.001) and 'I' .,, functional health (F=3.84; df=3.752; p<.01 ), demonstrating the variability in patient pools from which hospitals admit (age means range from 81.5 to 82.9 and functional health means range from 2.1 to 2.4). A functional health rating of 2 represents patients with minor illness or disease; a rating of 3 represents significant illness or disease. in functional health from a mean score of 2.1 in one hospital to ,, 2.4 in another, hospital reflects a greater number of older patients with significant illnesses in hospital with a mean functional health score of 2.4. I :11, ,,, Housing at Admission and Discharge Almost (72 percent) of frail elderly were admitted to the hospital from their own but less than half (44 percent including 9.2 percent using inhome services):were able to return to their own homes. (See Table 1.5). Thus, discharge servi9es included aid with housing placement in over one-fourth of all frail elderly hospital admissions. It is important to recognize that admission and discharge housing information ,,, were collected by hospital staff who provided addresses and, where appropriate, names of housing units, but these data were not initially recorded by the housing I '1i' ,'': 20

PAGE 33

', Table 1.3. Demographic Characteristics of Admissions Over Age 75 at 5 Denver Gender _lL 0/o Male 386 37.3 Female 650 62.7 75-79 396 38.1 80-'84 323 31.0 85-89 202 19.5 90-94 95 9.1 I II: 95.:99 24 2.3 100+ 0 0 Marital Status Married 340 33.5 Widowed 589 58.0 Div.orced/Separated 52 5.1 N.ever Married 35 3.4 Housing Level Own home 689 68.8 Owh home with services 32 3.2 Relative's home 30 3.0 Congregate housing 48 4.8 Assisted living 9 0.9 home 194 19.4 I' :I 21

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.. i ''ji Table 1.4. Characteristics by Hospital. HOSPITALS 1 2 3-4 5 Gender N % N % _li_ JL _li_ % Male 128 37.2 70 33.7 181 38.5 7 50.0 Female 216 62.8 138 66.3 289 61.5 7 50.0 Age 75-84 235 91.1 131 92.3 342 91.9 11 100 85-94 17 6.6 11 7.7 27 7.3 95 + 6 2.3 3 .8 Marital Status Married 109 32.1 62 30.1 164 36.0 5 35.7 Unmarried 231 67.9 144 69.9 292 64.0 9 64.3 categories as used in this study. Research staff assigned the housing to categories. Because addresses of housing units which could not be identified (either on the abstract or from lists of housing types} as some particular unit were automati cally assigned: home," the category "own home" likely represents an inflated :.: figure. An number of persons (31.7 percent compared with 20.3 percent .. at admission} released to an environment with strong supportive self-care and/or health care services (assisted living facilities, rehabilitation or extended care 22

PAGE 35

'' i Table 1.5. Housing Levels at Admission, Discharge, and Eight Week Follow-up. Admission Discharge 8 Weeks Housing Level _N_ % _N_ % _N_ % Own home 689 68.6 445 44.0 218 33.9 ,I Own home with Services 32 3.2 93 9.2 146 22.7 Congregate .. 48 4.8 20 2.0 16 2.5 Relative's Home 30 3.0 62 6.1 39 6.1 Assisted Living 9 .9 9 .9 10 1.6 Rehab/Extended Care 52 5.1 1 .2 Nursing Home* 195 19.4 255 25.2 156 24.3 ' Hospital 5 .5 2 .3 Died _.11 7.0 __. 8.6 Total li 1,004 100% 1,012 100% 643 100% *Includes in-patient hospice facilities, nursing homes, or hospitals). Note that 7 percent of the sample died while (This percentage may be artificially low because several abstracts for persons who died during hospitalization without :I sufficient information for inclusion in the study). Measures The effectiveness of the intervention was evaluated by analyzing for differences in the data collected at the two and eight week follow-up contacts, across the pha$es of the project. It was expected that the case manager's I presence at the hospital would have an impact on the patients' discharge plans because of her:.specialty knowledge, and because she would be able to track the patients for two. months after leaving the hospital to ensure follow-through of service referrals and, when necessary, to assist patients in moving from one type 23

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, 'I 'I I of housing to aMother. Thus, the effectiveness of the intervention was analyzed by ,, I ,, comparing all, discharges from the hospitals during the baseline and post-intervention phases the discharges during the intervention phase on the outcome variables. A more specific analysis was also conducted to determine whether patients assisted directly by the case manager differed on the outcome variables. 'I ;; ,, Design A multiple-baseline design was used to pace the onset of data collection I'' !1.::. and intervention procedures at the hospitals. A multiple-baseline design is a "single subject design in which the treatment condition is successively administered to several subjects or the same subject in several situations after baseline behaviors have been recorded for different periods of time" (Christensen, 1991, p. 344). By the use of. the pre-test, intervention, post-test design, behaviors exposed to the I treatment, which is a case manager, while all others remain at baseline, provides some evidence for the effect of the intervention. "It becomes increasingly implausi ble that rival hyJotheses would contemporaneously influence each target behavior at the same time as the treatment was administered" (Christensen, 1991, p. 345). The first hospital completed baseline data collection and was ready to initiate interve,ntion before the second hospital became involved with the project. The schedule: the project was established to ensure six months of data collection :'1: in each hospital,' followed by two months of follow-up data collection (by telephone). The purpose of the multiple-baseline design (staggered timing of data collection ,/ and intervention) was two-fold: 1) to allow the case manager to be full-time at each hospital during its intervention phase, and 2) to control for industry-wide policy ,j I 'I :! ', 'I I' 24

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changes which might coincide with one phase of the project (e.g., changes in reimbursement procedures or discharge policy) and thus might be a confounding :I: cause for any differences found among the phases. Delays in: the process of contracting with the five hospitals for their partici :: pation resulted in a shortened data collection period for the research. This neces-sitated adjustments to the data collection periods in some hospitals, and required I' the case to divide her time between two hospitals for a portion of the intervention peri:o,ds as shown in Table 1.6. Table 1.6. Multiple-Baseline Design. : i 1 Hospital2 Hospitals 3 & 4 Hospital 5 Pre-Test 4/0;1 -8/30/88 5/01 7/31/88 7/15 8/30/88 3/21 5/07/88 Intervention :1, 8/01 -9/30/88 9/01 10/31/88 Post-Test 10/01 -11/15/88 11/01 12/31/88 These modifications did not compromise the intent of the multiple-baseline I design, and the1 case manager's report was that the double assignments to I hospitals was not an undue strain. 'II Procedure A meeting: of discharge planners from hospitals throughout the eight county 'I Denver region was called to initiate interest in the project. A letter describing the :.: project and requesting participation was mailed to the administrative head of the I' Discharge Planning department in all 22 hospitals in the region. The scope of the ''I' 25 :i I,

PAGE 38

l I I' :jt :: project was described to the attending discharge planners who were encouraged to I contact their hqspital's administrator indicating their level of interest. Six hospitals :I! II expressed inte.rest in the project. One hospital, Rose Medical Center, was not ,I chosen since the hospital followed patients after discharge and the research results could have oofn affected due to procedural differences at this hospital. Five .l: hospitals self-selected to represent a diversity of organizational characteristics, as '' I well as patient,j,characteristics. The participating hospitals were Mercy Hospital, Mt. 'I' Airy Hospital, Presbyterian/St. Luke's Hospital, St. Anthony's Hospital North and St. Hospital Central. Agreements with each hospital were :I, I ,i! negotiated the parameters of participation. They included an agreement I' about the hospital's responsibility to participate in data collection and intervention for which they' receive payment of one dollar per abstract collected. A i' I, liaison was appointed from each hospital to coordinate the data collection and intervention phase. ll Much responsibility for ensuring the case management services and data ,,, collection fell to the hospital liaison, the case manager and the two persons making ',, the follow-up (who tracked the data). The case management intervention ar t '' rangement whih appeared to be most effective was direct referral from social services or planners (of any discipline). A direct referral allowed the '' I case manager to contact the patient or family on the floor of the hospital and initiate an asse:ssment at that time. !:. '! .1. '' I : 1: I, I 26

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. I : 'I The case manager's activities included assessment, housing placement, and referral for,services. In addition to these discharge services, the case manag'" : ,tl\, er was able to. ,tnaintain contact with the patient and family for as long as two !, 'I months to ensure the follow-through of the service referrals. The case manager also re-evaluated housing needs, and facilitated additional moves to result in an appropriate living environment for the longer term. It is im'pprtant to acknowledge the diversity in the time required by different I':; patients. ,sbme clients, 20 hours of work was required to assess, track, and implement their:housing and service needs. It appears that if the case manager had been used :extensively by all hospital staff, a second case manager would have been due to the amount of time required for many patients. Following the intervention phase, hospitals continued collecting data for two I months during the post-intervention phase. During this period, the case manager was no longer on-site to work with hospitalized patients, but was involved in tracking the adjystment of patients with whom she initiated contact during the intervention phase. The same case manager was consistently used throughout the ,' .,;, I 1 1 research to eli'"i'inate assessment and referral biases across case managers. 1: ,, In order :to prevent problems with external validity, five diverse hospitals ' were selected afld the limited timeframe for conducting the research was manageable since a 1o11ger timeframe could contribute to changes in staffing or hospital ,, policies. The individuals conducted follow-up throughout the research to ,, ',,ill prevent in coding. To ensure homogeneity in the sample, the study was limited to the and older population. Although more detailed health status data ':J I:': : li : ,'1 j! 27

PAGE 40

I: j 'I would have the results, the research was designed to ensure as much convenience as:. possible for participation; a one dollar fee was paid to each : I '1 'li hospital as an 'ihcentive to complete the data abstracts. The hospitals were I' I 1: geographically lpcated around the region to ensure diversity in neighborhoods, i service options,'' and patients. Appendix E is a map showing the locations of the participating hospitals. Qualitative Data r The exp!oratory nature of this research provides preliminary data from which , further quantitative analysis can be conducted. The qualitative research component provides another source of data through close-up, first-hand inspection of the discharge plann!ng process. A number of principles surrounding qualitative I 'I research apply !;Jere (Van Maanen, 1982). The discharge planning process was !t more dynamic less formally structured than originally anticipated. Qualitative ! research provided an opportunity for "analytic induction" or first-hand inspection in the hospitals. Due to the hospitals' proximity and the ability to observe normal behavior in a discharge planning environment, the data interpretation and recom-,' I ,h,, :i: mendations for further research were positively impacted. ,, Qualitative data were collected during the research at the five participating hospitals. In addition, observation time was spent at another suburban hospital to describe the hospital discharge planning process, the work environment, and to observe which could positively impact the discharge process for older II '' adults. The results of the qualitative data collection are summarized in Chapter 3. ' i 28 ',, ,:

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',,,. CHAPTER 2 ANALYSIS OF CONTEMPORARY RESEARCH ON MEDICARE COST CONTAINMENT AND THE IMPACT ON HOSPITAL DISCHARGE PLANNING AND NURSING HOME ADMISSIONS This review of contemporary research and literature includes demographic projections tor tre older population in the Denver metropolitan area, a review of the I Medicare program, a discussion about major transitions in federal Medicare policies, legislat.ive targets for control of Medicare costs, Medicare policy and its II II' 111 impact on nursing home admissions and hospital discharge planning, housing very old patients after hospital discharge, and a rationale for case management intervention. Demographic Projections The population is growing and is expected to continue to grow in the future. The general population in the metropolitan Denver region is expected to grow by 39.8 pe,rcent from 1988 to 2010 (Table 2.1) while the age 60 and over 1111; : :1 population will'g1row by 80.5 percent during the same time period (Table 2.2). The age '60 and older population is growing at twice the rate of the general I population. The1.substantial growth in older adults is a national phenomenon; one '' that concerns policymakers and managers who consider the corresponding health care costs. In over half (53 percent) of the older population resides in ' I' the eight county:metropolitan region. This concentration of older adults impacts

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Table 2.1. Denver Metropolitan Area Forecast Absolute and Percent Change of the,Total Population: 1988-2010. COUNTY 1988 TOTAL 2010 TOTAL ABSOLUTE PERCENT POPULATION POPULATION CHANGE CHANGE ADAMS 273,300 433,100 159,800 58.5% ARAPAHOE 398,650 579,500 180,850 45.4% BOULDER 221,650 302,000 80,350 36.3% CLEAR CREEK "' 8,500 14,000 5,500 64.7% DENVER 508,150 573,100 64,950 12.8% ,I DOUGLAS 50,200 195,700 145,500 289.8% GILPIN I ,',, 3,500 6,100 2,550 71.8% JEFFERSON 432.100 546,500 114,400 26.5% TOTAL 1,896,100 2,650,000 753,900 39.8% Note. Calculated from DRCOG, 1988 Population and Household Esti mates, (Tables 5 and 12) 1988, Denver: Denver Regional Council of Governments and 2010 County Population Forecasts by Age, 1989, 1 r:>enver: Denver Regional Council of Governments. Colorado's Medicare, Medicaid and health care expenditures. Therefore, the eight ',. county metropolitan area and the fastest growing component of the older population, those age ..75 and older, are targeted for this research. The metropolitan i 'I' region include.s /\dams, Arapahoe, Boulder, Clear Creek, Denver, Douglas, Gilpin and Jefferson. c'bunties. ,',1 Table 2.3 reveals the significant growth in the age 75 and older population from 1988 to 201 0. In 1988, the eight county Denver metropolitan area was home ' to 66,900 adultS age 75 and older. By the year 2010, this age group is expected to '. iii 'I 30

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'' I :,'j.: ':I: Table 2.2. Denver Metropolitan Area Forecast Absolute and Percent Change of I I the 1 60+ Population: 1988-2010 COUNTY 'I 1988 60+ 2010 60+ ABSOLUTE PERCENT I ' POPULATION POPULATION CHANGE CHANGE I ADAMS 29,546 58,483 28,937 97.9% II ARAPAHOE .. ,:; 38,156 93,575 55,419 145.2% BOULDER : 21,910 48,802 26,892 122.7% 'I I' CLEAR CREEK 886 2,039 1,153 130.1% DENVER DOUGLAS GILPIN JEFFERSON TOTAL Note. ' d 94,675 ,, 105,577 10,902 11.5% I' II, 94,675 15,272 11,951 359.9% I I 358 1,084 726 202.8% I I' 48,330 103,391 55,061 113.9% '!' 'I ''. 1: .I: l 237,182 428,223 191,041 80.5% I Galculated from DRCOG, 1988 Population and Household Esti:1 mates, (Tables 5 and 12), 1988, Denver: Denver Regional Council of Governments and 2010 County Population Forecasts by Age, 1'989, Denver: DRCOG. I 1: '1: II I grow to 115,183 representing a 72 percent increase. This research focuses on the age 75 and olpr population for three reasons. First, it's a growing segment of the older population. Second, the age 75 and older population is likely to experience more than one chronic health condition requiring support services after hospital II discharge. 1j: !' Third, th population age 75 and over, only five percent of the total population, accounts ffr 16 percent of the hospital discharges and 22 percent of all hospital days Center for Health Statistics, 1990). Growth in the age 75 and older population will precipitate increased utilization of health care services 'I I 'I' il' I, 31

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1988 1988 %0160+ 2010 60+ 2010 75+ %01 60+ Absolute Change %Change 60+ 75+ Population Population Population Population 75+ Population 75+ Population Population Population 1988-2010 1988-2010 ADAMS 29,546 6,664 22.6 58,483 16,341 27.9 9,677 145.2 ARAPAHOE 38,156 21.9 93,575 23,140 24.7 14,765 176.3 .. ""=== -----------' BOUI:.DER c c6,735 --30.7 .. ... 11,345 23.2 ----4,610 68.4 CLEAR CREEK 886 250 28.2 2,039 401 19.7 151 60.4 DENVER 94,675 32,607 34.4 105,577 33,498 31.7 891 2.7 DOUGLAS 3,321 813 24.5 15,272 2,980 19.5 2,167 266.5 GILPIN 358 126 35.2 1,084 282 26.0 156 123.8 JEFFERSON 48,330 11,330 23.4 103,391 27,196 26.3 15,866 140.0 TOTAL 237,182 66,900 28.2 428,223 115,183 26.9 48,283 72.2 Note. Calculated from DRCOG, 1988 Population and Household Estimates, (Tables 5 and 12), 1988, Denver: Denver Regional Council of Governments and 2010 County Population Forecasts by Age, 1989, Denver: DR COG.

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plus increased, Medicare and Medicaid expenditures. Densen (1991) described the ',i I 'If movement of inpividuals through the health services network to demonstrate the I' different utilization patterns for the 65 to 74 and the 75 and older age groups. ,. Figures 2.1 a11d: 2.2 reflect a much higher health service utilization frequency in the 'I' 'i! 75 and older The difference was primarily in the utilization of hospitals and nursing homes. Densen identifies hospitals as the major pathway to nursing homes. In Figure: 2.1, Densen follows 100,000 older adults age 65 to 74. Of the 100,000 individyals, 850 enter a nursing home from an acute care hospital and 400 I 1: enter the nursing home from their own home. These admission rates increase i, substantially in 'the age 75 and older population. In Figure1 2.2, Densen tracks 1 00,000 older adults who are age 75 and older. Of these :1 00,000 adults, 5,400 will enter a nursing home from an acute care hospital and 00 will enter the nursing home from their own home. These figures I ii reflect the for targeting the 75 and older population and the hospital I discharge process for further research. 'I A large of national health care costs is accrued by older adults in I '11 hospitals and nu,rsing homes. The largest proportion went to cover hospital care with nursing home and physician care as the next two largest costs. ii: Older paid a slightly higher share ($73 billion) of the health care costs than ($70 billion). Expenditures for the elderly were largely for "other care" and nursing home care, with physician services ranking third in the 'I .,. I 'I' ' ,, 33

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F1gure 2.1. Annual Movement of Persons 65-74 through tfle Health Care System. I I 100.000 PersOf\s i ; i ; I I I 82.200 ., rc .I I :.' I ::.; li' I L I I j I I I __ _. I 29.700 I jl 1-30!7j I 17.500 12.000 Prso"s : I I j 1-lnpalienl 1---diS.hehab. tac:ilf.y t--Acute care hoSPIIII menial heallh t--I I I ? I ., L----------- 400 ., 700 Nursing home JOO Deaths 2.801 Movement 10 more reslriCiove'rntensive care sellong. - Movement lo less restiCiivellntensive care senng. 1--lacd11y I I I ., I I ., I 1--------------J 1.500 Note: From Tracing the elderly through the health care system: An update (p. 6) by P.M. Densen, 1991, Rockville, Maryland: U.S. Department of Health and Human Services.

PAGE 47

-----.. w 01 Figure 2.2. Annual Mo'll'ement of Persons 75 and Ooer through the Healtli Ca1e Syste111. l J.600 Nursrng home 1 3.100 ., Movement to more reslnCiive tnlensve care senng. -- Movemenl 10 less res:cllve tnlensve care sentng. mental healln I--lacilty 1 I I I I ., I ... oso Note: From Tracing the elderly through the health care system: An update (p. 7) by P.M. Densen, 1991, Rockville, Maryland: U.S. Department of Health and Human Services.

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', '' :,,, ,. ''I. Medicare program. Over $70 billion of the totai health care costs of $175 billion ", 1: II went for care. As expected, Medicaid funds were primarily expended on I elderly nursing: home care ($13 billion out of $20.7 billion). "' Though:.the rate of increase in the Medicare program has slowed in the past i!l ,, few years, Medicare and Medicaid pay a large portion of the health care costs :. for older Americans. Unfortunately, the costs are shifting from Medicare to Medicaid and the older consumers. "Out of pocket health care costs for the elderly have I, more than doubled since 1980 and more than tripled since 1977" (U.S. House of Representative$, 1989, p.8). ,. i! As the primary funding source for health care of the elderly, Medicare ii coverage becomes increasingly important. "Medicare, which pays the majority of health care for older Americans, represents the largest health care expendiI ture for the government" (Schneider & Guralnik, 1990, p. 2337). The age ,. 75 and over Medicare population at hospital discharge were targeted for this ': :;: research due to the greatest potential for impacting the high cost of nursing home care if admission was prevented. I 'I' The Medicare Program I' Basic Components of Medicare This section describes the basic components and the financing of the Medicare Authorized by Title XVIII of the federal Social Security Act, Medicare assists elderly and disabled people with payments for their health care. The program provides two basic forms of protection: Medicare Part A and Part B. ,, ,j q A description of each follows. 36

PAGE 49

Part A, Hospital Insurance, financed primarily by Social Security ,::t:!li payroll taxes,: c'overs in-patient hospital services, and post-hospital care in skilled ,II ,, nursing facilities. Part A covers 31.2 million enrollees, and benefits amount to about $49 billidn. About $45.6 billion (93 percent} of Part A expenditures are for inpatient hospita}services (U.S. General Accounting Office, July 1988}. Eligibility for the Part A Insurance Program is based upon Social Security or Railroad :-: Retirement berlefits provided the individual is age 65 or older or provided the t ., i' person is disab,led for over 24 months. I Part 8, Supplementary Medical Insurance, a voluntary program financed by enrollee premiums (25 percent of total costs} and federal general revenues, covers physician services and a variety of other health care services, 'I ::: such as laboratory and out-patient hospital services. In fiscal year 1986, Medicare I '' 'I '' Part 8 covered1.30.6 million enrollees and benefits totaled abut $25.9 billion (U.S .. General Office, July 1988}. To qualify for the Part 8 Supplementary Medical Insurance Program, disabled persons or individuals aged 65 and older must request coverage and pay a monthly premium. Individual fees cover about a . fourth of the pr9gram cost; the federal government pays three-fourths through I II: general Prior to October 1983, hospitals were paid based upon complex ' Medicare formJias. Medicare theories in the 1960's and 1970's primarily focused on increasing patient access to services, increasing the range of providers in every community and ensuring quality standards. Policies did not encourage hospitals to restrain costs: ::rhe next section describes the policy changes in the Medicare ' II' ''ii1 program. 'il 37

PAGE 50

1,111 ,, :: Transitions in tile Medicare Program :: I' II Although Medicare offers benefits for over 33 million older and disabled beneficiaries, Medicare is an increasing target for federal deficit cutters. Medicare "i ,,, is only one care benefit but its cost to taxpayers of over $108 billion annually keeps it at the of government agendas. I: ,. The causes of the transitions in the health care system are multifaceted. Table 2.4 reves the factors causing changes in health care and the strategies I introduced to. cpntain costs. As a major buyer of health care, the government 0 I il : II shifted to prosp:ective reimbursement to control the rising costs of Medicare. A recent article in the Journal of the American Medical Association de. ;: scribed the rising Medicare cost projections. As the population ages, Medicare costs per persq1n increase. Older adults aged 65 to 74 years annually cost ;I Medicare an average of $2,017; this cost increases to $3,215 for the 85 and older age group. and Guralnik claimed "the total cost of Medicare rises impressively dL(ring the upcoming decades, nearly doubling (in 1987 dollars) to the : :lr I, year 2020. The greatest proportional increases are observed in the oldest age groups," those :,age 75 to 85 and older (Schneider & Guralnik, 1990, p. 2337). I, ,. Given these co,sts, Schneider and Guralnik predict the level of Medicare spending in 2040 to from $147 to $212 billion (in 1987 dollars). i' The Medicare program is only two decades old. However, major demo-: i, 11' graphic and tedhnological changes continue to concern public policymakers. As previously dern,onstrated, the older population continues to live longer and increase ; ,' ' 38

PAGE 51

''!! '!: Table 2.4. Role of Major Factors Affecting Health Care Transitions. ill i f Major Trigger Factors Cost-Containment Strategies i Government :. !; Medicare cost rise Shift to prospective payment li Federal deficits Freeze physician fees ,, Social Security bankruptcy Reduce Medicaid funds I : Business ' 1981-83 recession Use of HMO's/PPO's Health expenses rise 15Form employer health coali-I 1: 30% per year tions ,. Reinstall employee front-end i deductibles and co-insurance 'I II II: ' Insurance 1; Hospital costs rise 15-30% Develop HMO/PPO contracts per year Concentrate on administra-No effective controls over tive services to employers : hospital and M.D. use Require second opinions i : ,, Consumers I Increasing out-of-pocket Enroll in HMO's I costs Engage in fitness/wellness I !!i Rising co-insurance programs !' Malpractice Form consumer advocacy coalitions Integrated Plans Fee-for-service system not Form national HMO's/PPO's :I cost-competitive Create new alliances be',. : Rising HMO enrollment tween providers and insur., Physician surplus creates ance companies labor pool Mainstream MD's join HMO's/PPO's : I' i! Note. From Oyerview: Environmental forces and trends (pp. 11-21) by R.C. Coile, Jr., In Managing the Continuum of Care by C.E. Schwick & L.J. Weiss (Eds.), 1987, Rockville, Maryland: Aspen Publishing, Inc. 39

PAGE 52

il i '.1, ):::j : 'I, :,:!; 'I ,','1' in significant Many new medical procedures are available to prolong the t :i :.:II! lives of our citizens and the price of medical care continues to escalate. This 'i' combination 'qf,i1tactors calls for new theories and approaches to health care for the 'li elderly. Since .. charges for hospital care are approximately two-thirds of the medical : il: : .1. care for older people, and since medical care costs continue to I I I : ! 11, increase at a .wore rapid rate than the Consumer Price Index, new theories were considered to: dbntrol these escalating costs. A combination of factors precipitated increasing costs and eventually led to the theories which promote cost i.i: !I: i!' containment.' (li'he factors which led to increasing Medicare costs were the growth ,: in the MedicarJ, eligible population, drastic increases in medical malpractice I tl 'I. ,, insurance increased physician charges, escalating hospital prices as a ;!: ,' i result of lower i.h-patient usage patterns, and increasing labor and equipment I il prices. I o o! Medicare Cost 'containment 'I' ,, ;:: Medicare cost containment has been a focus of the federal administration i :J :1 for the past years. The Nixon Administration froze all health care costs for 'I one year. In to control rising costs in the Medicare program, President ,, if II! Jimmy Carter: a mechanism which would control costs by limiting hospital '1: ,,, expenditures.: Congress did not support the President's theory; however, Congress l11 :: ':i was concerneqiiabout Medicare costs and requested a study on prospective reim .. !!I ::II bursement for: as a theory which would result in controlled hospital costs. Ill ',i:, The Diagnosis Groups (DRG's) were established. (McGuiness, 1989) ::: I : I II I'"! :: ':i i II' 40

PAGE 53

As a result, the Medicare program created 468 categories of illness called 1!, ', "' Diagnosis Groups. For the first time, hospitals were reimbursed on a fixed ,'!I fee for the diag,hosis or category of illness (e.g., appendectomy) rather than the number of days or tests performed. The federal Department of Health and 1: Human determines the average cost of providing treatment for the ,,, 11, i: diagnosis and sets the hospital reimbursement rates. The theory was that a prospective reimbursement system would create incentives for hospitals to shorten the number of days and prescribe the minimum service for the patient. If I, the hospital costs are less than the federal reimbursable rate, the hospital retains the margin over cost. However, if the costs are greater, the hospital cannot charge more than the i,xed fee. The impact of this particular theory will be discussed further in this crapter. Prospective reimbursement was just one of many major federal policy changes which were enacted in the Medicare program from 1980 to I 11 I ',, 1987. The following section describes the six major laws which the Congressional !II Budget Office. would cumulatively reduce Medicare costs from 1981 to 1987 by $35:9 ,billion (U.S. General Accounting Office, July 1988). The Impact of Major Legislation on Medicare Costs ,, I, In the General Accounting Office presented a report to the Chairman I 111 ,, of the House of Representatives, Select Committee on Aging, regarding the effects of federal on costs to Medicare beneficiaries and the impact on federal programs. section summarizes the major findings of the General Accounting I Office study. ,, ; ' : !II 'L I 41

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The Congressional Budget Office claimed there was a slowdown in Medi,'Ill '! care Part A Hospital Insurance cost growth from 1981 through 1988 as compared ., : with 1970 through 1980. A decrease in the utilization of in-patient hospital services and major changes contributed to the slowdown. The Medicare Part B ,I 'I Supplementary:;Medical Insurance Program costs grew at the same rate during ,. I fiscal years 1 through 1986 as for the prior 1 0 year period. However, savings from the legisl*ive changes affecting Part B during the period were offset by higher : utilization of Part B services. I '. Five of six major laws enacted from 1980 through 1987 were expected I 0 I II to result in Meqicare savings; the other, the Omnibus Reconciliation Act of 1986, was expected to increase program costs. The Omnibus Reconciliation Act (OBRA) of 1980 was the first of the major laws enacted; the Congressional Budget Office !: ll estimated that its Medicare provisions would reduce program costs by about $2.3 billion during fiscal years 1981 through 1985. Table 2.5 contains a summary of the ,' '', !j six major laws.::the major provisions and the estimated cumulative savings projected by the Congressional Budget Office (CBO) and the Health Care Financing Administration '(HCFA). The Congressional Budget Office and Health Care I ! Financing Adm.inistration estimated cumulative savings for each of these six public I laws for fiscal years 1981 through 1987 at $35 billion and $28.9 billion respectively. ' "' According to the General Accounting Office, from 1981 through 1986, the average rate in cost per Medicare enrollee decreased by two percent; a much slower rate than the average growth rate of 2.3 percent from 1970 ,, II. I through 1980. ::"Had the average annual growth rate in cost per enrollee for fiscal 42

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Table 2.5. Estimated Medicare Savings from Six Major taws. Reconciliation Act Date Enacted Major Provisions Decemoer 5, 1980 --Required able charges for physician services be based on the date service was rendered rather than date claim was processed. Law also made Medicare secondary payer for people whose medical ex penses were covered by automobile or liability insurance plan. Cumulative Savings in Billions of Dollars Fiscal Years 1981-87.* CBO HCFA ---.._ __ .-$2.3 .. .. --$:7c __ .. Omnibus Reconciliation Act of 1981 August 13, 1981 Reduced routine nursing salary cost paid to hospi$3.2 $4.0 Tax Equity and September 3, 1982 Fiscal Responsibility Act tals from 8.5% to a maximum of 5%. Increased Medicare Part B deductible for subscribers from $60 to $75 beginning in 1982. Estimated to have the greatest impact on Medi care costs. Established a target rate reimburse ment system for hospital services which limited the rate of increase in Medicare payments per case for a 3 year period beginning 10/1/82. Re quired employers to offer employees and spouses age 65-69 the same health plans offered to youn ger workers. $23.1 $20.3

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iable 2.5. Continued. Deficit Reduction Act Consolidated Omnibus Budget Reconciliation Act Date Enacted July 18, 1984 April 7, 1.986 Major Provisions Medicare became second payer for older employ ees. Reduced reimbursement for radiologist! seryices provided to inpatients 0 from--1 00% to-,80% reasonable creased limits allowed for Medicare Part B premi ums. Eliminated the salary differential paid to hospitals and skilled nursing facilities. Established a reimbursement fee schedule for $6.1 laboratory services. Froze physician fees for a 15 month period beginning 7/1/84. Required employer-sponsored group health plans to cover employees' spouses (65-69). Medicare would become the secondary payer for spouses. Reduced Medicare reimbursement to hospitals for $2.0 the indirect costs of medical education. The prospective payment rate system increases were limited to 1 %. For 1988 increases limited to increase in the hospital market basket index. Expanded coverage requirement for employer group health plans to over age 69 so Medicare would continue as secondary payer. COBRA added to the program costs by increasing payments for hospitals serving a disproportionate share of lowincome patients. HCFA $4.2 $1.4

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I able 2.5. Continued. Omnibus Reconciliation Act of 1986 *Dollars in Billions Date Enacted Major Provisions October 21, 1986 Extended Medicare Part B coverage of occu pational therapy to include services provided in _skille_d nursing Made Jy1edicare -cthe beneficia ries employed by large companies and who elect to be covered by the employer's health insurance plans. The provisions in this Act were expected to increase program costs. TOTAL SAVINGS HCFA $-1.0 $-1.0 $35.9 billion $28.9 billion Note. From Medicare and Medicaid: Updated effects of recent legislation on program and beneficiary costs (p. 19) U.S. General Accounting Office/HAD 88 85, July 1988, Washington, D.C.

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years 1970 1980 continued through 1986, Medicare hospital costs would ' ,,: :, 'i: have been about $17.3 billion more in constant 1986 dollars than they actually : were" (U.S. Accounting Office, July 1988, p. 22). A decrease in the number of hosRital patient days controlled the growth rate in Medicare hospital I costs. ::: Two legislative changes, the Tax Equity and Fiscal Responsibility Act of iii 1982 and the prospective payment system in the Social Security Amendments of 1983, gave hospitals incentives to reduce the length of Medicare patient stay. The General Accourting Office analysis substantiates the cost savings and, thus, the theory that prospective reimbursement to hospitals would save money in Medicare :: costs. Prospective reimbursement under Medicare was viewed as so effective that the same type of reimbursement for physicians will begin in 1992. I. I : The Impact of the Growing Older Population and 'Medicare Policy Changes on Nursing Home Admissions According to new estimates by the federal agency for health care policy and !r 'i research, 43 percent of all Americans who turn age 65 in 1990 (929,000 persons " nationally) will use a nursing home at least once before they die. Projections indicate that half the women and almost one-third of the men who reach age 65 in 1990 will use nursing homes. Increasing life expectancy will lead to a gradual rise in risk of nursing home use (from approximately 43 percent in 1990 , 'I' ' to 44 percent in 2020). By 2020, there will be 1.7 million Americans aged 65 who eventually will a nursing home (Murtaugh, Kemper & Spillane, 1990). The expected growth in demand for nursing home care has implications for government "' 'I '': 46

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:I 'i policymakers with supply and financing of long term care services. For nearly a decade, public policymakers and analysts have studied the costs of ' nursing home care. In 1983, the General Accounting Office completed a report for the Subcom1 mittee on Health and the Environment for the U.S. House of Representatives. The I ;;I 'I report entitled Medicaid and Nursing Home Care: Cost Increases and the Need for ', Services are Cfeating Problems for the States and The Elderly provided information :i on the characteristics of nursing home residents, reimbursement policies, expendi1 I I, 1: tures and by state. Since the Social Security Amendments of 1983 (Public Law Section 601 ), which created the prospective reimbursement I 111 system for hospitals, was successful in reducing Medicare expenditures, this theoretical review will consider the potential impact the legislation has had on the ,, patients, on federal programs such as Medicaid, and on changes in the 'i:1' hospital discharge planning process. I Public plolicymakers anticipated that the new hospital reimbursement system '' would provide'$ufficient incentives and disincentives to decrease the number of 'I medically hospital stays. In anticipation of other spillover effects in I I the health care1 : system, the General Accounting Office identified a few of the II: potential problems. "The DRG payment method may cause problems for patients if they are by hospitals too quickly to nursing homes which cannot provide the of care they require. Because of the DRG incentives, nursing homes expect that the demand for their services will increase as hospitals seek !1. 47

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I 11i 1',11 ,, placement for convalescent Medicare patients" (U.S. General Accounting Office, ..... 1983, p. 119). : and Kramer (1990) studied the patients' problems to evaluate the effects of Medicare's prospective payment system and concluded that from !: 1982 to 1986 needs of the patients in long-term care increased substantially. ,,, This trend 1attributed to earlier hospital discharge to long-term care systems and Medicaid's;'policy of deinstitutionalization. Given the increased need for patient care, and Kramer called for a better system of reimbursing for long term care and ensuring its quality. l'lt .,, Hospitalized elderly are at high risk for poor post-discharge outcomes t 1, because of deqreased ability to adapt to physical and emotional stress (Johnson & Fethke, 1985; 1990). ... a key.;contributor to the institutionalization of persons aged 75 or more, in combin#tion with age and living in retirement housing, is a hospital admis sion. (This latter factor alone raises their chance of institutionalization within 7 years,:from 40% to 53%). It appears especially important to ensure that such pe'rsons have their medical, physical, and mental functioning problems thoroughly assessed and addressed prior to discharge and that special attentibt:l be paid in planning their discharge so that arrangements are made for follow-up care or support and for regular reassessments of their health and circumstances, if required. (Shapiro & Tate, 1988, p. 243) Although this age cohort usually needs more assistance after discharge for a larger :i period of time the general population, this group is the least likely to have the 'I! support system needed to assist them (Johnson & Fethke, 1985; Naylor, 1990). I, Densen. ( 1991 ) analyzed the percent of elderly hospitalized persons dis,. ,, charged home ,and the percent discharged to a nursing home in Table 2.6. Older adults enter nursing homes more frequently from hospitals than any other source. ':'i. :, I ,,,, 1111:' : 48

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Table 2.6. Percentage of Elderly Hospitalized Persons Discharged Hohle and Percent Discharged to a Nursing Home by Age: 1986*. '!: ' Discharge Destination I : !I Home 'I' Informal Care Home Care::Program Nursing 65 & Over 77.5 70.2 7.3 10.2 65-74 85.7 80.0 5.7 3.9 75 & Over 69.2 60.7 8.5 15.9 *Includes those discharged with and without referrals to a home care program. '' Note. From Tracing the elderly through the health care system: An update (p. 9) by P.M. Densen, 1991, Rockville, Maryland: U.S. Department : of Health and Human Services. ' I About 4 of the hospitalized 65 to 74 age group is discharged to a nursing '. !I home while 16 :percent of the 75 and older hospitalized elderly are discharged to a '' nursing home. :1The discharge location is of concern as is the length of stay in the nursing home. I ii: ,, Pennsylyania hospital data from 1983, 1984 and 1985, the timeframe just after implementation of the Medicare prospective payment system, revealed a 111 decline in Meqi.bare's average length of hospital stay by more than 20 percent between 1983 ,;:md 1985. During the same time, Pennsylvania experienced a 36 ,, :' percent increase in transfers to nursing homes, home health agencies, rehabilita tion centers other hospitals (Hospital Research Foundation, 1986). "In 1985, 19 percent of. tne discharged Medicare patients in Pennsylvania were transferred to I ;;I 49 i' :!:

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i' ::: , ',, ,, a post-hospital,':subacute care setting. Of these, approximately 40 percent went to skilled nursinQ facilities" (Morrisey, Sloan & Valvona, 1988, p. 686). A 1987 Uournal of the American Medical Association report on discharge I data of patientsi hospitalized for falls and hip fractures revealed the magnitude of d the problem predicted by the U.S. General Accounting Office. The extraordinary 'I' growth in the nursing home admissions after the prospective reimbursement payment systerfl (after Medicare DRG's were implemented) is shown in Table 2.7. I ,: Table 2.7. Impact of Prospective Reimbursement. i 1!, :: Pre-Prospective I' Reimbursement Length of Stay 16.3 days I # of Patient Sessions 9.7 Patients 21% to Nursing Homes Patients Still in Nursing Homes 13% After Six Mon1ths Post-Prospective Reimbursement 10.3 days 4.9 48% 39% Note. From Jdurnal or the American Medical Association (pp. 1762-66) by M.A. Sager,E.A. Leventhal & D.V. Easterling, 1987, Chicago, Illinois: American Medical :!'Association. ,: After pr9spective reimbursement, the number of patients discharged to I "' II nursing homes doubled and the number of patients remaining in nursing homes six months after discharge tripled. Since the cost of monthly nursing home care starts at .$?,000 per month and since the average length of nursing home stay I I 11: I! ,, !! ,, 50

PAGE 63

:. i: li is 2 to 5 years ;(u.s. General Accounting Office, 1983), it's relatively easy to under,.,,i stand that patients spend their resources within about 13 weeks (Estes, :' 1990). The payment sources for nursing home care in 1988 are shown in I ,. Table 2.8. ., II 'I ,. Table 2.8. Source of Nursing Home Revenues (Calendar year 1988). I ,, 1, Private Payments 51% I :Medicaid 41.4% ::other 6% ,Medicare 1.6% I ,, Note. From Q1pngressional Research Services, cited in Nursing homes: Admis sion problems for Medicaid recipients and attempts to solve them (p. 11) by U.S. Government Accounting Office, September, 1990, Washington, D.C. I I paid less than two percent of the cost of nursing home care in ,, I 1986. Fifty-one percent of the cost was paid by older patients. After patients i spend their finijncial resources down to about $2,000, the federal and state governments share: financial responsibility to ensure that Medicaid provides nursing I home care to patients who need it but are unable to pay for the care. Medicaid and other sources, except Medicare, paid 41.4 percent of the cost of ., 1 nursing care which translates into 20 percent of the shared cost (of 41.4 percent) by the federal government and 20 percent of the cost covered by , the state. The. increasing older population combined with the 41.4 percent Medic-.. '' ,1! aid payment rate precipitates concern about the growth in nursing home costs. ':,:' :,I 51

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' 1 II: t :: '!1: I Table 2.9 the growth in Colorado's nursing home population to double in I,:: size from 1980 ::to 2000. The 1980 nursing home population of 12,873 will grow to 24,306 by the year 2000. This growth will undoubtedly impact Colorado's Medicaid expenditures.: : !: Two recent studies described the payment source of the nursing home population at admission. :1' Historically, about 40 percent of elderly nursing home residents enter as recipients, about 50 percent as private payers, and the remaining 1 0 under private insurance, Medicare, or other public programs. Some of those who enter a nursing home as private payers, however, subsequently become Medicaid eligible ... about two-thirds of nursing home. residents are receiving Medicaid assistance at any point (U.S. Gener al Accounting Office, 1990, p. 1 0). Another study (Liu, Doty & Menton, 1990) claimed that 11 percent of those entering a nursing as a private payer spent their resources and became eligible for Medicaid during their nursing home stay. : ;! As the. demographics shift toward an increasingly older population, Medicaid expenditures ar.e projected to grow, further straining state and federal Medicaid budgets. Meditaid was initially intended as an acute-care program for the poor, I however, Medi9aid has become the principal public program financing long-term ,, I nursing home,qare for the elderly and disabled. Although not foreseen when II: !!, Medicaid was enacted in 1965, spending for nursing home care is one of the ,. largest components of Medicaid spending. Approximately $14.3 billion of the total $48.7 billion i11 federal and state Medicaid spending went for nursing home care in i, fiscal year 1988 (U.S. General Accounting Office, 1990, p. 11 ). In 1988, nursing home care 30 percent of the federal and state Medicaid costs. ',Ill ,. !: ,, :i, 52

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'' I': i 'i! ', Table 2.9. Number of Nursing Home Residents in Colorado and Percent Change by Age and Sex, 1980-2000. !l i, ,. Number:.o,f Nursing Home Residents Percent Change Total d 1980 1990 2000 1980-1990 1990-2000 1980-2000 Age 65 & 12,873 17,946 24,306 39.40 35.44 88.81 65-74 ,:,, 2,359 3,026 3,385 28.24 11.88 43.48 75-84' :: 5,095 6,986 9,068 37.11 29.8 77.96 85 & Over 5,419 7,934 11,854 46.42 49.40 118.75 I ,, Males ., 1980 1990 2000 1980-1990 1990-2000 1980-2000 Age 65 & over 3,355 4,276 5,449 27.48 27.42 62.44 65-74 1: 1,022 1,313 1,489 28.51 13.40 45.73 75-84 I 1,211 1,627 2,116 34.3 30.11 74.73 85 & Over '1, 1,121 1,336 1,843 19.18 37.93 64.38 ;. ,,: , : ,, Females : 1980 1990 2000 1980-1990 1990-2000 1980-2000 'I Age 65 & Over 9,519 13,669 18,857 43.60 37.95 98.11 65-74 1,337 1,712 1,896 28.04 10.71 41.76 7584.:.: 3,884 5,359 6,951 37.98 29.70 78.97 85 & Over '! 4,297 6,598 0,010 53.53 51.72 132.94 Note. From :C()Iorado Health Care Association, 1989, Denver, Colorado, unpub lished data. II 'I' A report in the Journal of the American Medical Association confirmed that by the time current baby boomers reach retirement age, their aggregate health care costs could exceed the nation's current annual deficit. "Approximately';40% of current nursing home costs are reimbursed by the govern ment through Medicaid. If this program continues and the number of nursing home L :: I I ,: 53

PAGE 66

',, ', 'li residents to almost 6 million, the cost to the government could be as high as "' $56 billion (ir'i 985 dollars)" (Schneider & Guralnik, 1990, p. 2338). In a related article, Carroll !Estes described the impoverishing effect of our current federal policies: We are: impoverishing people by all the bad decisions that make Medicaid our foremost program for long term care, and then primarily in institutions. It should have been a national thunderclap when CongreSsional researchers announced a few years ago that most older who must privately pay out of pocket for nursing home services spend down their resources so rapidly that they become eligible; for Medicaid coverage within approximately 13 weeks of admi5s.ion to a nursing home. (Estes, 1990; pp. 4-5) Medicare expenditures for hospitalization have been controlled by prospec:. tive reimburs,e!Jlent policies, however, the nursing home admissions are increasing, ,, I patients are. staying longer, and the longer these patients remain in a nursing I' home, the more likely they will require Medicaid coverage. Medicaid expenditures 'r '1: have been increasing substantially. Since Medicaid is a federal/state cost-shared program, the costs may decrease by moving patients from Medicare to Medicaid but then the state costs increase. In Colorado alone, the 1988 to 1989 ,. Medicaid budget was over-expended by $100 million. In 1978, Colorado devoted 60.5 percent its total Medicaid expenditures on nursing home care (Health Care Financing Adn;Jinistration, 1979, Table E). "Medicaid expenditures for nursing home ': care are alrea9y of major concern to the States and the Federal Government because they have increased at a high rate in the past. Virtually, all the States 'I have problems financing this program" (U.S. General Accounting Office, 1983, p. ii). : I II,. il: i: : i ,. 54

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: i! 1: 'I I i I' phenomenon in the Medicare program may increase patient spend,' :1 down and forcs premature utilization of the Medicaid program. As the deductibles and subscrib;erjifees for Medicare increase, and as more older people pay for services not co,vered by Medicare, there will be an increasing number of older I ,, ,, people needinQ the Medicaid program. More middle-class older persons will "spend-down" and become medically indigent (Feldstein, 1988). The literature clearly ties of the older population to the increasing Medicare costs and Medicaid costs as a result of nursing home placement. ,' Table 2.10 reflects the growth in Colorado's Medicaid expenditures from 1981 to '' 1990. In 1990 'the aged recipients represented 14 percent of the total Medicaid I 111 recipients in Colorado and the cost of nursing home care represented 26 percent of the state's total: Medicaid expenditures. States with budget shortfalls are examining their ever growing '!: Medicaid budgets. "New Jersey is projecting an $87 ,million deficit for its $2.1 iii billion Medicaiq program by the end of the year ... [due to] rising Medicaid costs on higher inpatient hospital and nursing home care costs" (Older American Report, 1991, p. 19). ,' Carolina faced a $60 million Medicaid shortfall by June, 1991. ,, States to seek opportunities for decreasing the spiraling Medicaid costs 'li for institutional: care. ,Summary of Research Findings Regarding the Impact of Medicare Changes on Hospital Discharge ,j A large :'portion of national health care costs is accrued by older adults in 'I I hospitals and homes. Prospective reimbursement slowed the rate of Medicare but the costs in Medicaid escalated as a result of increasing 55

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: ',il I ,II I ;i Table 2.1 0. Colorado's Medicaid Expenditures for Aged Hospitalization and Home Care: 1981-1990. ,. ;, I AGED AGED T011At. AGED TOTAL HOSPITAL NURSING HOME YEAR RECIPIENTS RECIPIENTS EXPENDITURES EXPENDITURES EXPENDITURES 1981 145,514 31,263 $215,712,006 $5,222,396 $67,788,936 1982 143,656 30,954 244,562,711 6,513,189 72,195,642 "' 1983 147,644 31,408 255,303,361 6,015,322 77,001,278 1984 31,960 290,171 ,047 6,292,278 82,082,354 i' c'l 1985 147,30$ 31,715 315,797,062 5,091,656 86,424,686 1986 149,030 33,209 300,313,127 695,127 89,940,836 1987 165,333 35,415 372,182,233 7,583,349 99,167,998 ,. 1988 211 ,38? 32,406 464,311,557 3,677,854 119,690,780 1---218,0,67 1989 32,497 451 ,909,848 2,509,278 119,048,253 ,,,, 1990 239,878 33,544 I $515,696,297 $2,282,610 $132,613,837 Note. Department of Social Services, Medicaid Division, unpublished file data, February, 1991. I '.::' : I nursing home and extended lengths of stay. Older adults are entering nursing more frequently from hospitals than any other source. After DRG's :: were utilized for reimbursement, more older adults were discharged from hospitals : to nursing hon],es, with longer lengths of stay in the nursing home. Approximately 40 percent of nursing home costs are covered by Medicaid; an increase in admis sions leads to 11spending down resources and an increased need for Medicaid coverage. Gplorado's Medicaid expenditures for elderly nursing home residents : ii increased trorri1 $67 million in 1981 to $132 million in 1990. Most states are having ''!' ,: I '1: ,, I ',::! 56

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' "' I ill: I : difficulty payillQ: their share of the growing Medicaid budgets. In 1988 and 1989 ,1: ,,1, ,I and again in 1 Colorado's Medicaid budget was over expended by $100 million. :i! il I The projected growth in the number of nursing home residents in Colorado increases about future Medicaid expenditures. From 1990 to 2000, the I. I number of Colorado's nursing home residents age 75 to 84 is expected to increase by 29.8 percent and the 85 and older population is expected to increase by 49 percent. New interventions are needed which will ensure that Medicare patients 1: ,I receive the appropriate level of care and prevent premature institutionalization. Characteristics as a Predictor of Posthospital Care ,, Over past twenty years researchers have attempted to assess the factors which cause institutionalization. A number of variables are associated with : ,, institutionalization. Advanced age has been cited as a factor (Brock and O'Sulliv-1 "!I an, 1985; Tell, & Wallack, 1986; Greenberg & Ginn, 1979; Shapiro. & Tate, 1985). Certain, diagnostic conditions, particularly those with a diagnosis including ,. ::: mental illness, are more frequently nursing home residents (Shapiro & Tate, 1985; ., Weissert & Gready, 1989). Gender, race, nursing home bed supply, and climate I :, are also associated with institutionalization (Unger & Weissert, 1988). Shapiro and Tate (1988) nine significant factors for the prediction of long-term institutionalization: .age, living in retirement housing, recent hospital admission, spouse at "I home, fair or poor self-rated health, female, problem remembering names, more than one with activities of daily living, and steadiness in state of mind .. :I Lack of availability of informal support, living alone or having limited contact with I' li ' I. I .,; 57

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relatives has associated with institutionalization (Brock & O'Sullivan, 1985; : .!i: Greenberg & :Ginn, 1979; Shapiro & Tate, 1985; Weissert & Cready, 1989). Weissert & Cready (1989) found strong associations of the following variables with institutional age, marital status, poverty, dependency level, and certain : I i diagnoses (mental disorder, cancer, anemia, kidney trouble, digestive disease, nervous system, disease, diabetes, and circulatory disease). The inability to do '" I II basic tasks such as bathing, feeding, toileting, was researched and I cited as a predictor of nursing home placement by Cohen, Tell, and Wallack (1986), and Ginn (1979), Shapiro and Tate (1985). After prospective I I :i reimbursement:was initiated, new variables were identified. Meiners and Coffey (1985) identified four DRG's most commonly referred from the hospital to nursing homes. The D,RG's included strokes, heart failure and shock, major joint proce,' i dures and hip and femur procedures, and pneumonia. Morrisey et al. (1988) analyzed the early effects of the Medicare prospective :1 payment systerh on the likelihood of hospitals discharging Medicare patients to 1: nursing ,or home health care. Their analysis reflected the probability of hospital transfer increasing for all DRG's and posthospital destinations. However, patients with penumonia, and major joint and hip procedure were more likely to be transferred to skilled nursing facilities. Morrisey et al. viewed the I probability of and the probability of length of stay prior to transfer as a ' I function of "the:'introduction of the prospective payment system as well as the I health status. aod demographic characteristics of the patient; the destination of I II: II' transfer, i.e., sk.illed nursing facility, intermediate care facility, or home health ,.1 "I Ill 'I .. ., ,I ,ir ,.,, 58

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"[ > I : : ; I : I 'i ,, !i I II ,, agency; the characteristics of the hospital, and the characteristics of the communi :i ty" (Morrisey al. 1988). Their research found significant differences in length of ,, stay and transfers by gender, race, age (75 and older}, the presence of a second ary diagnosis,' ,,bY characteristics of the hospital and characteristics of the communi-i ty. Hospital included ownership, teaching role, and the size of the institution. Community factors related to the availability of subacute care or other hospitals. research arid others did not find a consistent pattern between 1: severity of illness and either transfer probability or hospital length of stay (Morrisey ,' et al. 1988).: patient diagnosis does not appear to be a good predictor of resource I '1: use in nursing :homes (Cotterill, 1986). ,' There, is no clear evidence that financial status or poverty level is strongly associated wito institutionalization. Numerous studies found no association. Two 1, studies found, a positive association between individuals receiving Medicaid or public and institutionalization. Greenberg and Ginn (1979) found that I 1 recently institutionalized older adults in Minnesota were more likely to have higher I ,, incomes (Conan, Tell, & Wallack, 1986; McCoy & Edwards, 1981). (1985) claimed that although older age increases the risk of nursing home placement, the probability of an institutionalization remains low ', unless age by dependency, high-risk diagnosis, and the absence ,, or loss of a spbuse. Two other studies (Greenberg & Ginn, 1979; Shapiro & Tate, ; II 1985) found to be more at risk of institutionalization than males. Another study (Leibson, Naessens, Krishan, Campion & Ballard, 1990) demonstrated that ' : ; significant in mortality and nursing home transfers occurred after the I I II ,,: :: 59

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,,i ::1 :: II introduction of t,he Medicare prospective payment system, largely due to patient ,, age, gender, di,sease severity and complexity. I! evidence exists from other research to more closely examine the nature and pre9ictors of nursing home placements. If variables such as age, II! ,, gender, or marital status are predictors of institutionalization, the creation of multivariate mQdels could estimate older patients' risk of institutionalization. Limited ' !. resources, targeted to these high risk populations, would serve as a cost-effective approach to premature institutionalization. I' Patient Satisfaction with Discharge Planning Since Medicare prospective payment system (DRG's) was introduced, I researchers have reported on the discharge of "sicker" patients, decreasing hospital stays, :,increasing hospital readmissions, increasing outpatient visits, ,' premature and increasing admissions to nursing homes (Coe, Wilkinson, & Patterson, 1g86; Congdon, 1989; Fitzgerald, Moore, & Dittus, 1988; McGovern & I Newborn, 198S). Frequently, however, tha financial implications of the prospective li payment systeijh have overshadowed the vulnerability of the older patients who are ,, discharged. Data on older patients' experience and satisfaction with the discharge planning process is nearly nonexistent. In order to improve the discharge process ,, :I and improve patient outcomes, the perspective of elderly patients is critical :' (Congdon, 1989). This research includes follow up questions at two week and ,, ', eight week inte.rvals after discharge to assess patient satisfaction with discharge planning. ,, 60

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'i I The Impact of Medicare Policy Changes on Hospital Discharge Planning : :i Health 'eare Financing Administration data cited in the previous section I ,, substantiates cost savings of the prospective reimbursement system through fewer hospital days. One of the spillover effects of prospective reim-. '!! bursement was an increase in nursing home admissions. The prospective reimbursement system has also impacted the hospital dischatge planning process. Discharge planning and finding appropriate 1: post-hospital care will be discussed in this section. Recogni.zing that Medicare patients were discharged from hospitals "quicker I II. and sicker," Congress developed the patients' rights to discharge planning. The I' purpose of rights was to ensure that patients received a smooth and timely ! transition to the most appropriate post-hospital care. Also, patients could request a i' review of any proposed termination of Medicare-covered hospitalization. On October 22, 1987, the federal discharge planning legislation (U.S.PL 99::i: : : 509, 1986) into effect; hospitals participating in the Medicare program were I required to provide discharge planning. Medicare in-patients must be given a notice explaining that they have a right to a discharge plan and to discharge I I planning servicks. ' The federal statute 42 U.S.C. 1395 X (ee}, provides for the follow-lng. t : : :i: I' (1) hospital must identify at an early stage those patients who in the absence of adequate discharge planning are likely to suffer adverse health consequences on discharge; II: (2) :ihe hospital must provide a discharge planning evaluation on a timely basis for patients identified under subparagraph (1) and for other patients on request; ' 'i 61

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i ::1: II] (3) :the discharge planning evaluation must include an assessment of a ;. likely need for appropriate post-hospital services and of the of those services; I (4) on the request of a patient's physician, the hospital must arrange for the development and initial implementation of a discharge plan for .the patient; and I IIi I I i' (5) both the evaluation and the plan must be developed by or under the supervision of a registered professional nurse, social worker or other iilPPropriately qualified personnel. (Paulson, 1990, p. 5) These discharge planning requirements are an important step toward I :' identifying and ;planning for the assistance which Medicare patients will need after hospital Patients who are leaving the hospital "quicker and sicker" 'I ,llj require more support at discharge to facilitate recuperation and simultaneously : ' prevent readmission to the hospital. Hospita) discharge planning has received increased attention since imple-:: mentation of reimbursement. First, patients waiting in hospitals for appropriate ppst-hospital care have become a greater focus of attention since fees ,. '" '''I! are fixed by rather than number of days at the hospital (U.S. General Accounting OffiCe, 1987}. Second, new requirements for Quality Assurance encourage hospitals to provide effective and timely discharge planning as a il I, service. faced with a growing elderly patient census and the realities of the DRG prospective reimbursement system, must select appropriate services and housing for patients upon discharge while the timeframe from physician II li notification of discharge to actual discharge ranges from a few hours to a few days. At hospital discharge planners recommend services in nursing ::! ,, homes, in othet housing arrangements, or at home. In order to prevent the most I, li I ::1 62

PAGE 75

costly, most care referrals to nursing homes, some form of intervention is 'I :;i necessary which will: 1) provide the assistance needed by the patients to stabilize I their medical condition; and, 2) prevent readmissions to the hospital. In 1986, the U.S. House of, :Representatives Select Committee on Aging requested a study by ',II: ' the U.S. General Accounting Office (GAO). The survey of a nationally representa, tive sample of hospital discharge planners obtained information on their experiencI I : : es regarding access by Medicare patients to post-hospital care (U.S. General Accounting Offi'ce, January, 1987). The survey assessed the role of the new ,, prospective payment system (DRG's) and other factors in arranging access to care r' li: after hospital dj'scharge for the elderly. This GAO study was the first national study to examine problems facing Medicare patients whose need for post-hospital care had been determined by hospital professionals. Most of the hospital discharge .I ,I planners responding to the survey faced a number of important problems in gaining access to appropriate post-hospital care. This national survey of 866 hospitals , I J: il: included 111 hospitals in the mountain region. Table 2.11 presents the characteris' tics of the mountain region hospitals participating in the GAO study. The study reflected a number of potential trends or events that could ,I: affect access t9 post-hospital care. The introduction of the Medicare prospective payment system was seen as contributing greatly to the access difficulties. Other 'II: factors affecting access to post-hospital care were the increasing numbers of I Medicare patients, increased use of complex medical equipment and other "high.. tech" services in post-hospital care, state certificate-of-need regulation of nursing I ': 'I I' home beds, and changes in the number of certified skilled nursing facility beds. I I I 63

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' "j ; ',: i: ,, Table 2.11. Characteristics of the 111 Mountain Region Hospitals Responding to GAO Survey on Posthospital Care. ,,,i '";11 :,Bedsize Ran,ge Percentage <1,00 38.7% 100-299 34.2% I, 300+' 27% ,, Control Types Percentage Nonfederal government 23.4% Private not-for-profit 67.6% For-profit 9.0% Note. ; From Post hospital care: Discharge planners report increasing difficulty in placing Medicare patients (p. 24) U.S. General Accounting Office, January 1987, Washington, D.C of the Medicare prospective payment system was consistently : ql singled out by discharge planners as a major factor making placement of Medicare patients after hospitalization more difficult. While growth in the number of home health, was regarded as facilitating post-hospital placements, discharge planners in each region of the U.S. cited Medicare program rules and I regulations as, most important barrier to home health placement. ',, "i , II, The disharge planners were asked the post-hospital destination of their Medicare patients after receiving discharge planning. "Nationally, discharge planners that only about 37 percent of a hospital's discharges were I discharged to their homes without further care" (U.S. General Accounting Office, 1987, p. 30). Table 2.12 summarizes the destinations at discharge from the ,,',: hospitalf in region of the country (including Colorado). Fifteen ,, I' percent of the Medicare discharges were either to skilled nursing facilities or intermediate :care facilities. ' ,, : I :'I 64

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Table 2.12. Po:sthospital Destination of Medicare Discharges in the Mountain Region . Wrthout 'I Wrth Home Skilled lntennediate Group Living Rehab ,. Further Care ., Health Care Nursing Care Centers 50% : i I. 18% 10% 5% 0% 1% !: Note. From Post hospital care: Discharge planners report increasing difficulty in placing Medicare patients (p. 30) U.S. General Accounting Office, January 1987, Washington, D.C j, I ... I ,, In to impact the number of discharges to skilled and intermediate care facilities, its to know the perceived barriers to placing Medicare patients in home care:o:r adult congregate living facilities. Nationally, the two most important barriers to :arranging home health care for Medicare beneficiaries cited by hospital discharge planners were: (1) Medicare program rules and regulations, and I, ::j :' ,I (2) lack of availability of noninstitutional posthospital care services. Table 2.13 I' reflects the perceptions of hospital discharge planners from the mountain region of ' the United regarding barriers to placing Medicare patient in home health care. The of post-hospital serVices to which the discharge planners referred : ii: their patients included: chore service, homemaker service, extended observation, !' I custodial care (Hld chronic care. Over 17 percent of the planners raised problems regarding the of available home care services for their patients. In the I' mountain region, discharge planners described the availability of home health care as adequate, availability of homemaker services as marginal, and the availabili ty of adult corig:regate living facilities as inadequate (U.S. General Accounting Office, 1987). These barriers at discharge increase the number of nursing home I :i1 I 111 65

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i ;:: ol 'II 'd I; Table 2.13. Most Important Barrier in the Mountain Region :to Placing Medicare Patients in Home Health Care 1 . ; :'I! :I Number of Pr9gram Rules and Supply of Social or Legal Need for Chronic Care Hospitals ;' Regulations Home Situation Complex Problems Responding Health Care Skilled Care Medicare Medicaid .: ,. I ,, 111 61% 0 17% 5% 4% 5% 1 As reported qy the hospital discharge planners. Other Facilities 8% Note. ':From Post hospital care: Discharge planners report increasing -, ''difficulty placing Medicare patients (p. 12} U.S. General Accounting :office, January 1987, Washington, D.C. ;i' referrals. housing options such as adult congregate housing or home care services less costly than nursing home care if the patient does not require 24 hour per supervision. Although costs of home health care vary depending 1: upon the training of the individual caregiver, a few hours of home health care could easily exceed the Medicaid cost of nursing home care ($32 per day in .,. Colorado). must be carefully packaged to protect the patient during , recuperation their hospital stay while ensuring reasonable costs and service dependability. I,::: Other services which the hospital discharge planners cited as needed but available in sufficient quantities are: meals on wheels, home visitors, adult day care, transportation, board and care homes or alternative living :l1 arrangements.: If the services are available, frequently there are waiting lists, preventing access to services ... The aspects of this research demonstrated the pressure on I discharge the limited time available, and the need to quickly obtain 66

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l1" : : I available seryices for which the patient is eligible. Naylor (1990) and other experts have rated of discharge planning for the elderly as very poor (Fink, Siu, I' Brook, Park, &1:solomon, 1987). Historically, discharge planning has not been considered alpriority in the health care system and, therefore, suffers from delayed li' : "' assessments, documentation, and fragmented implementation (Naylor, 1990; ,, U.S. of Health and Human Services, 1988). Recent research on hospitalized elderly concluded that only 20 percent received discharge planning ! i from the socia(service department despite the fact that 85 percent of the patients were defined as high-risk patients in need of discharge planning (Johnson & I I Fethke, 1985; 1990). In order to impact the discharges of older patients, improved documentation and consistency in discharge planning services is essential. II: ',:' aspect of discharge planning is the follow-up care after discharge. Two important findings were cited in the U.S. General Accounting Office study on posthospital care. Hospital discharge planners were asked about the frequency of ' their contact type of posthospital contact with Medicare patients. Table 2.14 reveals that on.!y 17 percent of the Medicare patients discharged in the mountain II; region are corliacted after discharge by the hospital most of the time or almost always. When :,al?ked about the type or method of posthospital contact with Medicare i, II. patients, hospiial discharge planners in the mountain region, who were making follow-up contact, reported patient visits (19%), telephone contacts (60%), and '"' (68%) contactsi:with providers (U.S. General Accounting Office, 1987). 1: 67

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, II : ilj I, Table 2.14. of Posthospital Contact with Medicare Patients by .Discharge Planners in the Mountain Region. ,, IIi II Number of: Seldom Sometimes About Half Most of Almost Hospitals j: If Ever The Time The Time Always : 111 I, 11!, 13% 54% 15% 13% 4% 'I Note. From Post hospital care: Discharge planners report increasing difficulty in placing Medicare patients (p. 26) U.S. General Account i.ng Office, January 1987, Washington, D.C. I II .. I I .II As the population of frail older adults increases, the demand for housing options and services will also increase. The financial ramifications of ., utilizing nursir:1g homes instead of less restrictive, less costly services were de-l ,1' ,, scribed in the previous section. Discharge planning at the hospital becomes a ,, "I critical decisiori point for preventing premature nursing home institutionalization. :; The Impact of the Increasing Older Population on : Future Medicare Policies and Community Services A numb:er of recent books and articles deal with the increasing older population and, its impact on public policy. Medicare payments for personal health care rose by. pver 15 percent annually between 1970 and 1985 (Waldo, Levit & II Lazenby, 1986j, while the number of enrollees was growing by only about 2 :: percent per (Health Care Financing Administration, 1984). Policy analysts and researchers Stephen Zuckerman have called for new theories, research and policies which ,:!create incentives to control both quantities and development of the nation's for long term care." One intervention option was proposed by 'I i Vladeck (1980). who the U.S. to move its policies toward increased utilization of cohgregate care housing and avoid new nursing home construction. 68

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' "I I 'd In particular, he;! utilizing a portion of the excess hospital beds (at less ., reimbursement) for individuals who are not appropriate for nursing home placement. ':' I ,Ill I' 1: li !i Lawton a,nd Hoover (1981) have contributed work on housing policy II: II' analysis which sbows the close ties between housing and long-term care policies. First the older ,population is diverse and requires a wide variety of health, housing !:I and long term care policy approaches. Secondly, present long term care policies are escalating posts and are not meeting the needs of vulnerable elderly (White, Ill I, 1984). Third, ir:1creasing numbers of frail older adults makes public policies for the most frail, poor or at risk of institutionalization critical in the next decade. 1 I: II 'I, The population is increasing and the service delivery system is in transition. Constant changes (i.e., a continuing expansion of alternatives) are I 'I. ., I occurring in the housing continuum and in-home services precipitating a challenge to maintain accurate resource files. Without accurate data about options, '. !, ., hospital discharge planners refer clients to more expensive nursing home care. The domain of :eJ:der housing which ranges from independent living at home i' through a variety of supported environments to nursing home care, has become sophisticated, various levels of service in order to meet older persons' I' needs. A description of the long term care housing continuum is contained in Appendix F. Differences, both minor and major, exist between facilities throughout I the metropolitan 1Denver area--a statement that surely can be made of any other location in the u::s. Detailed knowledge about these differences is essential if '1: referral patterns from hospitals are to be changed. ,,, 69

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ld '"I ',:1] I, II ,. I' Housing of Very Old Patients after Hospital Discharge Due the aging of the hospital patient population, hospital staff must guide 'I! ,, an increasincily frail elderly population into appropriate supportive services and housing following hospitalization. These patients require particular care in the : "I 1 111 ',, discharge process because their frailty places them at risk for medical :I complications, and places their caregivers at risk for excessive burden. Additional '' pressure is placed on discharge planners by the prospective payment system !li (DRG's), which has shortened hospital stays for Medicare patients (Guterman & I, Dobson, 198Ei). Therefore, discharge planners must act quickly and efficiently in developing I comprehensive discharge plans which will ensure the safety of frail I' I, patients whe,n they leave the hospital (Coulton, 1988). Th$' fpcus of this research is but one major discharge decision for frail I 'II ''! elderly: housiing placement. Housing options range from independent living at home with no care through a full continuum of housing options to the most depen'll dent housihg' option which is nursing home care. Figure 2.3 shows the long term I: care housind continuum which ranges from the least dependent housing option (living at home with no services) to the most dependent housing option (nursing home care). Figure 2.3 .. 'Long Term Care Housing Continuum. ' 11. I; I Least Dependent ,. Most Dependent Own Home Own Home Independent Congregate Assisted No Services <-1 ...!..> With Services <-> Uving <-> Senior Housing <--> Uving <-> Nursing Home 'II! I i ., 70

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'' : ::1 '''II 1: 1[ 'I 'I' Appendix 'F provides a detailed description of each component in the ,,, i housing continuu'm and services offered under each housing type. 'I : II Changes 'in functional health represent a major reason why older persons move to more supportive housing, but elderly tend not to prepare for health-:' :1 induced housing prior to a health crisis (Kulys, 1984). Thus, hospitaliza-,. tion often serves ias juncture point for health care professionals to examine more closely older functional health, which in turn stimulates re-evaluation of 1: I' housing An older person may be hospitalized because of a slow decline of health which culminates in a health crisis, an acute exacerbation of a chronic illness, ot a new illness. In any of these circumstances, the hospitalization can reflect the ne,ed for housing to be reevaluated. While observing older persons in hospitals, professionals may recognize that the patient needs more support than '' I :' :!; is available in pre-admission housing. Of course, hospital staff may also note cases in which olper persons received unneeded support in their pre-admission .: housing. Systetn:atic assessments of patients as part of the discharge process have not been no,rmative (Victor & Vetter, 1988) but are effective means of I' identifying the needed upon discharge (Williams, Hill, Fairbanks, & Knox, 1973). ,' ,', 'I I i Discharge planners have the task of arranging professional support services to follow the patient for a period after a hospitalization. At times, however, support I, 1!, ive services in an:. independent housing environment are insufficient to provide the environmental prosthesis needed to maintain the patient at his or her highest level of functioning. :ln;!,such cases, the patient may be discharged to a new type of 'I housing, likely one offering additional support. I 71

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Hospital discharge planning is conducted by a wide variety of professionals 'I who have limited awareness of the specific housing options available in the ,. community, differences among them in financial and supportive service charac,. I teristics, or ttie availability of units (beds) within them at a given moment in time. in most hospitals, specific information about housing options is not readily available in an easily accessible format. In contrast to home health servic es, which generally arranged by an agency which offers the full array of : : ; relevant servi,ces, there is no centralized housing referral and placement service in most cities which can maintain detailed or even up-to-date vacancy information on ' all housing units in the region. Given the time pressure to plan the discharge, accessible c,omprehensive housing information can be a key factor in providing appropriate. rfferrals for patients at discharge. 'I complicating the housing referral component of the discharge , process is the fact that most discharge planners are unable to follow patients once I they leave the hospital to determine the appropriateness of the housing placement in the ensuing weeks of rehabilitation (Coulton, 1988). Elderly patients may then fear that in a highly supportive environment (such as a nursing home) ''I I may regardless of their potential to live in more independent ,, i housing after:. a few days or weeks of recovery. Hospital staff, on the other hand, ;, ' fear placing patients in an environment with insufficient support where they may relapse, with.:additional suffering as a result. Patients who have no family mem" bers to prov,de post-hospital care have a greater need for alternative housing I Ill which offers assistance. Hospital staff also fear the financial consequences of re! ,, 1: hospitalizatiop of patients during the DRG payment-exempt period following :' 72

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, I ',. ! .I discharge in the hospital will receive no Medicare reimbursement for read-: I' mission. Thus; .patients can be pressuring discharge planners toward independent 'ii ' placements their own homes) while medical professionals are encourag ing placements in more supportive (and restrictive) environments. '. 111 Recent which show a rapidly increasing rate of nursing home : admissions have' been interpreted to suggest that time pressure from DRG's is forcing hospitals,;,to discharge more frail elderly to nursing homes. This pattern is of :: :j: particular concerh because of the tendency for nursing home placements to , ., become permanent (Fitzgerald, Moore, & Dittus, 1988). Recent'ly;\:two new federal approaches were proposed to encourage I I hospitals to pay more attention to the importance of the discharge planning role. In 1988, new peer ieview organization guidelines were initiated to target review of II !l: Medicare patients readmitted to acute care hospitals within 30 days. The screens ., enable peer organizations to monitor subsequent care charts from skilled nursing health agencies, and doctors' offices, and to consider 1: recommending a reimbursement penalty on hospitals or physicians responsible for premature "The purposes of the new screen ... are adding quality ' : : assurance to physician review of hospital Medicare bills and providing incentives ,: for hospitals to pi:1y more attention to post-discharge care" (Weiner, 1990, p. 4). :. I, Federal :R,olicymakers are taking a look at the broader role which hospitals I. !: play. A 1990 budget proposal, developed by the Office of Management and Budget, would. consolidated Medicare hospital reimbursement and post hospital skilled care or home health care reimbursement under a single I DRG payment. "'under about 50 DRG categories, hospitals would have been 'li: 'I' 73

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' I I :' .. responsible :tpr direct provision or subcontracting of post-hospital care, in return for a small fixed,!:percentage DRG rate increase" (Weiner, 1990, p. 4). U.S. Secretary of Health and Human Services, Dr. Louis Sullivan, opposed the proposal but the "I proposal represented a financial incentive for hospitals to improve their hospital ,: .,, discharge planning role and prevent premature discharges that increase nursing home stays: ,li Clearly, an examination of nursing home placements from hospitals is I, t needed. patient characteristics tend to predict nursing home placement at ,: rl, hospital discharge? This research will collect data on causal factors. In summary, hospitalizations stimulate housing crises, as well as health I crises for many elderly who will need significant personal and health care assis tance following the hospitalization. Furthermore, the supportive housing needs of some elderly first come to the attention of health care professionals during a I hospitalizatiorl'. It is increasingly evident that hospital professionals are in a i, position to needs for supportive services for the elderly, and that the discharge process is mandated to implement services and housing changes to .: ): meet those m::eds. At this point, however, little is known about how much housing '', ,:, change occurs as a function of the discharge process, which populations are most likely to new housing placements, and how adequately prepared discharge planners are f9r this task. The describes the demographic characteristics of the age 75 and r( older at hospital discharge, identifies the extent to which hospitalization ,, I II' 74 1li

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' ,,! provokes changes, determines the nature and predictors of those place-1 :' ments, the permanence of the placements, and surveys hospital discharge plan ners regarding capacity to refer patients to housing placement at discharge. I Ill This research also determines the extent to which the intervention of a case I 11: manager can or delay nursing home placement at hospital discharge. The " following section 'reviews the literature which led to proposing case management as ., an appropriate for this research. : '!!' Rationale for Case Management Intervention I ,, At the of discharge, older people are vulnerable because they are limited to their resources and the services obtained by the hospital discharge planners. Older persons over age 75 who live alone and have sufficient health problems to be hospitalized will most likely need post-hospital care from their family ,1] and community resources. Family involvement must be encouraged. "Practitioners ,, also have a obligation to be knowledgeable about community resources ::: and to refer at-ri$k elderly people to resource personnel who may be in a better 'i position to assess ,the home and family needs than professionals primarily working .. i in their offices" (Shapiro & Tate, 1988, p. 244). ; ,j' Although any number of interventions could be tested to prevent premature institutionalization:fo nursing homes, a case management approach initiated at '' :: discharge would hi(J.ve the greatest opportunity for success. The ability to predict post-hospital will provide a foundation for developing the new policy 1, i options, which are required to build on family support systems to ensure appropri ate referrals and cost containment at discharge. Further, a case management ,',1: "", 75

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intervention has been proposed in the literature as a viable option to prevent premature in,stitutionalization. Case management is also referred to as service coordination, care coordi nation or service management. According to Evashwick and Weiss ( 1987) the basic steps of case management include "client identification, assessment, care planning, service arrangement, monitoring and follow-up ... The role of the case manager is to. facilitate access by clients to the various services constituting the continuum." In a description of the future trends in health care, Coile described the health care c,antinuum as the "factory of the future." All efforts will be made to speed up the through-put on a case management approach, reducing inpatient length of stay and increasing efficient use of all resources in the continuum of care (Coile, 1987). Case management services have been developed in most states since 1981, however, these services were initially established to divert existing nursing home patients to other environments rather than prevent nursing home admissions. For the most part, case management services are not available at hospital discharge. The high costs of health care and the growth in the older population has precipitated a number of publications regarding patterns of medical utilization and suggested interventions. A U.S. Department of Health and Human Services research project titled "Consistently High and Low Elderly Users of Medical Care" was conducted in Portland (U.S. Department of Health and Human Services, 1988). Evidence suggested that "mental health and other supportive services, particularly for older populations with specific physical problems, can result in more appropriate use of the medical care system and possibly decrease overall utilization and costs" 76 .....

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(U.S. Department' of Health and Human Services, 1988, p. 8). The report went on to state that high users of medical care "may be at greater risk for admission to nursing and might therefore benefit from interventions such as case management" (U.S. Department of Health and Human Services, 1988, p. 9). In a recent article, Estes called for a publicly financed long-term care system and described case management services as an integral component in the future long term care system (Estes, 1990). The fragmented complex service delivery system creates a demand for institutional care. According to Feldstein, the economic market response to the i high cost of searching for services and the uncertainty about available services has been case management. The case manager improves efficiency on the demand side by helping people and their families understand what services can be purchased to deal with a disability, how services can substi tute for o'r complement other services, where or how services can be found, to combine formal services with informal care, and how better to use informal care. To the extent that the case manager is familiar with the probable course of the disability, future consumption of services can be predicted. The net result of case management is that noninstitutional care for an older person can become, and be perceived as being, more feasible than was previously the case. Unfortunately, case management is not yet widely available, and where it does exist, most people do not know of its availability. :c:ase management as a market response to high search costs will develop more rapidly in coming years. (Feldstein, 1988, p. 567) The Omnibus Reconciliation Act of 1981 removed a provision which Medicaid recipients previously had for "free choice" of a provider. As a trade-off to save federal matching dollars the Reagan Administration gave the states greater flexibility to manage their Medicaid programs (Feldstein, 1988). States initiated new systems, such :as case management, for delivering services to Medicaid 77

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clients. More than 24 states currently use some form of case management system .' \ for their Medicaid population (George Washington University, 1985). Richard Ladd, Oregon's State Long Term Care Director, frequently com pares Colorad,o and Oregon (Kane, Wong, & King, 1990). Both states are compa rable demographically and geographically. About 10 years ago both states had a Medicaid nursing home population of about 8,500 people. Colorado had about 2,500 Medicai.d recipients in home. care programs; Oregon had a Medicaid home care population of about 4,000. (See Table 2.15.) Oregon made a number of changes in its:.'ong term care system. One ofthese changes was to institute case management services at hospital discharge. Table 2.16 reflects the change in long term care clients between Colorado and Oregon in 1990. Although the two states were similar ten years ago, in 1990 Colorado served approximately 12,000 Medicaid clients in nursing homes and between 5,000 6,000 Medicaid recipients in the community. Oregon served 7,500 Medicaid recipients in nursing homes, a thousand fewer than ten years I Further, Oregon is serving 13,000 Medicaid recipients in the community .. oregon is serving 2,000 to 3,000 more people at a cost of $20 million a year less than Colorado. Although no data is available to determine the extent to which case managers at hospital discharge contribute to the $20 million per year I' savings or to the increase in individuals served at home, the numbers are sufficiently stagger:ing to warrant further research. Sufficient evidence exists in the literature to propose case management services as an !ntervention to prevent premature admissions to nursing homes. I 78

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Table 2:15. Comparison of LongTerm Care Clients in Colorado and Oregon: 1980. ' Colorado Oregon ,. Nursing Home Population on 8,500 8,500 Medicaid Home Care Population 2.500 4,000 Total 11,000 12,500 Note. From "Funding for Long-Term Care and Case Management," (pp. 123-124) by R. Ladd in Kane et al., Case Management: What Is It Anyway?, 1990, Minneapolis, Minnesota: University of Minnesota. Table 2.16. Comparison of Long-Term Care Clients in Colorado and Oregon: 1990 Colorado Oregon Nursing Home Population on 12,000 7,500 Medicaid Home Care Population 5,000 13,000 Total 17,000 20,500 Note. From "Funding for Long-Term Care and Case Management," (pp. 123-124) by R. Ladd in Kane et al., Case Management: What Is It Anyway?, 1990, Minneapolis, Minnesota: University of Minnesota. Although much of the literature promotes the use of case management for cost containment reasons, Califano suggests that case management with care in the home is more huniane . . where people can be self-sufficient and stay at home with some care, is the solution we should seek for most of our elderly, not the institutiol")al. nursing home. The reasons are not simply financial; indeed, the most important ones are humane. Most people would much prefer to live in their homes and function independently than to endure the lethargy of institutionalized way stations on the road to death. (Califano, 1986, p. 174) 79

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If case management services are deemed to have such a positive impact, :I why is the availability of these services so limited? As previously cited, over 24 states now offer Medicaid funded case management services for adult Medicaid patients who are already in nursing homes or are determined eligible for nursing home placement. No other reimbursement through Medicare or Medicaid is available to prevent institutional placement or prevent older adults from admission to the Medicaid program after they've spent their resources on nursing home care. On a ,private pay basis, a few insurance companies are piloting long term care insurance which includes case management. A number of large national corporations recently started offering elder care services to their employees -one of the elder care services is case management. These progressive insurance companies and employers are small in numbers. Case management agencies in the Denver region which specialized in for-pay services to high income families were unable to generate a sufficient client base to stay in business. As case management services become well known, and as the reimbursement sources for this service increase, more older adults and their families will seek the services of a case manager. Can a case manager, at the critical point in time when decisions are made about institutionalization, prevent or delay referrals for premature institutionalization? If the investment of Medicare reimbursement for case management services' at hospital discharge was able to prevent the costly shift of patients into the Medicaid program, millions of public dollars expended on unnecessary institutional care could be saved. 80

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CHAPTER 3 RESULTS The purpose of this exploratory research was to: (1) determine the extent to which the intervention of a case manager at discharge can prevent or delay nursing home (2) describe the demographic characteristics of the hospitalized age 75 and older in 5 Denver metropolitan area hospitals; (3) identify the extent to which hospitalization provokes housing changes for older adults age 75 and older on Medicare; (4) determine the nature and predictors of those placements; (5) determine the permanence of the placements; (6) determine patient satisfaction with hospital discharge planning; (7) describe the discharge planning processthrough observation; (8) survey hospital discharge planners regarding their comfort with the responsibility of housing placement at discharge; and (9) recommend further quantitative or qualitative research to follow-up on the findings from this research. The results .of this exploratory research will be presented in three major sections. First, the indicators of housing placement will be discussed. Descriptive information regarding hospital discharges from the five participating hospitals will be examined. Second, the effects of the case manager intervention will be evaluated. Finally, current and proposed models regarding the hospital discharge process will be presented.

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Description of Hospital Admissions Patient Characteristics This sampled 1 ,040 Medicare admissions of persons over age 75 to five hospitals. Patient characteristics of the sample were identified, and rated to the type of housing to which these frail elderly respondents were discharged. The average age of this sample was 82; over half of the respondents were widowed. Predictors of Housing Placement at Discharge Not surprisingly, frail elderly admitted from independent environments were most likely to return to independent environments. However, other factors influenced the types of housing to which respondents were discharged. Age, marital ' status and gender all influenced the degree of independence in discharge housing. Likely marital status was the major factor in planning of discharge housing (age and gender systematically linked to marital status because older persons and women are more likely to be widowed). Generally, married persons were more likely to be able to return to their own homes, perhaps due to the support available in the home. Men in this cohort were far more likely to be married and, therefore, to have a caretaker in the home; they were much more likely to be discharged to their home. Women were far more likely to be unmarried or widowed, and thus to be discharged to long-term care despite being admitted from their own homes. By using regressio.n equations, it was possible to predict the degree of independence in discharge housing with information on housing at admission, marital status, age, and gender. 82

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I i' As is evident in Table 3.1, married males were the most likely group to return to their own home from a hospital stay. Unmarried males were no more likely than unmar(ied females to be discharged to home (with or without services). Unmarried persons were far more likely to be discharged to nursing homes than married persons (approximately 14 percent of married and 29 percent of unmar ried), a pattern similar to effects of marital status on admissions from nursing I I I. homes (1 0 percent of married and 24 percent of unmarried). Table 3.1. Housing Level at Discharge by Gender and Marital Status 1 Married Unmarried Males Females Males Females Housing Levels N %2 N % N % N % Home-no services 139 64.1 54 47.8 64 41.6 179 35.6 services 22 10.1 17 15.0 6 3.9 48 9.5 Congregate .5 1 .9 3 1.9 15 3.0 Relative's Home ''f 4 1.8 4 3.5 12 7.8 41 8.2 Assisted Living 0 1 .9 4 2.6 4 .8 Rehabilitation Extended Care 5 2.3 8 7.1 6 3.9 32 6.4 Nursing 30 13.8 18 15.9 40 26.0 158 31.4 Home/Hospice 0 2 1.8 .6 2 Died 16 7.4 8 7.1 18 11.7 24 1lncludes patients for whom data were available on all three variables, N=987. 2Column percentages add to 1 00%. In order to evaluate the significance of marital status and gender on discharge placement. housing levels were collapsed into four levels (without services, supportive housing, nursing care, and hospital) and submitted to a chisquare analysis by gender and marital status. Although the chi-squares for .4 4.8 83

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housing at admission were not significant, indicating no differential effects of gender and marital status on housing type at admission, the chi-squares were significant for housing level at discharge. Among married persons, men were significantly more likely to return to their own home at discharge (69 percent), while women were more likely to be in supportive housing (22 percent), nursing care (25 percent), or the hospital (2 percent) (chi-square= 12.54; df=3; p<.0001). As described above, married persons were far more likely to be discharged to inde. :. pendent housing and far less likely to be discharged to nursing homes than unmarried peisons (chi-square=47.85; df=2; p<.0001 ). There were no significant differences among unmarried men and women as to their housing level at dis-' i charge. Housing levels were ranked from most independent to most dependent and assigned a value to create an ordinal variable on which correlational data analyses , could be The housing levels listed in Table 3.2 were assigned values from 1 (own home without services) to 8 (hospital). This variable representing housing dependence (higher values reflect more dependence) was then correlated with background variables of the patients. (See Table 3.3.) Housing levels at admission and ,at discharge both correlated positively with age, health, gender, and marital status: :The direction of the correlations indicated that older women rated in poor health at discharge were most likely to have been in dependent housing at admission as well as at discharge. 84

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Table 3.2. Housing Level Eight Weeks after Discharge by Gender and Marital Statl:IS1 : Married Unmarried Males Females Males Females Housing Levels N %2 .J:L % .J:L % .J:L l Home-no services 79 60.3 34 41.5 20 24.4 82 24.5 Home-wnh services 25 19.1 23 28.0 17 20.7 79 23.6 Congregate .8 2 2.4 2 2.4 11 3.3 Relative's Home .8 2 2.4 7 8.5 29 8.7 Assisted Living .8 1.2 4 4.9 4 1.2 Rehabilnation Extended Care .3 Nursing 9 6.9 12 14.6 26 31.7 103 30.7 Home/Hospice 1 .8 1 1.2 Died 14 10.7 7 8.5 6 7.3 26 7.8 11ncludes patients for whom data were available on all three variables, N=630. 2Column percentages add to 1 00%. Table 3.3. Correlations of Background Variables with Housing Type. (Sample Sizes are Noted for Each Correlation) Housing at Mama! Admission Health Gender Status Age .19** (1004) Health1 .25** .13** (744) (756) Gender .15** : .08* .02 (1000) (1036) (752) Mamal .11** .09** .06 .22** Status3 (1004) (1040) (756) (1036) Housing at .62** .23** .40** .11** .15** Discharge (999) (1012) (749) (1008) (1012) Housing at .68** .29** .43** .12** .15** 8Weeks (639) (643) (455) (640) (643) *p less than .01 **p greater than .001 Housing at Discharge .76** (641) 1Health ratings made by discharge staff 1= very good, 2 =moderate, 3 =very poor. 2 Male = 1, Female = 2. 3Married = 1, Unmarried = 2. 85

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A regr,ession equation predicting housing level at discharge was construct-.' ed. Stepwise:procedures using the background variables (housing at admission, I age, marital status, and health) yielded an I equation accounting for 54 percent of the variance. Results of this analysis are presented in Table 3.4 which shows the step at which each variable entered. Stepwise procedures take the best predictor at each step from the pool of available variables. Table 3.4. Regression Equation Predicting Housing Level at Discharge. Step Patient Variables Bela .E R2 R 2 Change Housing at Admission .6935 413.18 .4809 .4809 2 Age .1890 236.44 .5152 .0343 3 Health .1641 173.62 .5398 .0246 4 Gender .0678 132.30 .5443 .0045 In predicting discharge housing dependence, level of housing dependence at admission was the most powerful predictor, accounting for 48 percent of the variance in the dependent variable. Age, health, and gender all added significantly to the ability of housing at admission to predict housing at discharge, although together they accounted for only another 6 percent of the variance. The order of I entry of these variables indicates, for example, that even once the effects of admission housing, age and health are accounted for, gender still was a significant predictor of discharge housing. Because the variance shared between gender and the other predictors (age, health and housing at admission) was already in the equation, the additional .5 percent of the variance which gender accounts for is 86

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"unique variance",;(see R2 Change column in Table 3.4}, or effects of gender that go beyond its shared effects with age, health and admission housing. Although significant, this is a miniscule amount of variance which lacks substantive importance. The direction of effects for these variables indicates that patients discharged to dependent housing were more likely to have come from dependent housing, and to. be older, female, and rated as in poorer health at discharge. It is important to note (hat due to correlations among the predictor variables, it is not meaningful to compare directly the Beta weights of the predictor variables in order ' to determine the relative importance of each predictor. A second predictor equation was built using demographic characteristics alone, omitting housing level at admission as a predictor. Once again, health, age, and gender were the significant predictors (marital status was not significant}, but the three accounted for only 24 percent of the variance. When admission housing information is not available, much power will be lost in predicting discharge '!' housing. Nonethele.ss, it is striking that age, gender, and an extremely simple health measure afford this much predictability. Predictions of Housing Level Eight Weeks after Discharge Housing level at the eight week follow-up was correlated strongly with housing level at discharge as well as with several background variables (see Table 3.5}. Regression equations predicting housing at eight week follow-up were constructed using stepwise procedures. The same variables predicted housing level at eight weekS and housing level at discharge. Table 3.6 presents the results ., of the first equatron, which included housing level at admission, health, and age as predictors and accounted for 52 percent of the variance. The second equation 87

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Table 3.5. Regression Equation Predicting Housing Level Eight Weeks after Hospital Discharge. Step Patient variables F R 2 Change 1 Housing at Admission 2 Health 3 Age: .6588 .2664 .1542 341.95 222.08 161.72 .4340 .4995 .5221 Table 3.6. Stepwise Regression Equation Predicting Housing Level .4340 .0655 .0226 of Elderly Patients (75+) Eight Weeks after Hospital Discharge. Step Patient Variables Beta F R2 R2 Change 1 Housing at Admission .5585 341.95 .4340 .4340 2 Health .2515 222.08 .4995 .0655 3 Age: .1542 161.72 .5221 .0226 predicting hqusing level at eight week follow-up omitted the admission housing variable to determine the amount of variance accounted for by demographic characteristics alone. Age, health, and gender provided the best set of predictor variables which accounted for 24 percent of the variance. Nursing Home Discharges In comparison with patients from other types of housing, patients admitted from, and discharged to, nursing homes were older, and in poorer health. Unmar ried persons, most of whom were women, were far more likely to be discharged to 88

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,,, nursing homes than married persons. Despite their poorer health, persons dis-' charged to nursing homes were no more likely to be hospitalized during the two weeks after discharge than other elderly. One set of subjects of special interest are patients discharged to nursing homes. Although, the percentage of subjects living in nursing homes does not vary dramatically from ,admission to discharge to 8 week follow-up, it is not clear from simple percentages whether the same persons are living in nursing homes at each ',I' period of assessment. It would seem likely, for example, that nursing home patients entering the hospital might be at greater risk of death during the hospital ization than persons coming to the hospital from other housing levels. In fact, the ,' probability of dying during the hospitalization is no different for persons admitted I I from nursing homes. Of the 71 persons who died during their hospitalization, 16 ' (22 percent) were admitted from nursing homes. This represents 8 percent of admissions from nursing homes (N=194), only slightly more than the 6 percent (55 of 908) of patients .. admitted from other types of housing. A total of 76 new persons were discharged to nursing homes who were not admitted from nursing homes. Other analyses of this subsample of patients admitted from nursing homes in comparison with'patients from other types of housing indica:te that nursing home patients are and rated as in poorer health than non-nursing home admittees. Similarly, persons discharged to nursing homes are older and in poorer health than others in the sample. These patients are no more likely than persons discharged to other housing types to be hospitalized during the two week period after discharge. 89

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Hospital Diffe'rences in Housing Placements I The five participating hospitals drew from diverse patient pools. Frail elderly patients admitted to the five participating hospitals differed in age and health. Even ' when these: patient characteristics were accounted for, however, the hospitals also differed in discharge practices. Some hospitals discharged to more independent I, housing. Although there were no differences in likelihood of readmission to the hospital during the two weeks after discharge, patients discharged to independent housing made. fewer doctor visits in the first eight weeks after discharge than patients dischfrged to more dependent housing. This research could not identify the reason for different discharge practices. Preliminary analyses indicated there were differences among the hospitals on patient variables which were likely to be related to housing levels (specifically, age and health). In order to remove variance in discharge housing placements which might be due solely to differences in patients, these patient variables are used as co-variates in analyses described below. Note also that due to the small number of data points available from one hospital, Mt. Airy, the analyses of variance below exclude that hospital. Hospitals differed significantly on discharge placements, even after differences among them on patient variables (age and health) were accounted for (F=18.75; dt:i:2.730; p<.0001). Mean housing levels ranged from 2.97 to 4.19, reflecting a considerable amount of variability in discharge practices. Similar differences were found eight weeks after discharge (F=11.08; df=2.443; p<.0001; means range from 3.01 to 4.14). Although the patients from the different hospitals 90

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1,, did not differ in of rehospitalization during the eight week follow-up period, there were significant differences in number of doctor visits within the first '' 'I two weeks (F=8.70; df=2.504; p<.0001; means range from .48 to .89). The hospitals with most extreme means on the two housing variables (at discharge and eight week :follow-up) also had the extreme means on number of doctor visits. The hospital with, patients discharged to the most independent housing also had I patients who reported the fewest visits to the doctor. The SOL-!rces of variation among the hospitals is not evident from these data. Because the analyses used age and health as covariates, differences in patient frailty are not likely to explain these differences. It is possible, of course, that the simplicity of the health measures mask meaningful health variability which could have been useful in explaining the different practices among hospitals. The strong relationship between housing at admission and at discharge suggests that hospitals '' I which differ on discharge placements may also differ on admission. For example, the hospital with patients discharged to the most independent environments also has a disproportionately low rate of admissions from nursing homes (only 6.6 percent of the total admissions from nursing homes comes from this hospital even though 20 percent of the overall sample was drawn from nursing homes). In summary, hospitals vary in the type of housing placements of elderly Medicare patients. The differences may reflect different discharge planning skills or policies, or may .. be only differences in patient characteristics. 91

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Effects of the Case Management Intervention Generalized on Hospital Discharges I the third and fourth month at each hospital, the case manager was available to the discharge planning department. The case manager was available on a consultative basis to offer resource information, recommendations, or respond to referrals for direct intervention with this patient. It was expected that the case manager's at the hospital would have an impact on the patients' dis.. charge plans Qecause of her specialty knowledge. The effectiveness of the case I management intervention was analyzed by comparing all discharges during the baseline and post-intervention phases with the discharges during the intervention phase on the outcome variables. The research concluded that the. case manager's presence in the discharge department had no generalized effect on the discharge practices of the hospital. Because discharges were planned by many different I personnel (including physicians and nurses who had no contact with the case manager), this lack of a generalized effect is not surprising. Analyses of discharge placements provided directly by the case manager, in comparison with others occurring within the hospital, also showed no differences in level of housing independence at discharge. The research design allows for analysis of general effects of the case manager upon the discharge practices of the hospitals. If case management presence had a generalized effect on the hospitals, the housing outcome ' variables should be different during the "intervention" phase than during the baseline phase., Specifically, it was hoped that the availability of a case manager 92

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would enable discharge planners to work toward more independent housing environments for their patients. The case manager was expected to provide additional information and consultation about housing placements in the community, and about assessments to more accurately determine placement. An important unique function qf. the case manager was the capacity to follow patients for two months. It was: anticipated that the case manager would be able to make placements to housing types due to the ability to follow-up on patients to re-assess the appropriateness of the placement. It was considered possible that effects of the intervention might remain during the final phase if the case manager was able to teach through example different housing placement practices. Analyses of characteristics identified systematic differences in the age and health of patients who were admitted to the hospital during the three phases ... (referred to here as baseline, intervention, and post-phases). These differences are extraneous to the purpose of this study, and confound the interpretation of analyses of the lilousing variables across the phases. The use of the multiple baseline research design allows us to rule out effects (e.g., changes in insurance policy or hospital policy) which might account for different patient profiles across the phases because each hospital proceeded through the phases during a different six month In the absence of reasonable explanatory power of these differences, the due to age and health is removed from analyses reported below using analysis of variance. There were ,no differences in housing placements during the three phases of the study. Patients discharged during the post-phase reported more doctor visits 93

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during the two weeks after discharge (F=1 0.67; df=2.309; p<.001; means range from .45 to 1 ;30) and eight weeks following discharge (F=11.25; df=2.272; p<.05; means range, from 1.76 to 2.60) than patients discharged during the baseline or ': intervention phases, but there were no differences in hospital readmissions. The reason for these differences is not clear. preliminary observations regarding the data need to be made. Of the five participating hospitals, one refused to participate in the case manager ' intervention failing to use the services of the case manager. Thus, data from that hospital was excluded from analyses of the case management intervention. Two hospitals are part of a larger hospital corporation which combine their dis charge services into one department. Data from these two hospitals are presented together. In summary, the case manager had no generalized effect upon the housing discharge practices of the hospital. This may be due to the fact that many discharges are planned by professionals outside the discharge planning department who had no contact with the case manager. Effects of the Case Manager's Direct Services The impact of the case manager occurred in the weeks after discharge due to the ability to track patients after they left the hospital. (See Table 3.7.) There were significan' oifferences in level of housing independence eight weeks later between patients receiving case management and those receiving typical discharge ,. planning The greatest differences occurred in patients discharged to nursing homes.' Patients receiving services from the case manager were more 94

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Table 3.7. Housing Levels at 8 Weeks: Patients Using Case Manager versus No Case Manager. Housing Level Intervention Normal DC/No Follow-uQ I % (N) % (N) '' Home 52 (13) 33 (205) Home-with Ser\tices 24 (6) 23 (140) Congregate 4 (1) 12 (15) Relative's Home 8 (2) 6 (37) Assisted Living 4 (1) 2 (9) Rehabilitation/Extended Care 0 (0) --* (1) Nursing Home/Hospice 4 (1) 25 (155) Hospital 4 (1) --* (1) Died 0 (0) 7 (55) Total 100% 25 100% 618 *less than 1% likely to have left the nursing home for more independent housing than were patients discharg:ed without her services. This effect appears to be due to the ability to track patients after they left the hospital, to reassess their abilities, and facilitate moves back into independent housing when their health permitted. This service is beyond the purview of traditional discharge planning functions, but appears to have a major impact on long-term housing placements. A more precise measure of the impact of the case manager is to compare housing levels of patients with whom the case manager made direct interventions and those with whom the case manager had no contact. Thirty-five subjects were identified as recipients of the case manager's direct service. Data on housing level 95

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at discharge'and at eight week follow-up served as the dependent variables in tests ,. comparing supjects receiving housing counseling (complete data were available on 25 subjects). These groups do not differ significantly in their housing levels at discharge (using housing level as an interval variable). In terms of percentages of nursing home placements, however, the counselor placed 81 percent of patients in non-nursing home settings while hospital staff placed 72 percent of patients outside of nursing (See Table 3.7.) The most powerful finding is that there are significant differences in patient housing levels eight weeks after discharge with the case manager's patients living in more independent housing than the other patients (t=3.72, df=29; p<.001; mean housing levels:were 2.24 and 3.75). This finding implies that the impact of the case manager occurred in the weeks after discharge. The patients in the two groups did not differ on background characteristics (e.g., age or health) which might influence the interpretability of the results. Patients receiving case manage ment also reported significantly fewer hospital visits within the first eight weeks following discharge (t=2.69, df=31, p<.011.) The impact of the case manager's tracking of patients after discharge appeared to be' the most significant tor patients discharged to nursing homes. Eight weeks after discharge 96 percent of the patients tracked by the case manag er were not in nursing homes, and 73 percent of patients discharged by hospital personnel (without follow-up) were not in nursing homes. It is important to examine I the housing shifts which occurred in the eight weeks after discharge to a nursing ,. home. Patients in nursing homes who were served with typical discharge services 96

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(no follow-up) were highly likely to still be in the nursing home (73 percent) while of the four patients discharged by the housing counselor to nursing homes for whom follow-up data were available (for two of the case manager's patients discharged to nursing only one (25 percent) remained eight weeks later, two were in independent and one was hospitalized. While this .sample is too small to draw major conclusions, these data are consistent with the hypothesis that the case manager's main impact would be through her follow-up activities with patients discharged to nursing homes. These results suggest that the effect of a case manager (which includes intervention at the time of discharge as well as case management) has its impact in the two months following 'discharge, but does not significantly affect the discharge placement. Patient Satisfaction with Hospital Discharge Services A large percentage (88.2 percent) of the elderly participants did not rate their satisfaction with discharge services during the two and eight week follow-up calls. Of the subjects reached by telephone for the follow-up calls (N=724), most (83.1 percent) did not recall a specific person who functioned as a discharge planner and therefore, were unable to rate their satisfaction. Subjects who made ratings (N=123) were very satisfied with the discharge seniices. Ninety-four (77.3 percent) rated themselves as a six or seven on a seven-point satisfaction scale. The qualitative collected during the research serves as an explanation for these results. When this research was initiated, there was a perception that discharge planning was conducted on a one-on-one basis with the patient. The 97

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"shadowing" .of discharge planners revealed that discharge planning is more frequently conducted by reviewing patient charts and consulting with other profes sionals rather than personal contact with the patient. One of the reasons the subject did not. recall a specific person who functioned as a discharge planner may be attributed to the fact that most patients had no personal contact with the planner. Another explanation is the variation in titles used in the hospitals (e.g., social worker,. utilization review coordinator, discharge planner, etc.). A patient who was asked about discharge planning may not have connected the discharge planning functi.on with a hospital employee with the title of social worker or utiliza tion review coordinator. Perceptions of .Service Offered During the intervention phase of this research, discharge planners were asked to rate 'the amount of services offered by their hospital in several areas: housing referral, housing follow-up, mental health referral, home health referral, and general services (e.g., meals and transportation) referral (see Appendix G). The discharge perceived their hospitals as offering comprehensive services in all areas except housing referral. A multivariate analysis of variance demonstrated the significant difference among the service areas (HotellingsT2=155.63; p<.001 ). Follow-up tests :identified the focus of the different perceptions of services. The discharge planners perceived their hospitals' services to be less comprehensive in the areas of housing referral and housing follow-up than in any other area. (See Table 3.8.) On. a scale ranging from 1 to 50 (50 represented the most comprehen sive services), discharge planners rated their hospital's services on housing referral 98

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Table 3.8. Discharge Planners' Perceptions of Adequacy of Services to Elderly Medicare Patients 1 Services Mean Standard Deviation Housing Referral at Dis21.60 15.42 charge '. 2 Month Post-Discharge 10.87 8.77 Mental Health Referral 45.47 4.26 Home Health Care 45.87 4.24 Family Counseling 43.33 8.17 '' Other Human Seryices 38.93 10.28 1 Each item was rated on a Likert-type scale from 0 to 50 with 0 anchored with "Our Hospital Do.es Not Attempt to Provide this Service" and 50 anchored with "Our Hospital Offers Comprehensive Services in this Area." with a mean of 21 (SD=15.4), and their hospital's ability to offer housing follow-up referral as 10.87 (SD=8.7). Mean ratings of services for other referral types ranged from 38.93 to 45.87. The variability in perceptions of comprehensiveness of services was in the areas of housing referral than in other service types as well. Qualitative Research Phases and Results This phase of the research was developed using the concepts by Kirk and Miller (1986). The tour phases for development of effective qualitative research design as by Kirk and Miller are: 99

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1. Invention preparation for research design and plan of action for i,l managing thequalitative research project. 2. Discovery this is the phase of observation, measurement and data collection. 3. this phase produces understanding from the evaluation and analysis. 4. Explanation the communication of the end-result is the product for this phase of qualitative research (Kirk & Miller, 1986, p. 60). While quantitative research emphasizes multivariate analysis with a lack of emphasis on context, qualitative research focuses on the situation and the structur-' al contexts ass,ociated with the research (Strauss, 1987). This research has utilized both quantitative and qualitative approaches to the problem of applying the prospective payment theory to patient care outcomes. Using the multivariant approach in the quantitative component of this research, the prime goal was to identify key variables for predicting high risk patients for placement at discharge and predicting the role which the case manager plays at hospital discharge. While the qualitative research has produced surprising results, the inclusion of the research function has provided even more interesting outcomes because the contextual and situational findings reveal other factors which may inhibit or enhance the placement of patients at discharge and may affect patient placement weeks after discharge. These factors would not have been identified if qualitative research design methods had not been applied. 100

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II Invention testing is not the only research activity in any scientific disci pline. Indeed, the most dramatic discoveries necessarily came about in some other way, because in, order to test a hypothesis the investigator must already know what it is he or she is going to discover" (Kirk & Miller, 1986, p. 17). The qualitative aspects of this research provided insight into the discharge planning process. Prior to describing moqels for discharge planning, a description of the environment sets the stage. The hospital discharge planning process was more dynamic than anticipated prior to starting the research. Qualitative data were collected during the data collection process at each of the five hospitals. However, in order to more clearly describe the environment and develop appropriate recommendations, an observation period was added to this research. A hospital, different from five hospitals participating in the quantitative research was selected for observation. Selection of a hospital did not impact the data collection process and it did not create a Halo effect at the five target hospitals. A local 200 bed general hospital was selected to observe for the following reasons: a description of the discharge planning environment enhances the quality of the research and the ability to decipher the results, the discharge planning staff allowed a backstage observer, and the staff agreed to waive patient confidentiality if the hospital name and patients' names were not reflected in any write-up. Two other hospitals would only allow observation if every patient signed a waiver to allow observation. Observation consisted of shadowing for two routine days with one hospital discharge planner, asking unstructured questions throughout each day and calling 101

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the discharge. planner for two weeks after the observation period to re-check the accuracy of the perceptions. Further, an afternoon was spent at the Colorado Association of Hospital Social Workers' annual meeting, listening to their issues and concerns: Althoug'h the two day timeframe seems short for an observation period, the time was sufficient to clearly describe a day in the life of a discharge planner at one hospital. These qualitative data were collected in addition to the observation data collected' at the five hospitals which participated in the research. The dis charge planner selected for observation had worked two previous years floating as a discharge planner at half of the other 22 hospitals in the region. Prior to her rotation, she worked five years at a mid-size downtown hospital. Her knowledge was extremely helpful when comparing procedures at the observed hospital with others in the metropolitan area. The two discharge planners at the 200 bed general hospital had a large office on the top floor. Since the floor was being remodeled, it was quiet but required walking through major construction when leaving or arriving. The two desks were piled with forms, messages, resource directories and family portraits. Both discharge planners worked approximately 30 hours per week. The discharge planner readily talked about the hospital and her role. The hospital was only 50 percent occupied at the time of the observation. Currently the discharge planners work with 20 to 30 patients at a time. Two years ago, only 15 percent of the hospital's admissions were elderly; currently it's 20 percent and increasing. The two discharge planners were concerned that they did not have 102

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time to see all the patients and they did not believe the hospital would increase ', their discharge planning staff. The follqwing "Discovery" section summarizes the major observations condensed from 43 pages of notes. The observation period in this research ,, generated similar findings as noted in the General Accounting Office reports regarding the ir;npact of prospective reimbursement on hospital discharge planning: shorter timeframe to provide discharge planning, earlier discharge, and sicker patients at discharge. Further, the discussions and observation raised a new series of issues: variations in discharge procedures between hospitals, service resource problems, the role of physicians in discharge planning, family counseling, insurance and reimbursement issues, the impact of prospective reimbursement, and management:issues. The following section describes the observations along with the implications. Discovery Discovery: Discharge Planning Process The pace at the hospital was constantly hectic from the 7:45 a.m. opening of the discharge planner's office to the 5:00 p.m. locking of the door. The day began by collecting messages from the answering machine. The first day, 12 messages were picked up; the second day there were 17. Messages were from physicians, family 111embers, local nursing home staff and other nursing staff in the hospital. The internal hospital mail box was checked and all of the pink "discharge sheets" were pulled; These sheets were sent daily to the discharge planners by the hospital DRG Coordinator; prior to the changes in Medicare to prospective 103

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I',' reimbursement, the DRG Coordinator's title was Utilization Review Coordinator. ,, The DRG Coordinator reviewed all Medicare patient charts daily to ensure that patients did not stay longer than the reimbursement period. When the patient is admitted, pink forms for discharge/DRG assignment are sent to the discharge planner. of these forms triggers a "discharge planning assessment" for each of the and Medicaid patients in the hospital. The 'hospital discharge planner takes the pink forms to each floor, reviews the patient and completes a "discharge planning assessment." Twenty-two assessments were completed the first day; thirty were completed on the second day. To the observer's surprise, no patients were actually seen to conduct the assessments.' : The patient charts were reviewed and information was transferred to the "Discharge' Planning Assessment" form. Information collected from the patient chart included:;:, patient at hospital before, diagnosis, address, living situation, nurse's assessments from admission, close proximity of family, whether patient is confused, need for supportive devices (e.g., wheelchair), whether patient lives with a developmentally disabled daughter/son, if they are blind or deaf, etc. Completion of all the assessments took two and a half to three hours per day. The only patients who are visited personally were perceived by the discharge planner to have a need for more supportive services when the patient was discharged to their home. Four older patients had been admitted the end of the previous week and were discharged over the weekend. No discharge plans were completed on these 104

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patients; they were discharged before they were seen since discharge planners in ,, the hospital don't' work on weekends. Discovery: The Physician's Role in Discharge Planning i Three situations were observed. First, a physician called requesting information from. the hospital discharge planner. Mrs. Y will be discharged tomorrow. Her condition was described. The discharge planner was given the names of two nursing homes where the physician wanted to refer her. The discharge planner was asked to determine the patient's payment sources and the availability of beds for her condition and financial resources. The discharge planner made calls to several local nursing homes; calls were friendly, cooperative and brief. Staff know .each other on a first-name basis. The physician recommended nursing homes which did not offer the specialized services the patient needed. One nursing home had no Medicaid beds available, only private pay. Since the patient was on Medicaid, the physician's choice was not acceptable. The other nursing home sele.cted by the physician did not have trained staff or facilities which would prevent the. male patient with Alzheimer's disease from wandering out of the facility. The discharge planner commented that "physicians are rarely aware of other services available in the community, usually recommend nursing home placement, and .frequently recommend facilities which are in close proximity to their office for visitation rather than facilities which are most appropriate for the care and financial condition of the patient." On two additional occasions during the observation period, physicians referred patients to nursing homes which did not accept Medicaid patients; the 105

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discharge planner had to find an alternative facility which met with the approval of ',.' the physician, patient and family. Discovery: Family Counseling Although the time spent with families was limited, the discharge planner was calm, patient, and helpful. The first morning, a family member had left a message requesting time to see the discharge planner. After a call to the nurses' station outside the patient room, the patient's brother came up to the office. He articulately described !l,is relationship and knowledge of his sister's condition. He had contacted many nursing homes himself and seemed very knowledgeable about the facilities and his sister's needs. He was concerned that the doctor wanted the patient discharged to Cherry Creek or Sable Nursing Homes. Neither nursing home had any Medicare beds available; the brother made suggestions about other facilities he preferred. Could the discharge planner call them? Yes, she agreed to call the two other facilities that day. The discharge planner had brochures about the two facilities he suggested; she gave them to him to read. The discharge planner went to see the patient and read her chart to see if there were other complications which required special care from a nursing home. The patient was 67 years old and was admitted from Manor Care Nursing Home where she had been a resident for six years. She was admitted with a medical diagnosis of an inoperable tumor in the pancreas; secondary diagnosis was Alzheimer's Disease. Only one of the nursing homes discussed with the patient's brother could provide the needed care. The hospital discharge planner would check to see if a bed was available so the patient could be transferred. 106

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The discharge planner remarked that most family members are not as well informed about services as the brother of this patient. Frequently family members have a difficult time making decisions for their relatives since they are unaware of services which are available or whether the services will be covered through insurance, Medicare or Medicaid. I During the consultation with the patient's brother, it was interesting to observe that most of the brochures available on the rack in the discharge planner's office were from nursing homes rather than other in-home service agencies. The discharge planner, remarked that the facilities were good about providing them with enough brochures to distribute to the families. Resource information is vitally important to the discharge planners. After a lengthy discussion, the discharge planner concluded that extensive work must be conducted to ensure that hospital discharge planners have current directories of information about available services. The discharge planning budget only allows the purchase of limited information, therefore, the information which is available directly influences decisions about referrals. More information is needed about in-home services. The discharge planner also confirmed previous General Accounting Office studies; it's difficult to obtain transportatiqn, home health or home delivered meals the same day or the day after the goes home. Therefore, discharge planners don't make as many referrals to these services because it takes too much time to arrange them. Another family meeting was held to discuss discharge options other than nursing home placement. The physician referred the patient to a nursing home; the patient refused .to go. The family supported the patient's decision and decided 107

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to obtain honie health care. The discharge planner called the home health agency; sixty days of care was arranged to be paid by Medicare; the family agreed to pay for the balance and fill in on weekends. The discharge planner commented that family systems frequently prevent patients from going .to nursing homes. Families provide care in the home often on a 24 hour-a-day basis. Discovery: Insurance and Reimbursement Issues The first insurance issue arose when a head nurse reported to the discharge planner that a patient signed a form discharging herself from the hospital against physician's orders. The patient refused treatment and decided to go home. The discharge planner described the potential problem with the patient's insurance company; since the patient refused care "against medical orders," the insurance company will refuse to pay the bill. The discharge planner and nursing staff suspected alcoholism, however, the patient refused treatment and left the hospital. The discharge 'planner did not have contact with the patient. The bu$iness department called the discharge planner: "can a 16 year old girl get Medicaid to pay for a miscarriage?" The discharge planner responds "not unless she has other children." If the patient has other children, she could get '' Medicaid through the other children. The nurse checked to see if the patient had other children; she called back later. The patient had no other children. The discharge planner stated that she was not eligible for Medicaid and since the patient had 'lO insurance the hospital was at risk of non-payment. Four family members were counseled each day. One couple was concerned about the wife's mother who did not want to pay her medical bill and she 108

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'J was not eligible: f9r Medicare. The discharge planner spent 17 minutes explaining that when the patient's husband died, the patient took a lump sum payment from '' his Railroad Retirement Insurance so there was no long term coverage. The 77 year old patient fell and fractured a hip; the hospital bill will be 'J around $8,000. 1he patient had sufficient funds in savings but refused to use her savings to pay ttte hospital bill. The patient had an income of $1,000 per month but no insurance. Although the hospital bill would reduce the patient's savings significantly, the family was informed that the patient must pay the bill. The disqharge planner talked about the families lack of information about Medicare, Medicaid, in-home services, insurance, or housing options. Hospital discharge planners just don't have the hours needed to counsel these families. Interpretation Interpretation: Discharge Planning Process As previously noted, the American Hospital Association simply defines discharge planning as "an interdisciplinary hospital-wide process that should be available to aid patients and their families in developing a feasible post-hospital plan of care" (American Hospital Association, 1984). This definition does not encompass the breadth of issues involved in the discharge planning process observed at the Prior to this observation, this researcher's perception was that each Medi-'' care patient was paid a personal visit by the discharge planner to conduct an assessment and arrange for the services. The observation period clearly changed the perception of the discharge planning process. Discharge planners work in a 109

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stressful, frantic, fast-paced environment. The qualitative research revealed nuances about the environment which have not been adequately addressed in previous research. Without this observation period, the issues could not have been properly focused. Although background preparation and reading on the subject was extensive, observing the environment contributed substantially to new ques tions about how to impact the discharge planning process. The dynamics are multi-faceted; the hospital discharge process is not the formal, routinely methodical procedure envisioned prior to this research. The literature rarely mentions the role of the physician in hospital discharge planning. A rare exception was the U.S. General Accounting Office report (1987) which claimed that in 23 percent of the Medicare referrals for discharge planning are by physicians. The observation period in this research demonstrated an active role by physicians in determining the post-hospital destination for their patients. During the observation period, the discharge planner was constantly called upon to recall reimbursement requirements for Medicare, Medicaid and a variety of private insurance programs. The discharge planner claimed that she learned the requirements on the job; there was no formal training about the limitations or requirements. Interpretation: DRG Impact The discharge planner talked about the major changes which occurred since DRG's, or prospective reimbursement, were initiated for the Medicare program. She experienced a new emphasis on discharge planning and very close hospital monitoring of the length of stay. The hospital renamed one of their 110

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administrative staff "DRG Coordinator." The fixed payment by diagnosis rather than the number of days at the hospital created tight control over the length of stay. Other issues causing tension for the hospital were the low reimbursement rates from Medicare and Medicaid, the large number of patients without insurance or who were unable to pay, slow reimbursement from Medicaid, and insurance I companies which refuse to pay for procedures which are covered in the patients' policies. The discharge planner described the difficulty in obtaining services for patients in such period of time and problems encountered when physicians make referrals to nursing homes but the patient could receive services at home for less cost. Nursing homes become a convenient referral source when time is limited. Each discharge planner had a personal relationship with different facilities; i they knew which facilities consistently accepted patients from the hospitals so they wouldn't have to make an excessive amount of calls in order to discharge the patient. Accordihg1 to the discharge planner, many more patients were discharged to nursing homes currently than prior to the implementation of prospective reim bursement. Interpretation: Management Issues Hospitals are required by the federal government to provide discharge planning services as a condition for receiving reimbursement from Medicare or Medicaid. The discharge planner claimed that since the hospital did not receive reimbursement for discharge planning as a discreet service, the planning was not perceived as a valu,able hospital service. Frequently the discharge planners saved the hospital money as a result of their knowledge about the payers. For example, 111

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' i the discharge planner described two situations where they were able to place a ,. patient onto the Medicaid program in order to obtain coverage for the patient care; ,, in one case the hospital received $20,000 and in another case $1 00,000 in reimbursement for care provided. The hospital would not have been reimbursed for this care without the direct intervention of the hospital discharge planner. However, the. planner felt that throughout the hospital industry, discharge planners were understaffed and undervalued in terms of their work. The. second management issue consisted of a call from the discharge planner to her supervisor regarding suggested procedural changes for discharge planners to adequately obtain needed services for the patients. Also the discharge I planner requested permission to work overtime by four hours during the week. The supervisor only authorized two hours overtime and said to take two hours off the following week; the hospital couldn't afford to pay overtime. The discussion reflected by the discharge planner--"too much work and not enough staff." The discharge planners didn't have enough time to go to meetings and simultaneously complete patient charts. Staff already work on Joint Commission for the of Hospitals' guidelines and paperwork at home because there wasn't enough time to complete the required paperwork during office hours. Interpretation: Resource Information on Alternative Patient Servicing The observer noted a lack of resource information about alternative patient services. Most of the brochures used were from nursing homes or large home l health agencies. Some of the materials on the literature rack were from the Denver Region:al Council of Governments' Area Agency on Aging. When asked 112

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' how the planners obtain information about services for their patients, the discharge planrier replied that some agencies send them information but they did not have the money to purchase information nor did they have time to request materials or visit housing or other alternatives. When asked what information would be most helpful for facilitating discharge, the discharge planner said an updated list of housing, nursing home, and public program vacancies are needed so discharge planners don't waste time on referrals to programs or agencies which could not accept patients within 24 hours. Interpretation: Industry Issues After the two day observation period, an afternoon was spent at the annual meeting of the Colorado Association of Hospital Social Workers. The purpose of attending was to listen to the discussion and obtain any additional information about the problems in the hospital industry which impacted the hospital discharge planners. The agenda included briefings about new research, the state hospital back-up program, federal nursing home admission guidelines, and discussions about quality of care provided by certain home health agencies and nursing homes. There was tension: and discussion about lay-offs in other hospitals and suggestions about promotion of qischarge planning services to hospital administration. Most members were very concerned about obtaining as much information as possible about services they could use to discharge their patients. Concern was expressed that there was no follow-up for patients after they leave the hospital. Discharge planners can barely handle the workload within the hospital; time is not available to serve patients after they leave the hospital. Another sensitive issue was discussed; 113

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.. the nursing shortage is creating tension between nursing staff and social work staff. Some hospitals were using nurses for discharge planning so the nurses could rotate if there was a nursing shortage for the filled beds. Obviously the industry is in transition. The frustration was consistently shared members of the Association. Tension was at a peak since social ' workers were being laid off at Mercy, Swedish and University Hospitals. A number of the participants at the meeting expressed concern that they might lose their job in the near .future. Explanation Overview The fourth and final phase of qualitative research is the explanation of the findings. for the observation in the qualitative research follows: Observations concerning the discharge process suggest that discharge planning in hospitals is in transition due to the increasing mandates for quality discharge services, the increasing number of older patients, and the impact of prospective reimbursement which encourages earlier discharges. Discharge planning serviCes may be influenced by the profession of the planner, the organizational structure of the discharge planning department, physicians, and time constraints on discharge planning services. Personal Visits by Discharge Planners Prior to this observation, the perception was that each Medicare patient was paid a personal visit by the discharge planner to conduct an assessment and arrange for the services. One explanation for the inability to impact the discharge 114

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planning is the nature of discharge plannings. High risk patients need to be targeted for more intensive service. Scheduling Discharge planners work in a stressful, frantic, fast-paced environment. They perceive ,that their department are understaffed, they're rarely allowed to work overtime and they don't have the resources to follow patients after discharge. Discharge planners in this research did not work on weekends. Patients were admitted on Friday and discharged Saturday or Sunday without seeing a discharge planner. If discharges are going to be impacted in the future, high risk patients should be targeted and served regardless of the day of the week they are discharged. Physician's Role in the Discharge Planning Process The obs.ervation period in this research demonstrated an active role by physicians in df;!termining the post-hospital destination of their patients. Frequently during the observation period physicians demonstrated a lack of understanding about non-institutional service options and a lack of understanding about the services for which the patient was eligible. In order to impact the discharge planning process, the role of physicians must be taken into consideration. Discharge Planning and Reimbursement Discharge planners need extensive knowledge about reimbursement requirements for Medicare, Medicaid and private insurance. Unfortunately the discharge planners in this research did not have formal training about benefits and 115

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I" had to learn on-the-job. Lack of knowledge about benefits may negatively impact the service options pursued at discharge. Counseling: of Families Famil,ies need counseling, information and support in order to make decisions about their elderly family members. Discharge planners did not have the hours or staffing needed to counsel the families. Without knowledge about institutional alternatives, families may choose or accept a recommendation of nursing home placement when other housing or service options would be appropriate. Limited Resources '' Discharge planners did not have enough time to visit each of the housing options in the .community and collect resource data. Hospital budgets were not sufficient to purchase resource information. Therefore, discharge planners make referrals to the resources with which they have familiarity. Nursing homes became a convenient, safe referral source when time is limited for patient discharge. These qualitative data represent a limited number of perspectives in a limited numl;>er of hospitals, and are offered as preliminary observations only. There were sufficient consistencies, however, to warrant further study. In the section which follows, the organization of discharge planning, and factors which influence the functioning of discharge planning departments will be described. 116

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'I<< ': CHAPTER 4 CONCLUSIONS AND IMPLICATIONS Conclusions Perhaps the most important finding of the project is the impact the case manager had in the weeks after discharge. Contrary to the research prediction, there were no differences between the patients with whom the case manager worked and those receiving traditional discharge planning in level of housing at admission or at discharge, but there were differences in the housing level 8 weeks later. Apparently the case manager's discharge practices did not differ from other discharge planners, but the capacity to follow patients for two months after dis charge led to changes toward more independent housing. The trend toward case management services, particularly toward the high risk/high cost cases, is increas ing. "Local case managers are being increasingly utilized by the insurance claims industry to pressure quality care and help control both acute and long-term costs" (Strickland & Boling, 1989, pp. 36-37). This finding suggests that the housing level at discharge may be dictated by the patients' health and resources to the point that dependent housing is necessary for convalescence. However, once the convalescence progresses, persons may be able to live in more independent housing, and a case manager who can track these patients over the two month period is in a position to facilitate changes toward more independent housing levels. Discharge planners are, of course, focused on the services needed immediately upon discharge from the hospital. There appears

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to be an advantage to the patients and, potentially an economic advantage to the system by patients over the first several weeks after discharge facilitating transitions'.to. more independent (less restrictive) housing. Impact of Case Management on Hospital Discharge The impact of case management on hospital discharge was primarily successful during the eight weeks after discharge. If case managers were hired to follow Medicc;tre patients age 75 and older, who were discharged to nursing homes for a of eight weeks after discharge, what would be the cost benefit to Colorado? Although the state of Oregon has utilized case managers in this suggested :manner, no data is available to quantify the portion of the $11 million savings in Oregon attributed to case management at hospital discharge. However, a number of assumptions could be made from the current research data. If using a case management approach after discharge results in a 21 percent decrease in the number of discharged individuals remaining in the nursing home eight weeks after discharge, an increase in those persons going home, the potential savings in nursing home costs in Colorado could exceed $3 million annually. Potential savings from implementation of case management at hospital discharge were calculated using the number of estimated 1990 Colorado nursing home over 75 years of age. It was assumed 43 percent of these residents will pe admitted from hospitals, as found by the 1985 National Nursing Home Survey: (U.S. Department of Health and Human Services, 1987). The number of home days avoided were calculated by using "Incidence Rates and Probabilities by Length of Stay" (U.S. Department of Health and Human 118

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,., Services, 1987, p. 87). The Colorado per diem reimbursement rate for skilled nursing facilities and intermediate care facilities ($38.54 per day), was used to calculate the million dollar savings. Estimating costs of $500,000 for 20 case managers at an average salary of $25,000 per year, approximately one case manager could be assigned to two hospitals in the state and still net a savings of i' $3 million per year. Of course, this assumes that individuals would not require extensive in-home care services. This research has important implications for policymakers and third-party payers. Currently, Medicare reimbursement is not available for case management services after discharge. The data suggest significant savings in Medicare and ultimately in Medicaid funds, could be accrued if case management were reimbursed. Case managers could follow discharged patients to nursing homes. When the patient's health status stabilizes, the case manager could divert that person to a more independent, less costly environment, annually saving millions of dollars in Medicare and Medicaid payments. i'' Policies and Practices Precipitating the Research A number c;>f public policies and practices precipitated the need for case I management intervention. The combined growth in the elderly population, drastic increases in medical malpractice insurance costs, increased physician charges, and increasing labor and equipment costs led to escalating Medicare costs. In order to control the rising costs in the Medicare program, seven major laws were enacted from 1980 through 1987. Two of the legislative changes are of particular interest 119

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for this research: the Tax Equity and Fiscal Responsibility Act and the Social Security Amendments of 1983. In 1983, the Medicare "prospective payment" system, known as Diagnosis Related Groups (DRG's), was initiated as a result of federal legislation. Hospitals : , were reimbursed a fixed fee for the diagnosis instead of the number of hospital days. Prior to implementation of the Medicare prospective payment system (DRG's), hospitals received reimbursement for costs on a per diem basis, and, in many cases, care for patients waiting for nursing home placement or community services was reimbursed at the full Medicare hospital per diem rate. Even though the legislative changes for prospective payments reduced the number of inpatient hospital days by twenty-eight percent and reduced Medicare expenditures by $28.9 billion, the legislation has lead to some inappropriate use of health care services. Of major concern is the increase in referrals to nursing homes. Unless efforts to limit the supply of nursing home beds are linked to the concomitant efforts to ensure that community-based services are sufficient to meet the needs of this growing population, the impact of these cost containment measures may be detrimental to the elderly and may encour age the continuation of an inappropriate use of medical services (U.S. General Accounting Office, 1983, p.131). Hospital discharge planning services for the elderly could ensure the most appropriate and least costly care alternatives. With the advent of DRG's, the discharge process is increasingly important due to patient's shorter length of stay and frailty at :discharge. The consequences of ineffective discharge can be seen. 120

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The hospital discharge process is a critical component of the health care delivery system, influencing resource utilization and future public expenditures for care after discharge. Discharge planning goes beyond identifying services, resources and financial: support. It concerns the patient's participation in the plan ning, and his willingness to participate in the plan. Discharge plan ning becomes such a difficult process because it must also account for the discharge plan, the patient's medical condition, and the home situation, but also what the patient has already endured regarding their previous experiences with the health-care industry and their hospitalization (Feuer, 1989, p. 32). This research was designed to describe the critical point of hospital dis charge in orde'r to develop casual hypotheses and new options for moving patients to appropriate, lepst costly, least restrictive environments. The present research provides an initial database for examining the process and outcome of hospital discharge planning for elderly over age 75 with a special examination of housing placements. In this section, the main findings will be highlighted and discussed, and implications research and practice will be suggested. Demographic Characteristics Which Provoke Housing Changes Patients over age 75 admitted to hospitals in this research reflect the national demographic profiles of this age group on gender and marital status. Over two-thirds are female, and a high proportion are unmarried (especially among the women). Most came to the hospital from their own home and most were rated as in poor to moderate health at discharge. The high proportion who were unmarried were unlikely to have in-home family resources to serve as 24-hour caregivers during the convalescent period, and thus were at greater risk during the period after Linking the poor health and few natural "caregivers" in the home, 121

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it is understandable that an increasing proportion were discharged to more supportive housing environments than the housing from which they entered. Although these data are not surprising (indeed the "at risk" status of the population was a major reason for the project), they document precisely the number of housing moves which occur as a result of hospitalization. These figures suggest the need for discharge planners to be keenly aware of housing options and techniques for assessing elderly housing needs. The oldest members of the age 60 and older age group are those 85 and older. This cohort has a predominance of females. Nationally, two-thirds of the 85 and older age group are females, most of whom are widowed, with fewer economic resources and more health problems than men, and more than one-quarter living in institutions. In view of these critical gender differences, it is surprising that the existing literature does not consider gender a key variable in discussions of the oldest old (Mintz & Feinson, 1987, p. 48A). Although this research focused on the age 75 and over population, 62 percent were female. ; Public policies and long term care policies do not analyze gender differences. The results of this research indicate that gender differences are an important cOnsideration in the development of long term care policies. Older r;nen and women differ by socioeconomic factors (Moon, 1990) and health factors (Markides, 1990). Women live longer than men but experience more physical symptoms and report greater levels of disability and, therefore, higher rates of institutionalization (Markides, 1990). This research indicates that gender differences an important consideration for future research and public policies. Housing level at discharge was best predicted by housing level at admission along with age; health, and gender. The strength of the admission housing level as 122

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a predictor of discharge housing suggests strong continuity in housing placements. Of the persons who changed housing types between admission and discharge almost all were discharged to increasingly dependent housing. Although discharge planners identified housing referral or housing follow-up as a service their hospitals did not offer in a comprehensive manner, assistance with housing transitions appears to be a significant function which discharge planners are being asked to perform. The discharge planners recognize the need for the service and recognize that their hospitals are not offering it comprehen sively. Discharge planners identified a wide array of information needed to do their jobs, among which housing information (especially vacancy rates) was a focal point. Other information requested had direct bearing upon housing as well (e.g., funding options, new long-term care legislation). Discharge planners appear to be quite aware of the central role of housing assessment, information, and referral in discharge planning services even as they acknowledge the limitations of services provided by their hospitals. Issues in Measuring Housing Research requiring follow-up contacts with elderly would ideally provide for face-to-face contacts. Telephone interviews with this population are extremely difficult due to hearing problems. In addition, some of the housing environments do not provide ready telephone access so it was impossible to gain information directly from the patients (especially from patients in the more dependent housing levels). In the present study informants were used when the patient requested, when the 123

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patient was not competent to respond, or when telephone access was not available. Key informants appear to be a viable source of information about the patients, and perhaps should be used as a proxy for data from impaired elderly. It was, however, another source of variability and potential measurement error. Nonetheless; it might be considered as a separate supplementary source of ; i' information regarding hospital discharge practices. Data collection procedures should minimize reliance upon information which must be recalled. Data which require subjects to recall information is subject to distortions which may be particularly marked for elderly subjects. Although major events like hospital visits are likely to be accurately recalled, more frequent and less major :events may be subject to distortion (e.g., number of doctor visits}. Ideally, subjects would be asked to keep a daily log of events to track more accurately the desired behaviors. Clear, simple definitions of the event need to be provided (e.g., what constitutes a doctor's visit in a rehabilitation facility where staff are constantly .around? Who should be considered a doctor?}. A major problem with data requiring recall of details is that subjects may not have been of, or encoding well the details of their hospital stay. Many subjects talked about their hospital experience in vague, global rather than detailed specific terms. The satisfaction ratings were particularly problematic in this study because not all subjects could identify a "discharge planner". In many cases the subjects actually had not made contact with a person with that unique title during their hospital stays (i.e., a physician, nurse, or social worker may have planned the discharge}. In other cases the hospital stay was experienced as a blur of contacts 124

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with professionals who were hard to distinguish, and subjects responded with their rating of their overall satisfaction with the hospital stay. In other words, it was hard tor them to ideintity the discharge planning function, but even harder to identify the person with the title, and so they responded in inconsistent ways to the questions. Through the qualitative research, it became apparent that most patients do not see I a discharge planner (e.g., the discharge planning is usually a review of patient records). Therefore, the percentage of respondents who could not identify a "discharge planner" may not have had a direct personal encounter with a discharge planner. Most of the participating hospitals did not leave discharge planners on duty over the weekend. If a patient was admitted on Friday and discharged on the L following Sunday, most likely neither the patient nor the patient's record were seen by a discharge planner prior to their discharge. Hospitals must acknowledge the important role of discharge planning and offer it to all Medicare patients, not merely those who are admitted and discharged from 8 a.m. to 5 p.m. Monday through Friday. Discharge Planning: A Role in Transition Contrary tb the researchers' beliefs at the initiation of this project, discharge planning is an enormously complex process. Although formal discharge planning is mandated by federally funded programs, (e.g., Medicare), the mechanism through which the planning is to be accomplished is not mandated. Current practices are quite diverse. lr:J fact, in the course of this research, increased regulatory control over the process and documentation of discharge planning occurred. Thus, 125

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observations made in the course of this project may be limited to this period of policy transition. In the. description which follows, a careful distinction must be made between discharge pla.nning as a function (or role) which may be performed by a variety of professiona.ls; and formal administrative departments whose organizational core is "discharge planning." Discharge planning is performed by a variety of professionals including physicians, floor nurses, social service personnel, and persons trained specifically to .. do discharge planning. The amount of discharge planning which was done outside 10f formal discharge planning service departments was surprising. In some hospitals, physicians controlled the referrals to discharge planning staff. In others, discharge planning staff could make contact with patients on the floors of the hospital .without physician referral. Although assessments were required before discharge planning could be completed, social service or discharge planning personnel were not always involved in those assessments. No estimates of the percentage of patients who were assessed by social service or discharge planning staff were available. The organization of discharge planning service departments was one factor which appeared to influence services. During the course of this research, changes occurred in the administrative structure of several hospitals which influenced discharge planning departments. First, some hospitals were separating the discharge planning function from social services. This occurred in two ways: hiring nursing staff to provide discharge planning rather than social workers, and separating the departments administratively. The assumption that discharge planners are 126

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drawn only from the social work discipline was no longer valid. Nor was the assumption that discharge planners were well trained in community services and community systems valid any longer. Even when members of the discharge planning department were called in, they may have been relatively new to the task of providing comprehensive discharge services. However, it was evident that persons within 'discharge planning departments were highly motivated to provide services to patients, and were eager to obtain information relevant to that goal. The number of discharge planners varied by hospital; most hospitals had a combination of nurses and social workers providing discharge planning. Table 4.1 shows the breakdown of discharge planners by discipline for each of the five hospitals participating in the research. Another factor influencing discharge planning was the time constraints under which discharge planners must function. In almost all cases, discharge planners in this' study worked under time limitations. DRG's reduce the length of patient stays, thus limiting the time available to assess discharge needs and implement a Discharge planners need immediate access to a broad array of information, but in some cases lack the most simple resources of a desk, a phone, and a budget for. collecting and storing information needed in the course of their duties. Due to the. recency and constancy of administrative changes, social service and discharge planning departments in this research appeared to be functioning under less than ideal conditions. In one hospital the administrative hierarchy was not clear. The discharge planners reported they had no clear avenue to pursue 127

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Table 4.1. Discipline of Discharge Planners at Participating Hospitals. Total Number of Number of RN Number of Social Work HospiTal. Discharge Planners Discharge Planners Discharge Planners Presbyterian/ St. Luke's HospiTal 3 2 Mt. Airy Psychiatric HospiTal 5 0 5 St. Anthony's HospiTal North : 3 2 St. Anthony's HospiTal Central 9 3 6 Mercy HospiTal .. 4 _g_ 2 TOTAL 24 7 17 when policy was confusing or practices impeded. The effect on the discharge planners appeared to be a groWing sense of powerlessness to get the resources needed to do their job, lack of predictability about the presence and nature of their job, and a resultant demoralization. Clear signals of the lack of power experienced by discharge planners was their lack of territory (many lacked a desk or an office), communication tools (e.g., telephone), or a place to store informational resources. Other more subtle signals include hospitals' policies restraining discharge planners from contacting patients without physician referral, and frequent administrative shuffling. 128

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Effective discharge planning can be demonstrated to be cost-effective by reducing recidivism rates and expediting timely appropriate discharges. The costeffectiveness not be readily evident because the service is not directly reimbursable. Some departments have been able to justify the cost-effectiveness of their services by tracking recidivism rates, but at this point data collection to justify discharge .planning is unusual. Changing Models for Discharge Planning Administrators are concerned with containing health care cost as well as providing quality patient care, and have shifted organizational structures in some hospitals to meet those goals. Organizationally, discharge planning functions have , been structured in different ways. It is clear that the discharge planning function is a hospital-wide interdisciplinary process. The impact of these changes on the lives of older adults is unclear. The data in the present research were not sufficiently detailed to identify any relationship which may exist between organizational or administrative features of hospitals, and impact on patient care. It is possible that some of the variability observed among hospitals on the housing and recidivism rates may have been caused by policy or administrative differences. It is clear that no single profession could respond to the myriad of patient and family problems which exist at hospital discharge. A number of factors influence the outcomes of the discharge plan, however, hospitals rarely have control over these factors: the capacity of the caregiver to provide the support needed by the patient; the availability of housing options related to the patient's 129

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level of care' needs and eligibility; the availability of community services; adequate financial resources for the care or housing needed; and the ability of the patient to manage the health providers or caregivers. The complex nature of caring for older adults whq frequently have multiple chronic conditions precipitates the need for multidisciplinary teams of professionals involved in the hospital discharge planning process. After surveying hospitals in various cities, Reichelt and Newcomb {1980) described four basis models of discharge planning. In Model I a designated discharge planner has major responsibility tor ensuring the patient's posthospital continuity ot.care. The discharge planner was usually a nurse who acted as casefinder, consultant, and referral agent. In this model the discharge planner is relatively autonomous -selecting patients; assessing their needs; and working with family members, hospital staff, and representatives of community agencies to ensure that the patient's posthospital needs are met. In Model II the discharge planners and nursing staffs assume the major responsibility for the patient's continuity of care. Physicians and nurses caring for the patient assess the need for posthospital care and then are assisted by the discharge planner in arranging for needed services so that discharge planning is an integral part of. the patient care process. In Model Ill social workers are assigned to specific clinical units working with nurses on the unit to identify the patient's posthospital needs. Discharge planning activities are then divided between them on the basis of the type of care needed {e.g., home care or nursing home care). 130

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In Model IV physicians and nurses assume major responsibility for identify ing patients who need posthospital care. They then refer those patients to the social worker, who assumes responsibility for both physical and social needs (e.g., transportation, nursing home referral, consultation with patient and family members) (McNulty, 1988; Reichelt & Newcomb, 1980). In Model I the discharge planner is virtually autonomous; while in Models II, Ill, and IV, overall responsibility are assumed jointly by specified hospital staff members and action is divided or delegated. Model IV, the most traditional model, is used most frequently. The five hospitals participating in this research primarily used Model IV where the physicians and nurses assume major responsibility for identifying the patients who need posthospital care. In a recent teleconference on trends in discharge planning, the presidents of the two national associations, which represent the predominance of discharge planners in theU,S., described the importance of integrating hospital and communi ty services with case management (Birmingham & Butler, 1991). Oregon's success, with inqreasing numbers of long term care patients served and expending $20 million per year less than Colorado, is partially attributed to the use of case managers in conjunction with hospital discharge planners. Although no data is available to quantify the financial impact of the case management intervention in Oregon, the staggering savings of $20 million annually warrants a closer look at the discharge planning model. The model utilized by Oregon is similar to the model described by Simmons and White (1988). 131

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The roles of discharge planners and case managers differ. This role differentiation follows: The purpose of discharge planning is to assure continuity of patient care while ensuring the shortest possible inpatient stay. Its goal is to move the patient out of the acute setting swiftly and safely while assuring continuing care of the patient in the post-hospital care setting that appropriately extends the regimen of care received in the inpatient setting. The purpose of case management is much broader. Its use as a service delivery approach has been attached to a variety of goals for specific programs, including alternatives to institutionalization, to assure cost effec tive care, to provide access to comprehensive care, to coordinate services, and to improve functional capacity. One or more of these may be included as the purpose of hospital-based case management. (Simmons and White, 198'8, p. 222) The fu.nctions of a case manager and a discharge planner are very different. In a hospital setting, the discharge planner should plan the discharge. If the patient is currently, or will become a case management patient, the case manager may participate in the planning as a member of the interdisciplinary team. The hospital discharges patients to case management. However, the case management program can refer and accept patients from the hospital and provide care beyond the acute care of the hospital. Through the use of an interdisciplinary team in the hospital and the use of a case manager to follow patients after discharge, not only will the continuity of care for the patientF be preserved, but cost savings can occur by preventing hospital readmissions pr premature nursing home placements. As previously noted in this research, patients who are high-risk of institutional placement must be targeted. Case management services will not be cost-effective without targeting the patients who need post-hospital monitoring. This research suggests targeting older adults 132

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age 75 and older who are unmarried women, and have a health status which causes concern for their health. One function of exploratory research is to guide the development of efficient research methods. Recommendations for research methods and directions useful to discharge planning research are presented below. Research Strategies Working within the administrative structure of hospitals proved daunting in most cases. The ,project held tentative status within the hospital system because its main support came from the departmental rather than the administrative levels. Hospital research projects function better when there is strong administrative :: support to enforce data collection policies as well as to facilitate integration of the intervention into on-going service units. In this study, responsibility for research participation and. for support within the hospital fell to staff of social service and discharge departments which lacked authority to require professionals of other departments to participate. Strong administrative support of, and involvement in, the project would have facilitated interdepartmental problem-solving. Sampling Issues related to sampling from the population are often determined at the administrative level. For example, mechanisms for obtaining patient consent, and conditions under which consent is needed, are concerns with which administrators need to be involved. In this research, the procedures for tracking patients through the system needed to be established by, and monitored by, administrators. Hospital staff were sometimes reluctant to add to their job responsibilities the 133

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demands of t,his research, and ignored or denied requests to complete data collection A procedure needed to be developed to attach an abstract to each elderly person's chart so it could be part of the paperwork to be completed at discharge. However, patients entered the hospital through a variety of departments (e.g., admission and emergency room). It was difficult to ensure that each chart received the appropriate form. Furthermore, there needed to be a mechanism for receiving the completed forms so elderly patients who were discharged without completed abstracts could be identified and data could be included. It was evident from the total. number of abstracts collected that not all patients who met criteria for participation in the research were tracked by hospital staff. A total of 1,089 abstracts were collected by the hospitals for this research; 1,040 had sufficient information to include them in the study. Because the participating hospitals did not keep their medical records on Medicare patients accessible by age, it is not ,' possible to determine the actual percentage of relevant patients on whom information was provided. This lack of comprehensive data collection leaves open to question the representativeness of the sample. Due to differences in hospital procedures for attaching the abstract to the chart, data from the hospitals vary in representativeness of the targeted populations. Departments responded inconsis tently to the request for data since the social service staff had no authority to enforce compliance. Selective sampling is likely to have occurred across depart ments. It was. a threat to the validity of this study that inconsistent sampling occurred. Administrative support was needed to sanction the project, to help in identifying effective sampling procedures, and ensure project continuity. Despite 134

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the inconsistenc,es across hospitals and even within hospitals across departments, a sufficiently large number of data points were collected to assume that the data will provide a useful profile of admittees in the age 75 and older group. It is important to remember that selective sampling may have occurred, however. Measures This project relied upon a variety of professionals to complete the data abstract. No training could be administered due to the diversity of the people involved. Thus, the intended physical and mental health ratings had to be simplitied from the two' proposed ratings, and a simple functional health rating was used. This measure is extremely global, and there is no way to evaluate the reliability or '! validity of the measure. Recording biases may have occurred due to the diversity of the professionals recording the data. In order to collect valid, reliable data consistently, a limited number of people need to be involved in, and responsible for, data collection. Control over the data collection staff would make it possible to use psychometrically sound rating scales which require training (e.g., ratings from the OARS). At the two1 week follow-up and eight week follow-up, patients were asked to report the of doctor visits and hospital visits since discharge. The reliability of the doctor visit ,information is unclear, as patients were asked to make a retrospective rating which is known to be less than ideally reliable. Another problem with the reports of doctor visits was that patients had difficulty identifying which health care personnel qualified as doctors (e.g., podiatrists, chiropractors). Patients w,ere also asked to rate their satisfaction with their hospital dis charge planner. Many of the patients were unable to identify a person who served 135

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as discharge planner, and thus were not asked to make the rating. Many of the elderly reported their hospital experience in global ratings, but could not distinguish among spec!.fic functions served by specific people. Telephone contact made the large number of follow-up contacts possible. However, significant impediments were experienced in the process of gaining accurate information. Older persons often experienced hearing deficits which made telephone cqmmunication difficult. Some of the information requested (especially the ratings of satisfaction with discharge planning) was quite difficult to obtain due to the need to rely upon language which was unfamiliar to the population (e.g., discharge was often rephrased to describe the function), and due to the general confusion of many persons in recalling specific details of their hospital experience. ,I In general, the callers made a judgment as to the confidence with which the patients reported recalling a specific person; patients not recalling a discharge planner with. c:onfidence were not asked to make a satisfaction rating. Generally, the two callers had to spend far more time than had been predicted in order to obtain reliable information from elderly patients and infermants. Hearing difficulties a major impediment to the telephone interviews. In addition, many elderly person were more comfortable imbelishing their answers to the researc.hers' questions in a full description of their hospital experience. Analysis was conducted to determine whether patients assisted directly by the case manager differed on the outcome variable. The latter analysis was not planned originally, but as it became evident that the discharge mechanisms were too diverse to be affected by a single case manager, it was decided to have the case manager identify patients with whom she worked directly. She made these 136

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identifications after data were collected and entered by looking through the informa tion available on the abstract forms, and matching them with her date book and the case records .. This procedure may have produced an under-identification of patients with whom she had contact. Delays in the process of contracting with the five hospitals for their partici pation resulted in a shortened data collection period for the research. This neces sitated adjustments to the data collection periods in some hospitals, and required the case manager to divide time between two hospitals for a portion of the inter vention periods. These modifications did not compromise the intent of the multiple-baseline design, and the case manager's report was that the double assignments to hospitals was not an undue strain given the low rates of referrals and consultation received. In some cases, the liaison appointed from each hospital to coordinate the data collection .and intervention phase was less than enthusiastic about the project and gave it low priority. In those hospitals, data collection tended to be initiated slowly and intervention was perceived as not useful, unnecessary, or threatening (i.e., implied they, were not already doing an adequate job). The case manager for the project reported experiencing herself in an awkward position in some hospitals, as she was clearly discouraged from working with staff. Other liaisons worked hard to implement the project, but lacked administrative power to require other depart ments to participate in consistent data collection. Still others used the case manager appropriately, gratefully, and in a manner consistent with the intent of the research. 137

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The differences among the hospitals appeared to be due to numerous factors. Administrative structure appeared to be an important variable because departments .with strong administrative support for the research could control data collection procedures more adequately. Recent structural changes (e.g., moving discharge planning out of social services into a department of its own) were also perceived to interfere with staff's comfort dealing with additional tasks. (Even helpful tasks like involving the case manager to relieve their workload felt burden some when departmental structure was in transition). Personnel stability was also a factor bec"ause high turnover rates in discharge planning staff, especially man agement, led to tension and impatience with the demands of the research. In one case, the hospital liaison left the job before data collection began and the replace ment staff person was forced to implement the research data collection even while learning the basics of the job. Much responsibility for ensuring the case management and data collection fell to the hospital liaison, the case manager and the persons making the follow-up calls (who tracked the data). The two data collectors and case manager reported a constant sense of tenuousness about their position in the hospitals because of their perceptions that they were seen as "outsiders" who were creating unnecessary work for sorne .hospital personnel. Data collectors had no administrative backing to enforce cooperation from hospital personnel, and in contrast, were often required to defend to hospital administrators (the liaisons were sometimes helpful in facilitating acceptance). A major limitation of the research was the "outsider" status of the case. manager within the hospital environment. 138

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After data collection for the baseline phase was complete, the case manag-', er made contacfwith the discharge planning staff (who were affiliated with either the Social Services, Quality Assurance, or Discharge Planning Departments} to discuss the reseflrch and describe the range of services she could provide. This contact met with varying levels of receptivity and involvement by the discharge staff. In some hospitals the case manager was told there was no space to work in their department.(i.e., no telephone or desk}, and the case manager was encouraged to return ,to her agency until contacted by them with a referral or consultation. 4 In another hospital the case manager was given referrals for two weeks, but a new deparment became concerned about patient "informed consent" procedures and required research staff to leave the hospital until further notice. Once the consent procedure was clarified, the case manager was invited back on site, but the inter-Vention period was thus shortened at that hospital. The intervention arrangement which appeared to be most effective was direct referral from: social services or discharge planners (of any discipline}. A direct referral allowed the case manager to contact the patient or family on the floor of the hospital initiate an assessment at that time. However, intervention effect was limited when hospitals did not offer discharge planning services on weekends. Because health (even measured as globally as was done in this project} is a major factor influencing discharge planning, future research needs to use more precise, reliable measures. Diagnostic categories are not likely to be useful, ' because they do not always reflect degree of impairment. A functional assessment I tool would be ideal. The tool currently being developed by the Health Care 139

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Financing Administration for systematic use in hospital settings may provide an ideal source of functional health data. The areas to be assessed for purposes of housing placement include ambulation, Activities of Daily Living competence (e.g., bathing and skills), Instrumental Activities of Daily Living competence (e.g., check writing and telephone use), and cognitive competence. In addition to health ratings, information is needed regarding finances, social support, caregiving support, and access to transportation. The uniform needs assessment initiative was mandated by Section 9305(h) of the 1986 Omnibus Reconciliation Act to evaluate individual patient needs, functional ability, and care required to assist the patient with their incapacities. The instrument designed for the use of discharge planners, home health workers, health care providers, and nursing facilities. Still in draft form, this standardized assessment may be the first step toward improved assessments and referrals at discharge. Discharge planning, in order to meet the needs of the older patients, must incorporate an interdisciplinary team of the patient, case manager, the discharge planner and others (family, physician, nutritionist, occupational therapist, physical therapist, speech therapist, etc.). Discussion of Future Research Certainly the complexity of the discharge process warrants attention as the primary focus in research, and depending upon the findings, may need to be incorporated into research designs as an independent variable. It appears that characteristics of the person planning the discharge might affect the process (e.g., the amount of patient and family involvement, types of housing considered, and 140

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factors placement). For example, do physicians refer different types of patients to each level of housing as compared to discharge planners? Do physi cians refer to discharge planners only a unique subset of all elderly discharges? Which geographic, financial, familial, and health-related factors influence such a decision? I of the patient need to be measured carefully. As described above, functional health measures need to be applied reliably to patients to identify I the impact of health on housing decisions. Several practical considerations in choosing housing determine other kinds of information needed (e.g., finances, etc., as described abo,ve}. Characteristics of the hospital may also affect the discharge process. Administrative structure, location, size, specialty services (e.g., psychiatry), population characteristics, policy, and staffing are all factors which may influence planning. Finally, community characteristics should be examined as factors influencing discharge planning. Housing availability, location, population characteristics, transportation availability, availability of in-home services, and even community values, mores, and awareness are likely to influence housing placements from hospitals. Of particular importance to health care planners and health care funders are the discharge practices related to long-term care. Conditions under which persons are referred to care, and the periods they are likely to stay in long-term care are of clear interest. The present research suggests that the development of services to evaluate housing appropriateness in the weeks following _hospital 141

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discharge may be one mechanism to reduce length of stay in nursing homes. However, services have no funding source at present. Follow-up monitoring services or case management are often beyond the scope of hospital services and often do not clearly belong to any other community agency. Although they may be seen as cosfeffective and preventive of premature institutionalization, there is no current source of reimbursement for the case management service. More definitive research nee8s to be developed before: (1) establishing formal programs and changing service networks, or (2) revising federal and state reimbursement policies. I Researching and exploring options to provide the care needed by older adults and their families will become increasingly important as the demographics shift. A recent public and private sector coalition called "Alliance for Aging Research" criticized the federal governments' miniscule investment in research for the aging. Their report was consistent with the findings in this research. Reducing dependency by helping older americans maintain their indepen dence can help older americans, their families, the federal and state govern ments, and private insurers control health costs. It is estimated that each one month reduction in the period of dependency for older americans would save $5 billion in health care and custodial costs ... aging research can an effective future cost-containment measure by making individuals independent longer. (Alliance for Aging Research, 1990, pp. 8-9) ,, Future research could evaluate the impact of public policies on the older population and evaluate research interventions which slow the demand for long term care. Discussion of Future Practices The results of this quantitive and qualitative research offered new insights into the hospital discharge planning process which evolved after the implementation 142

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of the federal Medicare DRG prospective reimbursement policy. Proposed policy reforms to the discharge planning process and simultaneously link patients to more appropriate, less costly service options must be addressed. lmplementation of modified policies will be directed toward the older (75 and older) Medicare patients and their families by reducing dependency and increasing autonomy appropriate to the physical and mental functioning of the patients. Millions of dollars in federal and state funding may be saved if precise policy options are generated from this timely research. This research intended to build upon the cost-saving policies of prospective reimbursement but test an intervention which could prevent cost-shifting by inappropriate placement of patients in expensive environments because other services are not available to or utilized by the hospital discharge planners. This exploratory research suggested that using a case management approach after ,hospital discharge could result in a 21 percent decrease in the number of elderiy patients remaining in nursing homes eight weeks after discharge, which is an annual savings of $3 million in Colorado's nursing home costs. If Colorado has one percent of the nation's older residents the projected savings in nursing hone costs could be astronomical. To take this preliminary research to a national demonstration project would require a Health Care Financing Administration pilot across a. number of diverse states. Subsequent research would need to take into consideration the methodological issues identified earlier in this chapter. Discussions with Health Care Financing Administration staff about this preliminary research indicate an interest in pursuing the idea. Further development of a 143

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proposal and cost data are required. The likelihood of funding for such a pilot will depend upon competing research needs at the U.S. Department of Health and Human Services, the federal budget, and the extent to which this research would lead to greater cost-savings than other competing proposals. 144

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I' S3XICN3dd'1f

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APPENDIX A: DISCHARGE ABSTRACT Discharge Date:-----------Patient Name:-------------Address at Admission:----------Gender: 'Male_ Female_ Age_ Marital Status: Married_ 1 Separated_ Divorced_ Widowed_ Never Married_ Functional Health Rating: 1 Very good (no significant illness or disease) 2 Moderate (minor illness or disease) 3 Poor (significant illness or diseaSe) Discharge Address:-----------Discharge phone number: ---------Name of Facility, if applicable: _______ Do not write below this line Two Week.Follow-Up Satisfaction Rating: # Hospital Visits in first week post-discharge __ # Physician VIsits in first week post-discharge NOTE: If respondent plans to move soon, ask for name of new residence and phone number: ____________________ Date of Effecti.ve Move: ____ Eight Week Follow-Up Satisfaction Rating:_ # Hospital Visits since Discharge Date Above: __ # Physician Visits since Discharge Date Above: #Housing Changes Which Have Occurred Since Discharge Date Above:_ Housing Level at Present Time __ 146

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APPENDIX B: MEDICARE PATIENT AUTHORIZATION FOR RELEASE OF INFORMATION Dear Medicare .Patient: ______ Hospital has been selected to participate in a special project regarding follow-up on Medicare patients after discharge from the hospital. Participation in this study is voluntary and would involve authorizing the hospital to release biographical and health status information relating to you at the time of discharge from the hospital. It would also involve a follow-up call to you two weeks and again in two months after discharge from the hospital. We appreciate your participation in this project and ask that it you are interested, please sign the attached form. If you have any questions regarding this project feel free to call at ------Patient Family Counselor/Discharge Planning Departments. I elect to partic,ipate in the research project regarding follow-up on Medicare patients after discharge and authorize Hospital to release biographical and health status information on me at the time of discharge from the hospital. I also will allow a follow-up call two weeks and again in two months after discharge from the hospital. I understand participation in this project is voluntary. Signature of Pat1ent Date Witness of Signature Date 147

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APPENDIX C: TELEPHONE SCRIPT FOR TWO WEEK FOLLOW-UP Hello, I am (Name) and I am calling for Hospital. We are collecting information so we can learn more about what happens to people when they le'ave the hospital. At this time, I would like to ask you a couple of questions concerning the assistance you received when you were discharged from hospital on (date) and about your health since you were discharged. When you were preparing to leave the hospital, do you recall having a nurse or social worker assist you in planning your health needs? (If answer is yes, ask question concerning satisfaction rating part (a) below. If no, ask question concerning in having assistance part (b) below.) a. How would you rate on a scale from 1-7 your satisfaction with the help you received from this person when you were discharged from -----hospital? b. Woulq it have been helpful for you to have assistance with your health needs upon leaving the hospital? Yes__ No __ Did you the first week after you were discharged from the hospital? If so, how many visits did you have? __ Were you admitted to a hospital the first week after you were discharged from the hospital? If so, how many admissions did you have? __ In approximately six weeks, I will be calling you again to follow-up on your progress-will I be able to reach you at this phone number? Yes__ No __ (If no, ask for: a new phone number.} I Thank you fer your assistance. 148

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APPENDIX D: TELEPHONE SCRIPT FOR EIGHT WEEK FOLLOW-UP Hello, I am (Name) and I am calling for Hospital. We are collecting information so we can learn more about what happens to people when they leave::the hospital. At this time, I wo'uld like to ask you a couple of questions concerning the assistance you received when you were discharged from hospital on (date) and about your health since you were discharged. 1. When you were preparing to leave the hospital, do you recall having a nurse or social worker assist you in planning your health needs? (If answer is yes, ask question concerning satisfaction rating part (a) below. If no, ask question concerning helpfulness in having assistance part (b) below.) a. How would you rate on a scale from 1-7 your satisfaction with the help you received from this person when you were discharged from hospital? 1 = indicates very dissatisfied 7 = indicates very satisfied b. Would it have been helpful for you to have assistance with your health needs upon leaving the hospital? Yes_ No_ 2. Did you see a physician the first week after you were discharged from the hospital? If so, how many visits did you have? __ 3. Were you admitted to a hospital the first week after you were discharged from the hospital? If so, how many admissions did you have? __ 4. Have you experienced any changes in your living arrangements in the past eight weeks? Yes_ No_ (If yes, what were these changes?} In approximately six weeks, I will be calling you again to follow-up on your progress. Will I be able to reach you at this phone number? Yes__ No __ (If no, ask for a :nE)w phone number.) Thank you for your assistance. 149

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APPENDIX E: MAP OF PARTICiPATING HOSPITALS ' ;.. I I \ .J '\\ ' ... ...... -,,._ 1 St. Anthony North 2. St. Anthony Central 3. Pres./St. Luke's 4. Mercy 5. Mt. Airy \Y --t-;----------' Mol ........ 150

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I APPENDIX F: LONG TERM CARE HOUSING CONTiNUUM I CONTINUUM COMPONENTS I INDEPENDENT UWm CONGREGATEHOUSNG ASSISTED UVING NURSING HOME ,. :lN CoVIIrs a broad range of housing Provides a living arrangement which Provides a Jiving arrangement which Provides a living arrangement which options for older persons who are Integrates sheHer and services for Integrates she Her and services for those Integrates sheHer wHh medical functionally and socially Independent those older persons who am frail, older persons who am frail older pernursing psychosocial and rehab. most of the time chronically Ill or socially lsolatad but sons who am functionally and/or socially services for persons who require 24 who do not need 24 hr.aupervislon impeirad and need 24 hr. supervllion hr. nursing supervision A -8--C-.I). Age Segregated Buildings A Pius A and B Plus A, B and C Plus Environmental Security ,, Msals Assistance with activities of Dally Uv 24-Hours Nursing Supervision Administrator may coordinile servic Transportation ing es for residents (le., transportation, Housekeeping Assistance Medications Monitoring housokeeplng, etc.) Case management 24-Hour Protective Oversight Creating opportunities for socializa. lion I RESIDENT ASSESSMENT CRITERIA L Capable of moving about lndeL Capable of moving about lndeL Mobile but may require escort L May require assistance with pendently. Able to seek and pendently. Able to seek and assistance due to confusion, poor transfer from bed, chair, toilet follow directions. Able to follow diroctions. Able to evacuvision, weakness or poor motiva-OR evacul!l& Independently in ar ate Independently In emergency lion IL Roquires transfer and transport emergency OR OR assistance. Requires turning and OR. IL Ambulatory with cane/Walker. IL Requires occasional assistance to posHioning In bed and whool IL Ambulatory with canetwalker. Independent with wheelchair but move about but usually indepenchair Independent with wheelChair but needs help in an emergency dent needs help in an emergency L Able to prepare own meals. Eats L Able to prepare own meals. Ells L May require assistance getting to L May be unable to unwilling to go meals without assistance ,. meals without assistance dining room and/or requires to dining room. May be depenmal assistance such as opening dent on staff for eatlngneedlng IL Minimum of at least one meal a cartons or other packages, cutting noads day available food or preparing trays OR IL Totally dependent on staff for nourishment (includes reminders '' to llallllldlor feoding L Independent in 1111 care L Independent In all care Including L May require assistance with L May be dependent on staff for all bathing and personal laundry bathing and personal laundry bathing or hygiene personal hygiene OR IL May require assistance, Initiation structure or reminders. Resident completes the task ,, 'NG L Independent in performing L Independent in performing L Housekueping and laundry urvices L Housekeeping and laundry housekeeping functions housekooping functions (Includes provided 1111rvlces provided (Includes making bad, vaeuummaking bed, vacuuming, cleaning lng, cleaning and laundry) and laundry) OR IL May need assistance wHh heavy housekeeping, vacuuming, laun-dry and changing linens L Independent and dresses appro L Independent and dressos appro-L May require occasional assistance L May be dependent on staff for priately priately with shoe laces, zippers, otc., and dressing or mad leal appliances or garments ' OR IL May require reminders, lnltil!lion or motimion. Resident complells the task L Independent and completely L Independent and complataly con-L Same as Independent Living L May have problem with inconti continent llntnt OR nenco colostomy, catheter and OR OR IL May have occasional problom with require assi&tance IL May have incontinence IL May have Incontinence lncontlMnce colostomy or catheter OR colostomy or clllheter but lnd&colostomy or clllhlter but lndeand may require assistance in IL May be dependent and unable to pendent In caring for uH pendent in caring for soH through caring for suH through proper uao communicate needs through proper IISI of materi-. proper LIS8 of materilllslsupplles of materials/supplies alslsupplles

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PENDilt F: LONG TERM CARE HOUSING CONTINUUM (Cant.J rAL rus I RESIDENT ASSESSMENT CRITERIA I INDEPENDENT UVING COOGREGATE HOUSING ASSISTED UVING NURSING HOME L Responsible far self edmlnlstra lion of all medications L Oriented to perscln, pla!:e and time AND IL Memory Is intact but has occa sional fargeHulness without consistent pattern of memory lass AND IlL Able to reason, plan and organize daily IIVBnls. Mental capa bllity to identify environmental needs and meet them L Responsible for self adminlstra lion of all medications L Oriented to person, place and time AND L Able to self-administer medica tions. Facility staff may remind and monitor the actual process OR IL May arrange for family or home health agency to establish a medi cation administration system. Staff may remind and monitor OR Ill Facilities staffed by RNs and LPNs can administer medications to rasi dents L May require occasional directions or guidance In getting from place to place L Medications administered by licensed personnel L Judgments may be poor and the resident may not attempt tasks which are not within capacities IL Memory is Intact but has acca sionalforgeHulness without con IL sislent pattern of memory loss OR May have difficuity with occasional IL confusion which may result in anxi ety, social withdrawal or depres-OR May require strong orientation and reminder program. May need guidance in getting from place to place AND IlL Able to reason, plan and organize dally events. Mental capability to Identify environmental needs and meet them sion OR OR IlL Orientation to time or placs or per-IlL Disoriented to time, piiiCS and son may be minimally impaired person OR IV. Memory is severely Impaired. Usually unable to follow direc tions L Deals appropriately wHh emo lions and uses available resources to cope with inner stress AND IL Dlllls approprilllely with othor rnldenta and IIIII L Deals appropriately with emo tions and uses available resourc es to cope with inner stress AND IL Deals appropriately with ather rnldtnta and IIIII L May require periodic Intervention from staff to facilitate expression of feelings In order to cope wHh inner stress AND L May require regular Intervention from staff to facilitate expression of feelings and to deal with peri-, odic outbursts of anxiety or agi llltlon AND IlL May require periodic Intervention from staff to facilitate expression of feelings in order to cope with inner sti'ISS AND IV. May require periodic Intervention from staff to msolw conflicts with other in order to cope wHh sHullllanal stress l. IL May periodic lnltlmntlon from staff ta resolva canllicts with ather in order to cope with situational stress ltlnce A D L s may be coordinated through H.ome Haalth Services ova crlteri should be considered "e889esment guidelines" !hill will help to assure the most approprillle placements OR IL Maximum staff Interventions Is requimd to manage behavior. Resident may be a physical dan ger to self or others OR IlL Expectations are unrealistic and approach to staff is uncooperative 1rd "ass+t mea" as it is used in this instrument may be wrbal or physical ld living mes may seek certillclllion to be 111 Cere Facility (A C F) Approved A C F clients must meat the P R 0 screen far nursing home placement 1: Colon Aesoclatlan of Home and Servlcss the Aging, Denver, Colal'lldo, Nov. 1986. 152

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APPENDIX G: EVALUATION OF BREADTH OF SERVICES AVAILABLE TO MEDICARE PATIENTS OVER AGE 75 DISCHARGED FROM THIS HOSPITAL. Note to Discharge Planners: This is NOT an assessment of your personal compe tence to meet P?tient needs. Rather, it is an assessment of the breadth of services provided by this.particular hospital. Please rate your confidence in this hospital's ability to provide the following discharge services to frail elderly: Immediate Housing Referral Services: I Our Hospital Does Not Attempt to Provide This Service 1 ......... .1 ......... ./ ......... ./ ......... .1 ......... .1 Our Hospital Offers Comprehensive Services in this Area Housing Referral Services 2 Months After Discharge: Our Hospital Does Not Attempt to Provide This Service Mental Health Referral Services: Our Hospital Does Not Attempt to Provide This Service / ......... .1 ......... ./ ......... .1 ......... .1 ......... .1 Our Hospital Offers Comprehensive Services in this Area / ......... .! ...... ... ./ ......... ./ ......... .! ...... ... ./ Our Hospital Offers Comprehensive Services in this Area Home Health Care Services or Referral Services: Our Hospital Does Not Attempt to Provide This Service Family Counseling Referral Services: Our Hospital Does Not Attempt to Provide This Service Other Human Services Referrals: / ......... ./ ......... ./ ......... ./ ......... ./ ......... ./ Our Hospital Offers Comprehensive Services in this Area ........ ./ ......... ./ ......... ./ ........ .! ......... ./ Our Hospital Offers Comprehensive Services in this Area (e.g., home-delivered meals, transportation, etc.) Our Hospital Does Not Attempt to Provide This Service 1 ......... .1 ....... .1 ......... .1 ......... .1 ......... .1 Our Hospital Offers Comprehensive Services in this Area 153

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BIBLIOGRAPHY Abramowitz, M. (1987, May 15). Putting Medicare in private hands. The Washington Post, p. HI. Alliance for Aging Research. (1990). The research gap: The need for boosting research to achieve independence for older Americans, Washington, DC: Author. Ambrose, J. (Ed.). (1990, October 24). Health cuts that don't kill. Rocky Mountain News,. Denver, CO, p. 52. American Hospital Association. (1984). Guidelines for discharge planning. Chicago, Illinois. (Catalog No. 0041 070.15M-6/84-4. 0899) Birmingham, J., & Butler, S. (1991, March 13). Teleconference on Trends in discharge planning: Integrating hospital and community services. Sponsored by UCLA Long Term Care Resource Center, Los Angeles, CA. Blumenfield, S., & Rosenberg, G. (1988). Towards a network of social health services: Redefining discharge planning and expanding the social work domf,lin, Social Work in Health Care, New York: Haworth Press, Inc., I (4), 31-48. Boone, C.R., (1987). The impact of early and comprehensive social work service's on length of stay. Social Work in Health Care. New York: Haworth Press, I (1 ). Bovbjerg, R.R., & Holahan, J. (1982). Medicaid in the Reagan era: Federal policy and state choices, Washington, DC: The Urban Institute. Branch, L;G., & Jette, A.M. (1982, December). A prospective study of long-term care institutionalization among the aged. American Journal of Public Health. Washington, DC: American Public Health Association, 72 (12), 1373-1379. Brock, A.M., & O'Sullivan, P. (1985). A study to determine what variables predict of elderly people. Journal of Advanced Nursing. Oxford, Englanq: Blackwell Scientific Publications, Ltd.,1Q (6), 533-537. Brookings Institution. (1989). Medicaid spend-down in nursing homes. Draft unpuqlished study. Washington, DC. Brown, W.P., & Olson, L. Katz. Eds. (1983). Aging and public policy: The politics of growing old in America. Westport, Connecticut: Greenwood Press. Califano, J.A., Jr. (1986). America's health care revolution: Who lives? Who dies? who pays? New York: Random House .... _....., ______

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Callahan, J.J., J'r., & Wallack, S.S. Eds. (1981). Reforming the long-term care system. Lexington, Massachusetts: Lexington Books. Caroll, N.V., & Erwin, W.G. (1987, December). Patient shifting as a response to Medicare prospective payment. Medical Care. Philadelphia, Pennsylvania: J.B. Lippincott Company, 25, 1161-67. ,. Christensen, L.B. (1991 ). Experimental methodology. Needham Heights, Massachusetts: Allyn and Bacon. Coe, M.F., & Wilkinson, A.M. (1987, October). Dependency at discharge: The correlation between observed ratings and chart ratings. The Gerontologist. Washington, DC: The Gerontological Society of America, 27, Special Issue. Coe, M.F., Wilkinson, A., & Patterson, P. (1986). Final report on the dependency at discharge. Beverton, Oregon: Northwest Oregon Health Systems. Cohen, M.A., Tell, E.J., & Wallack, S.S. (1986). Client-related risk factors of nursing nome entry among elderly adults. Journal of Gerontology. Office of Research and Demonstrations, Washington D.C.: Gerontological Society of (6), 785-792. Coile, R.C., Jr. (1987). Overview: Environmental forces and trends. Managing the Continuum of Care. In C.E. Shwick & L.J. Weiss. (Eds.). Rockville, Maryland: Aspen Publishing, Inc., pp. 11-21. Congdon, J. (1989). Managing the incongruities: An analysis of hospital discharge in the elderly. Unpublished paper. Denver, Colorado: University of Colorado Health Sciences Center. '. Congressional Quarterly Almanac. (1983). Major changes made in Medicare program. 98 Gong. 2 sess., Washington, DC. 39, 391-394. Continuing Care. Dying patients shift to nursing homes. Waco, TX: Stevens Publishing Corporation, .. (4). Cotterill, P.G. (1986). The relationship between cost and case mix: An initial test of a DRG-based case mix index tor skilled nursing facilities. Health Care Financing Review. 7(75). Coulton, C.J. (1988). Prospective payment requires increased attention to quality of post-hospital care. Social Work in Health Care. New York: Haworth Press, ll (4), 19-30. 155

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