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Organizational and managerial determinates of tribal diabetes program performance

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Title:
Organizational and managerial determinates of tribal diabetes program performance
Creator:
Noe, Timothy David
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English
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xvii, 264 leaves : ; 28 cm

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Subjects / Keywords:
Indians of North America -- Health and hygiene ( lcsh )
Public health -- Evaluation -- United States ( lcsh )
Indians of North America -- Diseases ( lcsh )
Diabetes -- United States ( lcsh )
Diabetes ( fast )
Indians of North America -- Diseases ( fast )
Indians of North America -- Health and hygiene ( fast )
Public health -- Evaluation ( fast )
United States ( fast )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

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Bibliography:
Includes bibliographical references (leaves 250-264).
General Note:
School of Public Affairs
Statement of Responsibility:
by Timothy David Noe.

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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:
463452565 ( OCLC )
ocn463452565
Classification:
LD1193.P86 2009d N63 ( lcc )

Full Text
ORGANIZATIONAL AND MANAGERIAL DETERMINANTS OF TRIBAL
DIABETES PROGRAM PERFORMANCE
by
Timothy David Noe
B.A., Carson Newman College, 1987
M.Div., Southern Baptist Theological Seminary, 1995
A thesis submitted to the
University of Colorado Denver
in partial fulfillment
of the requirements of the degree of
Doctor of Philosophy
Public Affairs
2009


This thesis for the Doctor of Philosophy
degree by
Timothy David Noe
has been approved
by
Paul Teske

Date
William Henderson


Noe, Timothy D. (Ph.D. Public Affairs)
Organizational and Managerial Determinants of Tribal Diabetes Program
Performance
Thesis directed by Professor Linda deLeon
ABSTRACT
The health status of American Indians and Alaska Natives (AI/ANs) continues to be
worse than any other group in the U.S. The extent of the problem of diabetes
among AI/ANs is staggering with some of the highest rates of diabetes in the world
found in American Indian communities. Additionally, cardiovascular disease is
now the leading cause of death among AI/ANs, and the high and rising mortality
rate of cardiovascular disease has been closely associated with diabetes.
Consequently, the effective management of tribal health programs, especially those
focusing on diabetes and its comorbidities, is extremely important to the health
status of this unique population. Based on the principles of the Competing Values
Framework (CVF) and indigenous self-determination theory, this thesis investigates
the relationship between organizational and managerial characteristics and diabetes
program outcomes. Using primary, cross-sectional organizational survey data and
program and clinical outcomes, this study examines the predictors of tribal diabetes
program performance using a combination of multiple linear regression and


multilevel, mixed model regression. The results indicate that high scores among
organizations on the CVF organizational effectiveness measures do not predict
diabetes program outcomes (recruitment and retention), nor do they predict
successful knowledge, lifestyle, and clinical indicator outcomes among diabetes
program participants. Results also indicate that the exercise of indigenous self-
determination related to diabetes program management does not predict successful
program outcomes, nor does it predict successful lifestyle and clinical outcomes.
However, the exercise of self-determination was shown to predict successful
knowledge outcomes (general diabetes knowledge and health literacy) among
program participants. Potential explanations regarding the lack of support for the
study hypotheses include: change scores on knowledge, lifestyle, and clinical
outcomes were insufficient to determine variables predictive of those outcomes;
unmeasured factors may have influenced the potential relationship between CVF
variables and the performance measures, such as socioeconomic conditions,
psychosocial factors, lack of family support, and cultural barriers; lack of
administrative record data to support the subjective perceptions of staff respondents;
and challenges faced by tribes in exercising self-determination, such as inadequate
funding and recruitment and retention of professional health care staff in isolated,
rural reservation areas.


This abstract accurately represents the content of the candidates thesis. I
recommend its publication.
Signed
Linda deLeon


ACKNOWLEDGEMENT
The completion of this dissertation would not have been possible without the
assistance and support of the Special Diabetes Program for Indians grantees and
Coordinating Center staff and their tireless work in collecting, entering, and
assembling of the data and datasets. I especially want to thank Luohua Jiang for
assistance with the datasets and statistics.
Also, it is from my employment at the Centers for American Indian and
Alaska Native Health (CAIANH) that I have learned about health research with
American Indians and Alaska Natives and have gained an appreciation for all those
who are committed to research with this special population. I am particularly
indebted to Dr. Spero Manson, Distinguished Professor and Head of the CAIANH,
and his guidance through the years with various projects and his guidance, direction,
and support of this research.
I would also like to express my sincere gratitude for my dissertation
committee. Spero Manson, William Henderson, Donald Klingner, Paul Teske, and
chairperson Linda DeLeon. All of these members provided guidance and support
and significant commitments of time for this dissertation. I especially want to
express sincere appreciation for William Henderson and his tireless guidance and
assistance on statistical issues.


Finally, I want to express utmost gratitude for my wife, Shannon, for
pushing me to pursue a Ph.D. and providing her support and encouragement
throughout the process.


TABLE OF CONTENTS
Figures............................................................xii
Tables.............................................................xiii
CHAPTER
1. INTRODUCTION..................................................1
Current Situation in Health Care Environment..............2
The Unique Context of American Indian and Alaska Native
Health Care...............................................3
Purpose/Research Questions................................7
Thesis Outline............................................8
2. LITERATURE REVIEW.............................................9
Organizational Effectiveness..............................9
Organizational Effectiveness Models that have been Applied
to the Health Care Setting...............................15
The Competing Values Measurement Model of
Organizational Effectiveness.............................28
Organizational and Managerial Determinants of Quality of
Health Care..............................................33
Organizational and Managerial Determinants of Diabetes
Care Performance.........................................35
viii
Theoretical Framework
36


Rationale for Using the Competing Values Framework
to Examine Tribal Health Care Organizations..............36
Limitations of the Competing Values Framework............38
Self-Determination Theory................................40
Diabetes Care Performance................................44
3. METHODOLOGY....................................................51
Study Design................................................51
Research Questions and Hypotheses...........................52
Study Population/Sample.....................................55
Organizational Survey Respondents...........................56
Domains of Measurement......................................58
Independent Variables....................................58
Dependent Variables......................................61
Covariates...............................................65
Data Collection Procedures for the Organizational Survey....65
Data Collection Procedures for the SDPI Participant
Baseline, Follow-Up and Annual Assessment of Core Elements.67
Validity, Reliability and Limitations.......................69
Data Analysis...............................................71
Inferential Statistics...................................71
Human Subjects Protection................................77
4. RESULTS........................................................78
IX


Sample Characteristics........................................78
SDPI, Demonstration Project Grantee Organizations.........78
Organizational Survey Respondent Characteristics..........82
SDPI Program Participant Characteristics..................91
Survey Characteristics.......................................100
Variable Characteristics.....................................106
Hypothesis Testing...........................................125
Hypothesis la............................................125
Hypothesis lb............................................130
Hypothesis lc............................................135
Hypothesis Id............................................144
Hypothesis 2a............................................171
Hypothesis 2b............................................174
Hypothesis 2c............................................177
Hypothesis 2d............................................183
5. DISCUSSION AND CONCLUSIONS......................................206
Higher organizational effectiveness scores will predict
better diabetes program performance..........................206
Exercising self-determination will predict better
diabetes program performance.................................219
Strengths and Limitations of the Study.......................224
x


Significant Contributions.............................224
Limitations...........................................225
Implications for Future Research......................227
APPENDIX ............................................................233
A. Organizational Survey.......................................234
B. Brief Description of Special Diabetes Program for Indians,
Competitive Grant Program....................................240
REFERENCES...........................................................250
xi


LIST OF FIGURES
Figure
2.1 The Competing Values Framework......................................20
2.2 Example Organizational Effectiveness Profile........................32
3.1 Analytical Framework for Inferential Analyses.......................73
xii


LIST OF TABLES
Table
2.1 Variables of the Competing Values Framework and Supporting
Literature...............................................................24
2.2 DQIP Performance Indicators and Comparable IHS Measures...................47
3.1 Independent Variables, Survey Items.......................................60
3.2 Special Diabetes Program for Indians, Competitive Grant
Program, Outcomes by Program Type........................................64
4.1 Organization Type.........................................................81
4.2 DP Organizational Characteristics.........................................82
4.3 CVD Organizational Characteristics........................................83
4.4 Number of Organizational Respondents per Site.............................84
4.5 DP Organizational Survey Respondent Characteristic:
Role in Organization.....................................................85
4.6 CVD Organizational Survey Respondent Characteristic:
Role in Organization.....................................................86
4.7 DP Organizational Survey Respondent Characteristic:
Time in Current Position.................................................87
4.8 CVD Organizational Survey Respondent Characteristic:
Time in Current Position.................................................88
4.9 DP Organizational Survey Respondent Characteristic:
How Long Employed at Organization........................................89
4.10 CVD Organizational Survey Respondent Characteristics: How Long
Employed at Organization.................................................90
xiii


4.11 DP Organizational Survey Respondent Characteristics: Gender................90
4.12 CVD Organizational Survey Respondent Characteristics: Gender...............91
4.13 DP Organizational Survey Respondent Characteristics: Age...................91
4.14 CVD Organizational Survey Respondent Characteristics: Age..................92
4.15 DP SDPI Program Participant Characteristics: Marital Status................95
4.16 CVD SDPI Program Participant Characteristics: Marital Status...............95
4.17 DP SDPI Program Participant Characteristics: Job Status....................96
4.18 CVD SDPI Program Participant Characteristics: Job Status...................97
4.19 DP SDPI Program Participant Characteristics: Gender........................97
4.20 CVD SDPI Program Participant Characteristics: Gender.......................98
4.21 DP SDPI Program Participant Characteristics: Age...........................98
4.22 CVD SDPI Program Participant Characteristics: Age..........................99
4.23 DP SDPI Program Participant Characteristics: Education Status..............99
4.24 CVD SDPI Program Participant Characteristics: Education Status............100
4.25 DP SDPI Program Participant Characteristics:
Annual Household Income...................................................100
4.26 CVD SDPI Program Participant Characteristics:
Annual Household Income...................................................101
4.27 Factor Loadings for the Rotated Factors...................................102
4.28 Means, Standard Deviations and Range for Independent Variables: DP..109
xiv


4.29 Means, Standard Deviations and Range for Independent Variables:
CVD.................................................................110
4.30 Means, Standard Deviations and Range for Covariates: DP.............110
4.31 Means, Standard Deviations and Range for Covariates: CVD............Ill
4.32 Means, Standard Deviations and Range for Dependent Variables:
DP Program Outcomes.................................................Ill
4.33 Means, Standard Deviations and Range for Dependent Variables:
CVD Program Outcomes................................................112
4.34 Means, Standard Deviations and Range for Dependent Variables:
DP Knowledge Outcomes...............................................112
4.35 Means, Standard Deviations and Range for Dependent Variables:
CVD Knowledge Outcomes..............................................113
4.36 Means, Standard Deviations and Range for Dependent Variables:
DP Lifestyle Outcomes...............................................114
4.37 Means, Standard Deviations and Range for Dependent Variables:
CVD Lifestyle Outcomes..............................................115
4.38 Means, Standard Deviations and Range for Dependent Variables:
DP Clinical Outcomes................................................116
4.39 Means, Standard Deviations and Range for Dependent Variables:
CVD Clinical Outcomes...............................................118
4.40 Intercorrelations between Independent and Control Variables: DP.....122
4.41 Intercorrelations between Independent and Control Variables: CVD....124
4.42 Multivariate Regression Analyses, DP Program Outcomes...............129
4.43 Multivariate Regression Analyses, CVD Program Outcomes..............130
xv


4.44 Multi-level Regression Analyses, DP Knowledge Outcomes.................134
4.45 Multi-level Regression Analyses, CVD Knowledge Outcomes................135
4.46 Multi-level Regression Analyses, DP Lifestyle Outcomes.................140
4.47 Multi-level Regression Analyses, CVD Lifestyle Outcomes................142
4.48 Multi-level Regression Analyses, DP Clinical Outcomes:
Weight, BMI...........................................................146
4.49 Multi-level Regression Analyses, DP Clinical Outcomes: Waist, Hips,
Waist/Hip Ratio.......................................................149
4.50 Multi-level Regression Analyses, DP Clinical Outcomes: LDL, HDL
Total Cholesterol, Triglycerides......................................153
4.51 Multi-level Regression Analyses, DP Clinical Outcomes:
Systolic BP, Diastolic BP.............................................156
4.52 Multi-level Regression Analyses, CVD Clinical Outcomes:
Weight, BMI...........................................................159
4.53 Multi-level Regression Analyses, CVD Clinical Outcomes:
Waist, Hips, Waist/Hip Ratio..........................................162
4.54 Multi-level Regression Analyses, CVD Clinical Outcomes: LDL
HDL, Total Cholesterol, Triglycerides.................................166
4.55 Multi-level Regression Analyses, CVD Clinical Outcomes:
Systolic BP, Diastolic BP, HbAlc......................................170
4.56 Multivariate Regression Analyses, Organization Type, DP Program
Outcomes..............................................................172
4.57 Multivariate Regression Analyses, Organization Type, CVD Program
Outcomes..............................................................174
xvi


4.58 Multi-level Regression Analyses, Organization Type,
DP Knowledge and Lifestyle Outcomes................................181
4.59 Multi-level Regression Analyses, Organization Type,
CVD Knowledge and Lifestyle Outcomes...............................182
4.60 Multi-level Regression Analyses, Organization Type, DP
Clinical Outcomes: Weight, BMI, Waist, Hips, Waist/Hip Ratio.......189
4.61 Multi-level Regression Analyses, Organization Type,
DP Clinical Outcomes: LDL, HDL, Total Cholesterol, Triglycerides,
Systolic BP, Diastolic BP....................................190
4.62 Multi-level Regression Analyses, Organization Type, CVD
Clinical Outcomes: Weight, BMI, Waist, Hips, Waist/Hip Ratio.......198
4.63 Multi-level Regression Analyses, Organization Type, CVD Clinical
Outcomes: LDL, HDL, Total Cholesterol, Triglycerides................199
4.64 Multi-level Regression Analyses, Organization Type, CVD Clinical
Outcomes: Systolic BP, Diastolic BP, HbAlc..........................200
4.65 Summary Results Table: Significant Findings: DP.....................201
4.66 Summary Results Table: Significant Findings: CVD....................203
5.1 A Comparison of Significant Findings for Competing
Effectiveness Criteria..............................................218
XVII


CHAPTER 1
INTRODUCTION
The desire to measure organizational effectiveness has dominated much of
the organizational research since its beginnings more than a century ago (Kalliath,
Bluedom, & Gillespie, 1999). Indeed, the topic has been the focus of many
prominent studies and continues to be examined today. In fact, some organizational
researchers (Goodman & Pennings, 1980) have argued that, on a theoretical level,
effectiveness is a central theme in all of organizational analysis and it is difficult to
conceive of a theory of organization that does not include the effectiveness
construct (Quinn & Rohrbaugh, 1983, p. 363).
As a construct, organizational effectiveness has focused on measuring how
successfully organizations achieve their mission through their core strategies and
practices (McCann, 2004). Organizational effectiveness studies are primarily
concerned with the unique capabilities that organizations develop in order to
perform well.
1


When examining organizational performance, the construct of organizational
effectiveness must eventually be examined to explain the intra- and
interorganizational variations in key values, practices and strategies that predict
success. Thus, an assessment of organizational effectiveness is a critically
important step in any study designed to identify the determinants of organizational
performance.
Current Situation in the Health Care Environment
The current situation in the health care environment in the U.S. makes
examining the organizational effectiveness and performance of health care
organizations a particularly salient topic for research. For instance, total
expenditures for health care were $647 billion in 1990 and increased to
approximately $2.3 trillion in 2000. Expenditures for prescription drugs more than
doubled in the last ten years (Mick & Wyttenbach, 2003). Given the increasing costs
of health care, the costs of health care insurance also increased dramatically. As a
result, the number of people without insurance grew substantially. In 2003, the
number of uninsured individuals in the U.S. reached 45 million, over 14 percent of
the U.S. population (Mick & Wyttenbach, 2003).
In response to these changing forces, health care delivery systems in the U.S.
have undergone significant and rapid change. Hospital downsizing and
consolidations have increased dramatically. Community hospitals across the country
2


lost 72,000 beds during the 1990s. By 2000, urgent care centers, surgi-centers, and
ambulatory care clinics were operating successfully across the country and had
become an accepted and efficient alternative to more expensive acute care hospitals
(Mick & Wyttenbach, 2003).
The Unique Context of American Indian and Alaska Native Health Care
These trends and issues within the health care environment create
exceptionally fertile ground for organizational effectiveness research. Within the
health care delivery environment, a particularly interesting and unique setting for
organizational effectiveness research is the Indian Health Service tribal and urban
Indian health care delivery system. There are several reasons why this is an
important setting for organizational effectiveness inquiry: 1) the public
administration/management literature has ignored American Indians and Alaska
Natives (AI/ANs), yet they represent a unique system of governance and non-profit
organization; 2) tribes are learning to overcome dependency on the Federal
government for services; 3) many tribes have recently assumed the management of
their own health and human services programs; and 4) the health status of AI/ANs
continues to be worse than any other group in the U.S. Therefore, effective
management of tribal health programs is vitally important.
The public administration/management literature has ignored AI/ANs.
AI/AN tribes make up approximately 2.5 million inhabitants of the total U.S.
3


population and they constitute a completely different level of governance. Tribes
possess inherent powers of self-governance, have their own governance structures,
and are dealt with on a govemment-to-govemment relationship by the U.S. Thus,
they have a significant and unique place in the field of public administration.
However, as Aufrecht (1999) has pointed out, The public administration literature
almost completely ignores the topic of Native Americans (p.371). In fact, to date,
there is only one article in the public administration literature that specifically
addresses American Indian issues (Ortiz, 2002).
One of the significant legacies of U.S. administrative history has been its
relationship with Native American cultures and societies, one that is often
characterized as assimilative and even attempting to displace or destroy native
cultures. American Indians are the quintessential wards of the state. Hundreds of
treaties and agreements with the Federal government define this govemment-to-
govemment relationship (Stafford 1999).
Tribal societies lived self-sufficiently for thousands of years prior to western
European exploration and colonization of this continent. However, through the
course of dealing with colonization and later the United States, often through formal
treaties, tribes relinquished ownership to millions of acres of land, containing
invaluable natural resources. In exchange, the U.S. agreed through treaties to protect
the reserved lands, rights, and resources as well as to provide health, housing and
educational services to Indian people. Many believe, however, that as a result of
4


generations of Federal dominance and control, self-sufficiency was replaced as the
United States through its Congress, courts, and particularly the Federal bureaucracy
transformed independent tribal status into tribal dependency (Dixon & Roubideaux
2001). Thus, examining the contemporary organizational and management capacity
of tribal nations is vitally important to determining if tribes have been able to
develop the necessary organizational infrastructure and managerial capacity to
effectively self-manage their health services.
Many tribes have recently assumed the management of their own health
services, which were formerly administered directly by the Federal government. In
1970, President Nixon laid the foundation for a new Federal policy to promote tribal
self-determination. Since that time, the policy of the Federal government has been to
promote tribal self-determination. As a major first step, the Indian Self-
Determination and Education Assistance Act (the Act) was passed in 1975 to allow
tribal management of programs that previously had been managed on their behalf by
the Departments of the Interior (DOI) and Health, Education, and Welfare.
Specifically, Title I of the Act authorized tribes to assume management of programs
in the Bureau of Indian Affairs (BIA) and Indian Health Service (IHS) through
contractual agreements (P.L. 638 contracts). Under these contracts, tribes assume
full responsibility for planning, conducting, and administering health services,
including hiring personnel, delivering services, record keeping, and other
administrative functions (Dixon and Roubideaux, 2001).
5


The National Indian Health Board has argued that lack of information,
misinformation, and lack of understanding of the roles and capabilities necessary for
effective tribal management among tribal leaders could be the greatest threat to self-
governance implementation (National Indian Health Board, 1998). Unfortunately,
there is a lack of research to provide tribal leaders with this information. No studies
in the U.S., to date, have focused on tribal self-governance from a public
management perspective. Consequently, research has not provided key insights into
the organizational and management requirements of effective tribal management of
these key programs.
However, the effective management of tribal health programs is vitally
important. The health status of AI/ANs continues to be worse than any other group
in the U.S. (Dixon & Roubideaux, 2001). Data collected in 2001 by the Indian
Health Service revealed that AI/AN infant mortality rates were higher and life
expectancy was lower than the general population. AI/ANs have a tuberculosis rate
that is 425 percent greater than the U.S. All Races population. They also
experience significantly greater rates of death due to behavioral health problems,
including alcoholism (579 percent greater), accidents, (212 percent greater), suicide
(70 percent greater), and homicide (41 percent greater).
In addition, the extent of the problem of diabetes among AI/ANs is
staggering (Acton, et al., 2001; Gohdes, Rith-Najarian, Acton, & Shields, 1996;
Mayfield, et ah, 1994; Newton, Wagner, Ramsey, & et ah, 1999; Quinn, et ah,
6


2001; Rith-Najarian, et al., 2002; Roubideaux, et al., 2004; Sperl-Hillen, et al.,
2000; Wagner, 1995; Wilson, Brown, Acton, & Gilliland, 2003). Some of the
highest rates of diabetes in the world are found in American Indian communities. In
some AI/AN communities, over 50 percent of the adult population has diabetes and
the prevalence is increasing. Diabetes prevalence rates are 74 percent for Al women
living in Arizona. The death rate from diabetes mellitus is 231 percent greater
among AI/ANs than the U.S. All Races population (Dixon & Roubideaux, 2001).
Additionally, cardiovascular disease is now the leading cause of death in AI/ANs
and the high and rising mortality rate of cardiovascular disease has been closely
associated with diabetes in native communities (Rith-Najarian, et al., 2002).
Consequently, the effective management of tribal health programs,
especially those focusing on diabetes, is extremely important to the health status of
this unique population. Unfortunately, there are few studies focusing on the effect
of organizational characteristics and managerial practices on the quality of diabetes
care among AI/ANs.
Purpose/Research Questions
This project sought to address the above-noted deficiencies in the public
management literature by focusing on AI/AN tribal health programs from a public
management perspective. The primary purposes of this study are to identify and
describe key organizational characteristics and management practices of
7


organizations implementing tribal diabetes programs and to explore whether these
factors relate to organizational performance. Thus, the research questions are:
1. What are the predominant organizational effectiveness profiles of
organizations implementing Indian Health Service tribal diabetes programs?
2. Which organizational effectiveness variables are associated with successful
performance among tribal diabetes programs?
3. Are tribes and tribal organizations that exercise self-determination by
managing their own health care more successful in implementing diabetes
programs?
Thesis Outline
The following chapters describe the theoretical and methodological approaches
and present the results and conclusions of a study aimed at investigating the
research questions listed above. In Chapter 2 a review of the organizational
effectiveness literature is provided, which will critique key organizational
effectiveness research models and provide a rationale and a detailed analysis of the
chosen approach. Chapter 3 offers a discussion of the methodological approach
including the hypotheses, study design, study population, sample, dependent
variables, independent variables, validity and reliability issues, and the data analytic
methods. Chapter 4 presents the research findings and Chapter 5 discusses the
significance and implications of these findings.
8


CHAPTER 2
LITERATURE REVIEW
This chapter provides a review of the literature related to the theoretical
underpinnings of this study. First, a review of the construct of organizational
effectiveness is provided, which includes a critique of the popular organizational
effectiveness measurement models. Next, an examination of the models that have
been applied to the healthcare setting is presented and is followed by a discussion of
the organizational determinants of healthcare quality and diabetes care performance.
Then a discussion of the theoretical framework to be applied in this study is
provided, which includes an examination of the strengths and limitations of the
chosen theoretical framework. Finally, discussions regarding indigenous self-
determination theory and diabetes care performance measures are offered.
Organizational Effectiveness
The measurement of organizational effectiveness is essential to the improvement of
any organizations performance. Yet, there is little agreement as to the definition,
criteria and approaches to measuring organizational effectiveness. Yuchtman and
Seashore (1967) saw effectiveness as the ability of an organization to exploit its
environment in the acquisition of scarce and valued resources. Hannan and
Freeman (1977) argued that effectiveness is the concordance between goals and
9


outcomes. Some researchers define effective organizations as those that receive
inputs, transform them into outputs, export them into environments, and monitor
changes in the environment and take corrective actions to ensure survival (Handa &
Adas, 1996; Miner, 1988). In a review of the effectiveness literature, Campbell
(1977) identified 30 different criteria for effectiveness. This led Campbell to
conclude:
.. .different people adhere to different models, and there is no correct
way to choose among them. Thus, when a list is put together from
different conceptual points of view, the composite list will always
inevitably look messy (Campbell, 1977, p. 40)
Thus, researchers who study organizational effectiveness typically do not
agree on one conclusive model or framework for measuring effectiveness
(Cameron, 1988; Rainey, 1997, 2003). Therefore, there are many approaches to
measuring organizational effectiveness. One of the most common is the Rational
Goal Model. The rational goal model implies that the manner in which to examine
organizational effectiveness is to determine ones goals and evaluate whether these
goals are successfully achieved (Etzioni, 1960; Miles, 1980; Rainey, 1997, 2003;
Steers, 1977). However, this assumes that the goals are clear and measurable, and
that people in the organization can identify the actual goals. This exercise is often
problematic because organizations have many goals, which often have various
dimensions, operate at different levels of generality, and conflict with one another.
10


This is especially true in public organizations such as hospitals and health systems
(Rainey, 1997; Rojas, 2000).
Organizations usually have many different stakeholders to whom they are
accountable, such as managers, constituency groups, oversight and regulatory
agencies, different subunits within the organizations, and trustees (Rainey, 1997;
Rojas, 2000; Scholl, 1981). Each of these groups may have different and varying
goals and expectations for the organization. Goals vary in terms of time frames,
with some being short-term and others long-term. Organizations can have formal
goalsthose that are known to the publicand actual goalsthose known only to
the organization (Rainey, 1997; Rojas, 2000; Scholl, 1981). Consequently,
measuring organizational effectiveness using a goal model entails the difficulty of
specifying an organizations goals. However, even when organizational goals are
clear, the goal approach does not provide a structure for evaluating how goals are
achieved. Thus, the goal approach does not provide a framework for researchers
seeking to analyze what organizational characteristics or managerial practices may
be associated with successful performance.
Another well-known model for measuring organizational effectiveness is the
Systems-Resource Model developed by Yuchtman and Seashore (Rainey, 1997;
Yuchtman, 1967). This model focuses on whether an organization can gamer
enough resources from its environment to sustain itself (Rainey, 1997; Yuchtman,
1967). Yuchtman and Seashore studied insurance companies and identified a
11


number of criteria useful for measuring effectiveness. These criteria are business
volume, market penetration, youthfulness of organizational members, and
production and maintenance costs (Rainey, 1997; Yuchtman, 1967). These
secondary criteria should lead to the ultimate organizational outcome of
effectiveness, which is an organizations ability to exploit valued resources and
opportunities (Rainey, 1997; Yuchtman, 1967).
The systems-resource model has been criticized because it seems to confuse
the hierarchy and dimensions of important variables. Some of the criteria could be
considered goals and others could be means of achieving goals, and some are
obviously more important than others (Molnar, 1976; Rainey, 1997; Smith, 2003).
The criteria also ignore customers and public interest groups that might have
different interests in an organization. In addition, the criteria may not be
generalizable to public organizations (Molnar, 1976; Rainey, 1997; Smith, 2003).
The Participant-Satisfaction Model is another well-known organizational
effectiveness measurement approach. This approach measures the effectiveness of
the organization by surveying participants about their satisfaction with it and
whether or not it meets their needs (Cameron, 1978; Kenny, 1987; Rainey, 1997).
However, this approach has been criticized because it has serious limitations if the
participant group is defined too narrowly. Participants often include suppliers,
customers, regulators and others external to the organization. However, measuring
this broad range of participants is challenging. Even the studies that use a broad,
12


comprehensive approach often encounter problems in measuring the general social
significance of an organization such as this approach pursues (Keeley, 1984;
Rainey, 2003).
The Human Resource and Internal Process Model, which measures
organizational effectiveness by focusing on such factors as internal
communications, leadership styles, motivation, interpersonal trust, and other factors
assumed to be desirable within an organization, also holds promise as an effective
measurement tool (Blake & Mouton, 1984; Likert, 1967; Rainey, 1997). Some
management scholars have identified weaknesses in public management because of
inadequate management systems and ineffectiveness procedures (Crane, 1982;
Rainey, 1997). Therefore, they believe better internal control systems are needed.
Focusing on these key aspects to organizational effectiveness may prove to be a
sufficient measurement procedure. However, this method of measurement often
overlooks important output indicators, systematic program and policy evaluation
activities, and key performance measures (Rainey, 1997).
Several researchers have offered suggestions regarding how to clarify the
construct of organizational effectiveness. Steers (1975) argued that the initial step
should be to identify all of the variables in the domain of effectiveness and then
determine how they are related. Campbell recommended a similar approach and
stressed the need to weed out the overlap and get down to the core variables
(Campbell, 1977, p. 39).
13


Scott (1977) suggested that the various criteria for effectiveness could be
reduced to three basic models: the rational system model, the natural system model
and the open system model. According to Scott, the rational system model focuses
on productivity and efficiency. The natural system model stresses not only the
production function but also the activities required for the unit to sustain itself. The
open system model focuses on adaptability and resource acquisition.
Seashore (1979) has also proposed a three-model integration of the
effectiveness criteria which includes a goal model, which is similar to Scotts
rational model; a natural system model, which includes both Scotts natural and
open systems models; and a decision process model. (See Quinn & Rohrbaugh,
1983). The decision process model stresses the importance of optimizing the
processes for getting, storing, retrieving, allocating, manipulating and discarding
information.
Cameron, Quinn and Rohrbaugh (Cameron, 1978, 1986, 1988; Cameron &
Freeman, 1991; Cameron & Whetton, 1983; Quinn & Cameron, 1983; Quinn &
Kimberly, 1984; Quinn & McGrath, 1985; Quinn & Rohrbaugh, 1983; Quinn &
Spreitzer, 1991; Rohrbaugh, 1981) have advocated a four-model integration of the
popular organizational effectiveness criteria. These four models are the human
relations model, which stressed flexibility and internal focus; the open system
model, emphasizing flexibility and external focus; the internal process model,
14


stressing control and internal focus; and the rational goal model, emphasizing
control and external focus.
Organizational Effectiveness Models that have been Applied to the Health Care
Setting
Contingency-Strategic Model.
Several organizational effectiveness models have been applied to the health
care setting and hold promise for examining health organizations. Lin (1999)
applied a contingency-strategic model to examine determinants of integrated health
networks performance. Contingency theory challenges the traditional claim that an
organization has a best way to be organized (Taylor, 1912) and asserts that there
is no best way. Thus, effectiveness of an organizational structure depends on the
nature of the environment to which the organization relates (Lin, 1999). However,
this approach is often criticized because organizations become what they are not
only because of the environment, but also because of the choices made by members,
especially the choices about strategy and organizational design. Thus, an integrated
contingency-strategy approach assumes that organizations are open systems that
confront and respond to various challenges and opportunities in the environments in
a strategic manner.
The contingency-strategic model developed by Lin used hospital
administrative record data that are not readily available from tribal health systems
15


and focuses exclusively on vertically integrated health networks. However, most
tribal health programs do not fit into this type of health system.
Comnetim Values Framework
Another model which holds promise for measuring organizational
effectiveness of health care organizations is the Competing Values Framework. As
can be seen in the literature, organizational effectiveness models have competing
values and diverse criteria for measuring organizational effectiveness. This fact led
Quinn and Rohrbaugh (1983) to develop their Competing Values approach (Quinn
& McGrath, 1985; Quinn & Rohrbaugh, 1983; Quinn & Spreitzer, 1991). Initially,
the framework was developed through a multidimensional scaling process that
identified three axes undergirding eight commonly used criteria for measuring
organizational effectiveness. The three axes are flexibility versus control, internal
versus external focus, and means versus ends. The same three dimensional
configuration was found again as the result of a larger, replication study of
organizational researchers and theorists (Quinn & Rohrbaugh, 1983).
The first set of axes contrasts two dimensions of an organizations structure:
flexibility and control. Flexibility values innovations, adaptation and change, while
control values stability, order and predictability (Quinn & Rohrbaugh, 1983).
The second set of axes focuses on whether emphasis should be placed
internally on the well-being and development of people in the organization or
16


externally on the environment in which the organization operates. The third set
relates to organizational means versus ends, with means stressing internal
processes and a short-term timeframe. The ends emphasizes final outcomes and a
long-term timeframe (Handa & Adas, 1996; Quinn & Rohrbaugh, 1983).
A major strength of the CVF is its development from four major organizational
effectiveness schools of study. Each reflects long traditions in management and
organizational psychology (Patterson, et al., 2005; Quinn & McGrath, 1985; Quinn
& Rohrbaugh, 1983; Quinn & Spreitzer, 1991; Rainey, 1997):
The human relations approach which reflects the tradition of the socio-
technical (Emery & Trist, 1965) and human relations schools
(McGregor, 1960). It emphasizes the well-being, growth and
commitment of the community within the organization.
The internal process approach which reflects the concern of Frederick
Taylors scientific management (Taylor, 1912) for formalization and
internal control of the system in order to use resources efficiently.
The open systems approach emphasizes the interaction and adaptation of
the organization in its environment with managers seeking resources and
innovating in response to environmental demands (Shipper & White,
1983; Yuchtman, 1967).
17


The rational goal approach reflects a rational economic model or
organizational functioning and emphasizes productivity and goal
achievement (Etzioni, 1960; Hall, 1980; Miles, 1980; Steers, 1975, 1977)
Quinn and Rohrbaugh (1983) assert that managers constantly face
competition among values and they must balance or concurrently manage them
effectively. As illustrated in Figure 2.1, there are contrasting values that define the
four approaches. Each approach represents a particular set of values/criteria of
effectiveness and has a polar opposite with contrasting emphasis. The horizontal
axis depicts whether dominant values are internal or external to the organization.
The vertical axis relates to organizational structure and it contrasts stability and
control with flexibility. The organizational means and ends (represented by the
diagonal axes) contrast the processes or means (e.g., goal setting) with
organizational outcomes or ends, for example, productivity (Handa & Adas, 1996;
Quinn & Rohrbaugh, 1983).
The flexibility/control continuum represents the way organizations structure
themselves to handle their internal components while simultaneously meeting the
external challenges of competition, adaptation, and growth. For example, the
tumultuous transformations in the health care environment have generated extensive
internal reorganization in many health care organizations. The intemal/extemal
continuum represents how well organizations manage the demands for change
arising from its environment while simultaneously maintaining continuity. For
18


example, a health care organization must align externally induced structural changes
with its mission. Therefore, in responding to the demands from the organizations
external environment, all structural changes must contribute to the organizations
ability to achieve its mission and to increase its effectiveness.
There are inherent contradictions within the framework. Thus, that is why it
is called the Competing Values Framework. However, it is critical to point out that
although certain pairs of concepts are at opposite locations in the value space, it
does not mean that they are empirical opposites or mutually exclusive in actual
organizational environments. In fact, an organization might be cohesive (human
relations model) and productive (rational goal model) at the same time. Also, an
organization may be stable (internal process model) and innovative (open systems
model) concurrently. As Quinn and Rohrbaugh suggest, in the real world, an
effective organization may need to perform well in more than one quadrant (Quinn
& Kimberly, 1984; Quinn & Rohrbaugh, 1983).
19


Figure 2.1
The Competing Values Framework
Human Relations
t
Open Systems Model
Org. Structure:
20


Each model emphasizes dominant effectiveness values which contrast with
the other models and which influence the level of effectiveness in the organization
differently. The open systems model stresses a flexible organizational structure and
an external organizational focus as dominant effectiveness values; readiness and
flexibility are means, while growth and external support are ends. The rational goal
model emphasizes a structure of control and an external organizational focus as
dominant effectiveness values, planning and goal setting are means and
productivity and efficiency are ends. The internal process model stresses an
organizational structure of control and an internal focus as dominant effectiveness
values; emphasizing communication processes as means and control as ends.
Dominant effectiveness values for the human relations model are flexible
organizational structure and internal focus, with cohesion and morale as means and
skilled workers as ends (Handa & Adas, 1996; Quinn & Rohrbaugh, 1983).
The Rational Goal model represents the application of rational economic
principles in the design and direction of work and in rewarding workers. This
model measures organizational effectiveness by profits and productivity. The roles
of management in the rational goal model are to set clear goals for the organization,
to rationally analyze what actions contribute most to the goals, to plan and organize
work, to define expectations and job responsibilities, to give instructions, to
prescribe policies and rules, and to initiate problem solving when necessary. In
health care today the rational goal models concept of organizational effectiveness
21


is manifest in the emphasis on strategic management (Handa & Adas, 1996;
Quinn & Rohrbaugh, 1983).
In the Internal Process model, an effective organization is seen as one that
evidences continuity, stability, reliability, and predictability. The focus is
internalon the organization itselfand on control of the processes and resources
the organization employs to accomplish its work. This model reflects the values
and principle of classical bureaucratic theory and focuses on the organization as a
whole. The principles advocated are a clear division of labor, assignment of
authority equal to responsibility, unity of command, and subordination of
individual interests to the interests of the organization. Much of the attention of
health care organizations today is directed outward as market demands become
more intense. Although the origin of these issues lie outside the organization,
effective responses require close management of internal operations and processes
(Handa & Adas, 1996; Quinn & Rohrbaugh, 1983).
Emphasis in the Human Relations Model is on the organizations people
and on the informal or social side of the organization. The effective
organization is characterized by commitment, cohesion and high morale on the part
of its people. Great value is place on the development of peoples full potential
through training, team building, empowerment, participation and attention to
collegial relations. Health care organizations today are facing intense pressure to
change, and change in fundamental ways. The future is unclear, demands are great,
22


nurse recruitment and retention has been unsuccessful, resources are insufficient,
and critical stakeholders do not see eye to eye on what the organization should do.
Thus, health care executives are coming to recognize that changing times demand
renewed emphasis on the organizations human resources (Handa & Adas, 1996;
Quinn & Rohrbaugh, 1983).
The Open Systems perspective of organizational effectiveness emerged as
the external environment of organizations became more complex, demanding and
uncertain. Adaptability and innovation became keys to success as organizations
sought to respond quickly to changing demands of the marketplace. Thus, in this
model, organizational effectiveness is measured by the organizations ability to
adapt and by its ability to acquire support from external stakeholders (Handa &
Adas, 1996; Quinn & Rohrbaugh, 1983).
Thus, the CVF offers a meta-theoretical model which provides a framework
of values that underlie organizational effectiveness, is anchored at the
organizational level, and represents a broad class of organizational variables that
constitute the organizational context for managerial actions. The frameworks four
quadrants describe four broad domains (latent constructs) of valued outcomes and
associated managerial ideologies about the means through which outcomes may be
achieved. As a summary, Table 2.1 lists the variables and supporting literature for
the Competing Values Framework.
23


Table 2.1
Variables of the CVF and Supporting Literature
Variables
Supporting Literature
Stability and control
Documentation, information
management
Management of individuals,
cohesion, morale
Human resources, smooth
functioning group
Planning and Goal Setting
Productivity and accomplishment
(Blake & Mouton, 1984; Coch,
1948; Hall, 1991; Likert, 1967;
Likert, 1961; Pugh, Hickson,
Hinnings, & Turner, 1968)
(Callan, 1993; Cummins, 1990;
Eisenberger, Stinglhamber,
Vandenberghe, Sucharski, &
Rhoades, 2002; Gattiker, 1995;
Guest, 1998; Heller, Pusic,
Strauss, & Wilpert, 1998;
Hollander & Offerman, 1990;
Lawrence & Lorsch, 1967a;
Miller & Monge, 1986; Morrow,
Jarrett, & Rupinski, 1997; Nauta
& Sanders, 2000; Robinson &
Rousseau, 1994)
(Deming, 1986; Etzioni, 1960;
Hackman & Wageman, 1995;
Locke, 1991, 1979;McCaol,
Hinsz, & McCaol, 1987; Miles,
1980; Ostroff & Schmitt, 1993;
Steers, 1977; Taira, 1996)
Flexibility, innovation and adaptation (Garrahan & Stewartj m2.
Growth and resource acquisition Kiesler & Sproull, 1982; King &
Anderson, 1995; West, 1996,
2000; West & Farr, 1990)
Quinn and Rohrbaugh (1983) assert that organizations tend to pursue the
values of more than one model concurrently. This is represented by the
24


hybridization of values between the four models. Thus, when organizations pursue
conflicting values, certain trade-offs result between the levels of these values based
on the specific environmental context faced by the organization. For example,
emphasizing the development of workers and adopting strategies to increase morale
does not preclude an organization from stressing competitiveness in the external
environment. Therefore, the Competing Values Framework is a more realistic view
of the nature of the organization and how it operates to achieve effectiveness
because it views effectiveness as a hybridization of certain levels of values across
four disparate models (Handa & Adas, 1996; Quinn & Rohrbaugh, 1983).
Although the framework was originally developed to identify the structure
among possible criteria used to measure organizational effectiveness, the CVF has
been applied in a wide range of organizational research, including the investigation
of organizational culture (Bluedom & Lundgren, 1993; Cameron & Freeman, 1991;
Hooijberg & Petrock, 1993; Quinn & McGrath, 1985); organizational structure
(Bahargava & Singha, 1992; Flood, 1994); leadership styles and effectiveness (Di
Padova & Faerman, 1993; Flood, 1994; Quinn & Kimberly, 1984); managerial
understanding (Di Padova & Faerman, 1993); information systems (Cooper &
Quinn, 1993); management communication (Bahargava & Singha, 1992);
organizational lifecycle (Quinn & Cameron, 1983); compatibility of organizational
culture and strategy (Bluedom & Lundgren, 1993); organizational transformations
(Hooijberg & Petrock, 1993); union-management interface (McGraw, 1993);
25


corporate ethical codes (Stevens, 1996), management training (Sendelbach, 1993);
health care quality (Flood, 1994; Kalliath, et al., 1999); human resource
management (Panayotopoulou, Bourantas, & Papalexandris, 2003); participative
budgetary control processes (Dunk & Lysons, 1997); and teaching (Thompson,
1993).
The CVF incorporates three sets of competing values which are recognized
dilemmas in the organizational effectiveness literature. The first dilemma,
flexibility versus stability, represents an ongoing debate. While many social
theorists have emphasized authority, structure, and coordination, many others have
stressed diversity, individual initiative and organizational adaptability (Quinn &
Rohrbaugh, 1983). Lawrence and Lorsch (1967b) focused their landmark study on
this dilemma and argued that integration and differentiation were the core issues in
the history of organizational design. They found that organizations that are able to
best balance integration and differentiation are also the most effective systems.
Other organizational effectiveness theorists have developed similar arguments
(Aram, 1976).
The second set of competing values in the framework, internal versus
external focus, represents another basic dilemma of organizational reality. The
emphasis of the external focus is on the overall competitiveness of the organization
in changing environments. An internal focus would emphasize the organization as a
socio-technical system. Thus, when the value of the external focus is maximized,
26


the internal focus on the socio-technical equilibrium may be reduced.
Alternatively, when the internal harmony grows, it may tend to shift the emphasis
away from overall competitiveness (Quinn & Kimberly, 1984; Quinn &
Rohrbaugh, 1983). However, non-profit organizations have much less incentive to
focus on overall competitiveness, especially when they are the only organization
offering the service, such as is the case with tribal diabetes programs.
The third set of competing values in the framework is means versus ends.
Organizational effectiveness researchers have discussed this dilemma in terms of
conflicting time horizons (Lawrence & Lorsch, 1967b) and have stressed the
difficulty of balancing means and ends at some optimum point. However, the
balancing of means and ends may result in optimum performance (Quinn &
Kimberly, 1984; Quinn & Rohrbaugh, 1983).
It is important to note that the CVF does not propose that organizations can
be located predominantly in one quadrant; instead, reflecting the rich mix of
competing views and perspectives in organizations, the CVF proposes that
organizations will be active in, and give emphasis to, each domain, but with
differing strengths (Quinn, 1988; Quinn & Rohrbaugh, 1983). Indeed, Quinn
(1988) and others (Patterson, et al., 2005) have argued that a balance of competing
organizational values is required for organizational effectiveness.
27


In summary, the Competing Values Framework represents a comprehensive
model for measuring organizational effectiveness based on four dominant
organizational effectiveness constructs (i.e., open systems, internal process, rational
goal and human relations). It holds promise as an effective model for measuring
effectiveness within tribal health system organizations. The CVF has been used
extensively with many types of organizations and the measurement model has
undergone extensive validity and reliability testing.
The Competing Values Measurement Model of Organizational Effectiveness
The four latent dimensions of the Competing Values organizational
effectiveness constructhuman relations, open systems, rational goal, and internal
process valueswere tested by Quinn and Spreitzer (1991) in a sample of 796
executives from 86 public utility firms. The psychometric properties of the
subscales designed to measure each of the four dimensions were assessed in two
separate analyses: a multitrait-multimethod analysis and a multidimensional scaling
analysis. The multitrait-multimethod analysis was conducted by comparing the
results from two types of competing values scales: a Likert-type scale and an
ipsative scale. Ipsative scores are generated by forced choice questionnaire
formats, where respondents order sets of items loading on different scales. In
effect, a constant number of points (the available rankings) are distributed between
28


the different scales. Data from both of these scales were used to establish
convergent and discriminant validity estimates in order to assess construct validity.
Convergent validity was established by showing that scale scores from the same
competing values quadrant (e.g. human relations and open systems) had
correlations significantly greater than zero and of moderate magnitude.
Discriminant validity was established by demonstrating that scale scores from the
same quadrant (e.g., human relations and open systems) correlated more highly
with each other than they did with scale scores from different quadrants measured
by separate methods. Analyses also showed that scale scores from the same
quadrant correlated more highly with each other than they did with scale scores
from different quadrants measured with the same method. Multidimensional
scaling also supported the measurement model. In addition, spatial mapping
provided support for the models hypothesized relationships (Kalliath, et al., 1999).
Additional analyses on the Competing Values Framework were conducted
by Kalliath et al. (1999). They used structural equations modeling to investigate
the structural relationships between the four latent constructs of the CVF. Based on
a sample of 300 hospital managers and supervisors, the results supported the four
factor structure of the Competing Values Framework.
Data from the Kalliath study show that organizational effectiveness is a
multidimensional construct comprising multiple criteria. The results of this study
29


support a conceptualization of organizational effectiveness based on the four
dimensions of the CVF. These four dimensionshuman relations, open systems,
rational goal and internal processmay be used individually or together as distinct
dimensions of effectiveness, but it is essential to think of the organizational
effectiveness construct as consisting of four distinct variables instead of one
(Kalliath, et al., 1999). Thus, the measurement model provides a comprehensive
profile of organizational effectiveness along the eight CVF variables and the four
latent constructs [i.e., innovation and adaptation; growth and resource acquisition
(open systems); planning and goal setting; productivity and accomplishment
(rational goal); documentation and information; stability and control (internal
process); and management of individual, cohesion and morale; smooth functioning
group (human relations) and is illustrated in Figure 2.2.
Figure 2.2 represents a sample organizational effectiveness profile of an
individual organization. This profile is created by taking the mean of all individual
scores of respondents completing the CVF measurement instrument within a
particular organization. For example, if a researcher conducted the CVF survey
with a number of individuals (typically both managers and general staff) at an
organization, s/he would then take the mean of their scores on the instrument
(based on a 5 point scale for each item) and rank the organization on each of the 8
variables listed above to get the organizations effectiveness profile. Thus, as can
be seen in Figure 2.2, this sample organization scored high on management of
30


individuals, cohesion and morale and smooth functioning group. This indicates that
the organization values a flexible organizational structure and an internal
organizational focus. Thus, this organization fits best into a human relations
organizational effectiveness model.
31


Figure 2.2
Example Organizational Effectiveness Profile
Human Relations Model
t
Open Systems Model
Org. Structure: FLEXIBILTY
Internal Process Model

Rational Goal Model
32


Organizational and Managerial Determinants of Quality of Health Care
There is substantial empirical evidence in support of an organizations
impact on quality of health care. Several studies suggest that the
hospital/organization where care is provided is a better predictor of quality than the
qualifications and experience of the physician providing the care (Flood & Scott,
1987; Rhee, Luke, & Culverwell, 1980; Rhoades, 2002; Winslow, Kosecoff,
Chassin, Kanouse, & Brook, 1988; Yergan, Flood, LoGerfo, & Diehr, 1987). In a
cross-sectional analysis of 100 integrated health networks, Lin (1999) found that
integrated health networks organizational characteristics (i.e., for profit versus
non-profit status and service complexity) show more statistically significant effects
on their service differentiation strategies (i.e., contract variability, HMO strategy,
non-hospital service strategy), integrated structural design (i.e., integrated
leadership, centralized decision making, disease/case management), clinical
efficiency (i.e., average length of stay, charges per hospital admission) and
financial viability (i.e., net incomes, operating margin, profit margin) than do
environmental factors (i.e., market competition and managed care).
Mitchell and Shortell (1997) evaluated the state of the science with respect
to morbidity, mortality, and adverse effects as outcomes indicative of variations in
organizational variables in health care delivery systems. Eighty-one research papers
examining relations among organizational structures or processes and
mortality/adverse effects were reviewed. Results indicate that there is support in
33


some studies, but not in others, that nursing surveillance, quality of working
environment, and quality of interaction with other professionals distinguish
hospitals with lower mortality and complications from those with higher rates of
these adverse effects. (Mitchell & Shortell, 1997)
Based on data collected from 17,440 patients across 42 intensive care units,
Shortell et al. (1994) examined the factors associated with risk-adjusted mortality,
risk-adjusted average length of stay, nurse turnover, technical quality of care, and
ability to meet family member needs. Using the Apache III methodology (i.e.,
prognostic scoring system for intensive care units) for risk-adjustment, findings
reveal that: 1) technological availability is significantly associated with lower risk-
adjusted mortality (regression coefficient: beta = -.42); 2) diagnostic diversity is
significantly associated with greater risk-adjusted mortality (regression coefficient:
beta = .46); and 3) caregiver interaction comprising the culture, leadership,
coordination, communication, and conflict management abilities of the unit is
significantly associated with lower risk-adjusted length of stay (regression
coefficient: beta = .34), lower nurse turnover (regression coefficient: beta = -.36),
higher technical quality of care (regression coefficient: beta = .81), and greater
ability to meet family member needs (regression coefficient: beta = .74).
Furthermore, units with greater technological availability are significantly more
likely to be associated with hospitals that are more profitable, involved in teaching
34


activities, and have unit leaders actively participating in hospital-wide quality
improvement activities (Shortell, et al., 1994).
Other studies have broadened their scope to include not only whether but
how health organizations can affect the quality of care provided under their
governance. Flood (1994) argues that the following determinants explain why and
how organizations affect quality of care: the physician and his or her training and
experience; the profession and its formal procedures for selecting and licensing
physicians; the hospital as a workshop; and health care organizations as complex
organizations influencing work through their effects on processes such as
coordination, communication, and incentives.
Organizational and Managerial Determinants of Diabetes Care Performance
Recent research in the management of chronic disease care, including
diabetes care, has identified the following management practices as essential for
effective performance: 1) organization of the healthcare delivery systems with a
focus on chronic disease management; 2) well established linkages between the
health delivery system and community resources; 3) provision of self-management
support built into the care model; 4) provision of decision support systems and
resources for providers; 5) delivery system design; and 6) clinical information
systems (Bonomi, Wagner, Glasgow, & VonKorff, 2002; Davis, Wagner, &
Groves, 2000; Gohdes, et al., 1996; Grant, Buse, & Meigs, 2005; Omstein &
35


Jenkins, 1999; Sperl-Hillen, et al., 2003; VonKorff, Gruman, Schaefer, Curry, &
Wagner, 1997; Wagner, 1995, 1998; Wagner, Austin, et al., 2001; Wagner, Austin,
& VonKorff, 1996; Wagner, Glasgow, et al., 2001).
To date, there have been no studies focusing specifically on organizational
and managerial determinants of the performance of tribal diabetes care and
prevention programs. Most studies found in the literature have been concerned
with measuring and improving the quality of care for patients with diabetes as
related to performance indicators and none of these studies have examined
organizational and management determinants (Acton, et al., 2001; Acton, et al.,
1993; Rith-Najarian, et al., 2002; Roubideaux, et al., 2004).
Theoretical Framework
Rationale for Using the Competing Values Framework to Examine Tribal Health
Care Organizations.
Organizational effectiveness researchers have suggested that in order to
develop accurate measurement at the organizational level, variables/measures must
be combined into an overall model that indicates performance in the multiple
domains of effectiveness (Cameron, 1986, 1988; Dotty, Glick, & Huber, 1993;
Meyer, Tsui, & Hinings, 1993; Tsui, 1990). They also argue that a
multidimensional view of performance implies that different patterns of
36


relationships of organizational performance and its determinants will emerge (Tsui,
1990). Miller and Freisen, suggest that organizational effectiveness researchers
should use an approach based on recurring patterns of attributes or configurations
of attributes that relate to effectiveness empirically (Miller & Friesen, 1984).
Additionally, Meyer et al. (1993) argue that using configurational approaches
represents a more holistic approach and allows researchers to explain how order
emerges from the interaction of these parts as a whole rather than only from
segments of the organization (Handa & Adas, 1996).
Dotty et al. suggest three main steps in order to develop valid quantitative
models based on configurational inquiry. First, organizational configurations must
be conceptualized as ideal types where effectiveness is highest because the fit
among the contextual, structural and strategic factors is at a maximum in these
configurations (Dotty, et al., 1993). Second, organizational characteristics which
represent the different effectiveness domains of ideal types must be integrated into
an overall multivariate profile or model. Then the level of these characteristics
must be determined against a valid measure of effectiveness (Handa & Adas,
1996). Finally, the overall model can then be used to predict the effectiveness of
the organization based on an measurement of the level of these characteristics in
the organization under study (Dotty, et al., 1993).
After a careful review of the models and approaches for measuring
organizational effectiveness, the Competing Values Framework appears to be a
37


valid configurational approach with which to measure effectiveness for this
proposed study for several reasons. First, its configurations represent integration of
most of the effectiveness criteria already used by organizational effectiveness
researchers (Quinn & Rohrbaugh, 1983). Second, the theoretical model has been
confirmed through multi-method analysis, multi-dimensional scaling and
structural equation modeling with data gathered from health care systems and has
been deemed reliable (Kalliath, et al., 1999; Quinn & Spreitzer, 1991). Finally, the
measurement instrument has been validated and deemed reliable through
confirmatory factor analysis and structural equation modeling (Kalliath, et al.,
1999).
Limitations of the Competing Values Framework
Although the Competing Values Framework provides a comprehensive,
multidimensional construct for measuring organizational effectiveness and allows
the researcher to create a profile of an organizations dominant strategic, structural,
and focus values, it does not predict which profile represents the most effective
organization. CVF developers argue that the most effective organization has the
most well rounded shape on the CVF profile and the highest scores on the largest
number of criteria (Thompson, McGrath, & Whorton, 1981). The authors of the
CVF would most likely argue that the frameworks most important quality is its
ability to answer the question which effectiveness values an organization pursues
38


and how an organization defines success. Thus, the framework answers the
question: effectiveness from which perspective?
However, organizational researchers who want to use the CVF to link an
organizations strategic, structural and focus values to objective organizational
performance outcomes will be left with many unanswered questions. For example,
does emphasizing the open systems criterion actually result in more new ideas,
products, and services? Does emphasizing the human relations criterion result in
higher morale and lower employee turnover? Is a rational goal emphasis associated
with higher quality and higher profits? Is an internal process emphasis associated
with accurate records and on-time delivery of goods and services (Thompson, et al.,
1981)? Additionally, do high scores on a number of the CVF organizational
effectiveness variables predict success in implementing health related programs?
Thus, researchers seeking to connect an organizations CVF profile to
organizational outcomes will need to relate the CVF profile to some objective
construct of organizational performance. However, to date, only one such study has
been conducted. This study sought to predict the performance of construction firms
using the Competing Values Framework (Handa & Adas, 1996). The study
hypothesized a multivariate linear model using 14 variables relevant to construction
firms and congruent with the Competing Values dimensions as predictors of
construction firm performance and related these predictors to a construct of
construction firm performance/outcomes. Cross-sectional data were collected from
39


76 firms. The model shows that five of the 14 hypothesized variables (i.e.,
organizational attitudes toward change; multiple project handling ability; level of
planning my management; strength of organizational culture and level of workers
participation in decision-making) are highly significant in predicting the level of
organizational effectiveness in the construction firms studied. It is important to
note, however, that Handas and Adas used objective, administrative data related to
the CVF variables not the subjective CVF measurement instrument.
Self-Determination Theory
Research question three for this study seeks to answer whether the exercise
of indigenous self determination predicts successful performance among the
diabetes programs. Thus, the theoretical background for this line of inquiry is
provided here.
Indigenous self-determination represents the various strategies of
indigenous groups to regain control over their destinies after a history of imperial
oppression and dispossession (Gilbert, 1993). The theory or hypothesis of self-
determination can be summarized as simply: 1) if indigenous people gain control;
2) their lives will improve (Conroy & Yuskauskas, 1996). Gaining control is
seen first and foremost as control over resources. Thus, a major component of the
Indian Self-Determination and Education Assistance Act which was passed in 1975
is to allow tribes to assume management of programs in the Bureau of Indian
40


Affairs (BIA) and Indian Health Service (IHS) through contractual agreements
(P.L. 638 contracts). Under these contracts, tribes assume full responsibility for
planning, conducting, and administering health services, including hiring
personnel, delivering services, record keeping, and other administrative functions
(Dixon and Roubideaux 2001). Under the theory of self-determination as power
and control shift away from Federal domination through contractual arrangements
with tribes lives will improve.
Several studies have examined this theory. Research on individual self-
determination has indicated that autonomous and competence motivations are
correlated with improved glycemic control suggesting that perceptions of autonomy
and competence may underlie effective diabetes self-management (Deci & Ryan,
1985; Senecal, Nouwen, & White, 2000; Sheldon, Williams, & Joiner, 2003;
Williams, Freedman, & Deci, 1998). Several studies have focused on the exercise
of self-determination related to general tribal management. The Harvard Project on
American Indian Economic Development has conducted a number of studies which
have focused on the conditions under which sustained, self-determined social and
economic development is achieved on American Indian reservations (Cornell,
1993; Cornell, Jorgensen, & Kalt, 2002; Cornell & Kalt, 1992, 1995,1998). Since
its creation in 1986, the Harvard project has been working for and with tribes to
research and document how tribes are building healthy, prosperous Indian nations.
41


Among the key research findings of the Harvard project are: 1) sovereignty
matters, 2) culture matters, and 3) institutions matter. Harvard research has shown
that when tribes exercise sovereignty and manage their own affairs, they
consistently out-perform non-tribal decision-makers.
The effective exercise of sovereignty is manifested in many ways, from
tribal control over resource management and tribally designed economic
development strategies to tribal administration of health care and other social
services.
Culture is also important. Successful tribal economies are based on a
institutions of self-government that enjoy accountability to and legitimacy among
tribal citizens and demonstrate an appropriate cultural match. Cultural match
refers to the match between governing institutions and the prevailing ideas in the
community about how authority should be organized and exercised (Cornell &
Kalt, 1998). Given a diversity of Native cultures and circumstances, tribes are
challenged to equip themselves with institutions (e.g., governance structures,
constitutions, economic systems, etc.) that fit their unique societies (Cornell, 1993).
Institutions are also important considerations. Harvard Project research
consistently finds that
assertions of sovereignty must be backed by capable institutions of
governance for development to take hold.. .Stable political
institutions and policies, fair and independent mechanisms for
dispute resolution, a separation of politics from day-to-day business
management, a capable bureaucracy and a strategic orientation are
42


institutional attributes that help tribes create an environment
conducive to economic development (Cornell & Kalt, 1998, p. 12).
Tribes continue to face many challenges to self-determination
implementation however. Inadequate funding is one of the most commonly cited
barriers (Noren, Kindig, & Sprenger, 1998). Shortfalls in contract support funding
for tribes have been well documented (Adams, 2000; Dixon & Roubideaux, 2001).
To deal with these shortfalls, many tribes have reduced their indirect costs or offset
the shortfall with tribal resources. Understandably, these methods have had
negative effects over the years. Administrative infrastructures have deteriorated,
lack of funding for competitive salaries has prevented them from hiring highly
skilled workers, equipment has not been upgraded, and resources that have been
redirected to shortfalls have reduced program services (Noren, et al., 1998).
Recruitment and retention of professional health care staff continues to be a
commonly cited challenge to self-determination implementation in tribal health
care (Noren, et al., 1998). Many tribes operate in remote, isolated areas with little
access to entertainment, shopping and cultural attractions. Additionally, low rates
of educational attainment and high unemployment rates decrease the probability
that most tribes will have adequate local health care management and provider
expertise (Adams, 2000). Consequently, tribes are faced with recruiting and
retaining health care workers from outside their local areas yet these providers are
often faced with distance from friends and families, lack of adequate housing,
43


excessive working hours, poor local school systems, and inferior pay. The IHS has
attempted to address these staffing issues through incentives such as the Loan
Repayment Program and Title 38 legislation that allows health services centers
greater flexibility in setting pay scales (Kim, 2000). However, tribes are not
eligible for these programs. Consequently, recruitment and retention of skilled
health workers is a common challenge for self-determination tribes.
Diabetes Care Performance
In recent years, much attention in the literature has been concerned with
measuring and improving the quality of care for patients with diabetes (Acton, et
al., 2001; Acton, et al., 1993; Gohdes, et ah, 1996; Grant, et ah, 2005; Keating, et
ah, 2003; Kerr, et ah, 2004; Kim, et ah, 2004; Mayfield, et ah, 1994; McCulloch,
Price, Hindmarsh, & Wagner, 2000; Newton, et ah, 1999; Padgett, Mumford,
Hynes, & Carter, 1988; Quinn, et ah, 2001; Rith-Najarian, et ah, 2002;
Roubideaux, et ah, 2004; Smith, et ah, 1999; Sperl-Hillen, et ah, 2003; Wagner,
1995; Wilson, et ah, 2003). Several national organizations have published
performance indicators (e.g., The American Diabetes Association; The Health Care
Financing Administration; state public health programs). Although most of the
quality of care measures used by the various groups have been similar, there are
enough differences to make comparisons difficult (Acton, et ah, 2001). Therefore,
in 1997 the National Committee for Quality Assurance (NCQA) developed a
44


unified set of performance and outcome measures for diabetes called the Diabetes
Quality Improvement Project (DQIP(Acton, et al., 2001).
The final set of DQIP recommendations includes two sets of measures: an
accountability set and a quality improvement set. The accountability measures
focus on key process outcomes that must be achieved in order to meet performance
objectives. These measures are evidence based, received consensual support from
the scientific and medical community and have been field-tested. The quality
improvement measures are for internal performance information only and are based
on IHS requirements and do not represent key measures that have been confirmed
by the scientific community (Acton, et al., 2001).
The DQIP performance measures are very similar to the Indian Health
Service (IHS) measures. As part of its public health approach to diabetes, the IHS
National Diabetes Program created guidelines to improve the process of diabetes
care and the outcomes for patients with diabetes seen in Federal, tribally operated,
or urban health facilities (Indian Health Indian Health Service, 2004; Zuckerman,
Haley, Roubideaux, & Lillie-Blanton, 2004). These guidelines were formalized to
become the IHS Standards of Care for Diabetes in 1986. Table 2.3 displays a
comparison of the DQIP and IHS diabetes measures. The IHS standards have been
promoted on an ongoing basis by regional diabetes coordinators through the
Federal, tribally operated and urban health centers and significant improvements in
45


diabetes care based on these standards have been demonstrated (Acton, et al.,
1993; Gohdes, et al., 1996; Mayfield, et al., 1994).
46


Table 2.3
DQIP Performance Indicators and Comparable IHS Measures
DQIP Accountability
Measures___________________
1. Percentage of patients
receivings 1 HbA)ctest
per year
2. Percentage of patients
with the highest-risk
HbAic level (i.e., HbAic>
9.5%)
3. Percentage of patients
assessed for nephropathy
4. Percentage of patients
receiving a lipid profile
once in 2 years
5. Percentage of patients
with LDL <3.35 mmol/1
DQIP Quality-Improvement
Measures________________________
1. HbAic levels of all patients
reported in six categories (i.e., <
7.0%, 7.0-7.9%, 8.0-8.9%, 9.0-
9.9%, >10%, none detected)
2. Distribution of LDL values (i.e.,
<2.60,2.60-3.35, 3.36-4.10, >
4.10 mmol/1, no value
documented)
IHS Diabetes Care and Outcome Measures*
Most recent HbAjc in past year or mean value
of three blood glucoses in past year if no
HbAic
Mean blood glucoses are calculated to
estimate HbAic when HbAic unavailable
Urinalysis in past yearproteinuria positive;
microalbumin screen in (-) urinalysis for
negative/unknown proteinuria
Annual cholesterol and triglyceride values
Total cholesterol distribution


Table 2.3 (Cont.)
DQIP Accountability Measures DQIP Quality-Improvement Measures IHS Diabetes Care and Outcome Measures*
6. Percentage of patients with BP < 140/90 mmllg. 3. Distribution of BP values (i.e., < 140, 140-159, 160-179, 180-209, > 209 mmHg systolic; < 90, 90- 99,100-109, 110-110=9, > 119 mmHg, no value documented Mean of last three Bps in the past year
7. Percentage of patients receiving a dilated eye examination Yearly dilated eye examination by experienced provider
4. Proportion of patients receiving a well-documented foot examination to include a risk assessment Yearly foot risk assessment to include neuropathy and vascular status
Source: (Acton, et al., 2001)
*Some of the measures have exclusions based on comorbidity or based on the results from a previous examination. All
measures apply to people with diabetes between 18 and 75 years of age, regardless of type of diabetes. For all measures
requiring a value (e.g., LDL cholesterol and BP), the most recent test result is used.


Even though there are currently no uniform performance measures for
diabetes prevention programs1, research indicates that lifestyle changes can prevent
the onset of type 2 diabetes. The Diabetes Prevention Program (DPP) is a Centers
for Disease Control (CDC) funded, 27-center randomized clinical trial that studied
more than 3,200 adults who were 25 years or older and who were at increased risk
of developing type 2 diabetes. The DPP evaluated the effectiveness of the
following ways to prevent or delay type 2 diabetes: intensive lifestyle modification
(healthy diet, moderate physical activity of 30 minutes a day 5 days a week);
standard care plus the drug metformin; standard care plus placebo (a pill that has no
effect).
This is the first major clinical trial of Americans at high risk for type 2
diabetes to show that lifestyle changes in diet and exercise and losing a little weight
can prevent or delay the disease. Results showed that participants who made
lifestyle changes reduced their risk of getting type 2 diabetes by 58 percent. The
lifestyle intervention was effective for participants of all ages and all ethnic groups.
Participants with standard care plus metformin reduced their risk for getting type 2
diabetes by 31 percent (Centers for Disease Control, 2004; Knowler, et al., 2002).
Therefore, performance measures for diabetes prevention programs should focus on
1 The sample of organizations for proposed study will include organizations implementing diabetes
prevention programs and organizations implementing cardiovascular disease risk reduction program
with diabetics.
49


lifestyle change indicators such as exercise, weight loss, and diet (Knowler, et al.,
2002).
Summary
The effective management of tribal health programs, especially those
focusing on diabetes, is extremely important to the health status of AI/ANs.
Unfortunately, there is a lack of studies focusing on the impact of organizational
factors and managerial practices on the performance of diabetes programs among
AI/ANs. Several organizational effectiveness models hold promise for providing a
viable method of inquiry into the management of tribal diabetes programs. Among
them, the Competing Values Framework is the most efficacious because the CVF
utilizes a configurational view of organizational strategies, structure, and dominant
values to measure effectiveness. Thus, the CVF defines ideal types or
configurations that organizations tend to pursue based on their structure, strategy
and dominant values.
The CVF is not without limitations. The organizational profiles identified
by the model will need to be related to a construct of organizational performance in
order to use the framework as a predictive model.
Applying the Competing Values Framework to organizations implementing
tribal diabetes programs should prove to be helpful for identifying the
organizational factors and management practices that predict effectiveness. These
data could potentially provide tribal leaders and health administrators with
50


worthwhile information and understanding of the roles and capabilities necessary
for effective tribal management of these vital programs.
51


CHAPTER 3
METHODOLOGY
This chapter discusses the methodological and analytical approaches
employed in this thesis including the study design, the hypotheses tested and
variables included in the analyses, a description of the study population and
sample, data collection procedures and the analyses conducted.
Study Design
In order to test the proposed hypotheses, a cross-sectional research design was
employed. A cross-sectional design is one of the most common designs in social
science research. The cross-sectional design is well suited for studies, such as this
study, aimed at determining the prevalence of a phenomenon, situation, problem or
issue, by examining a cross-section of the population (Kumar, 1996). Thus, cross-
sectional studies can provide an overall snapshot of the situation or problem at one
point in time (i.e., the strategic, structural and focus values of effective health
organizations) (Babbie, 1989).
52


Research Questions and Hypotheses
The research questions for this thesis are:
1. What are the dominant organizational effectiveness profiles of organizations
implementing Indian Health Service tribal diabetes programs?
2. Which organizational effectiveness variables are associated with successful
performance among tribal diabetes programs?
3. Are tribes and tribal organizations that exercise self-determination by
managing their own health care more successful in implementing diabetes
programs?
The following research hypotheses direct the investigation of these research
questions:
Hia: Higher scores on organizational effectiveness variables will predict better
program outcomes (recruitment, participation and retention) than lower
organizational effectiveness scores.
Hu,: Individuals within organizations with higher scores on organizational
effectiveness variables will demonstrate better knowledge outcomes
(diabetes knowledge and health literacy) than those within organizations
with lower organizational effectiveness scores, after controlling for the
participants individual level characteristics.
53


H]C: Individuals within organizations with higher scores on organizational
effectiveness variables will demonstrate better lifestyle outcomes (weight
loss, physical activity; consumption of healthy and unhealthy foods) than
those within organizations with lower organizational effectiveness scores
after controlling for the participants individual level characteristics.
Hid: Individuals within organizations with higher scores on organizational
effectiveness variables will demonstrate better clinical outcomes (BP, LDL,
HDL, TGL, HbAlc) than those within organizations with lower
organizational effectiveness scores, after controlling for the participants
individual level characteristics.
Hypotheses la-d relate to the Competing Values Framework of
organizational effectiveness. The developers of the Competing Values
Framework have hypothesized that, in order to be effective, organizations must
score highly on a number of important organizational effectiveness criteria.
These include stability and control; documentation and information
management; human resources; management of individuals, cohesion and
morale; growth and resources acquisition; innovation and adaptation; planning
and goal setting; and productivity (Aram, 1976; Lawrence & Lorsch, 1967a;
Patterson, et al., 2005; Quinn, 1988; Quinn & Kimberly, 1984; Quinn &
Rohrbaugh, 1983)
54


H2a: Organizations exercising self-determination will demonstrate better
program outcomes (recruitment, participation and retention) than IHS
organizations.
H21,: Individuals within organizations exercising self-determination will
demonstrate better knowledge outcomes (diabetes knowledge and health
literacy) than those within IHS organizations after controlling for the
participants individual characteristics.
H2C: Individuals within organizations exercising self-determination will
demonstrate better lifestyle outcomes (weight loss, physical activity,
consumption of healthy and unhealthy foods) than those within IHS
organizations after controlling for the participants individual
characteristics.
H2d: Individuals within organizations exercising self-determination will
demonstrate better clinical outcomes (BP, LDL, HDL, TGL, Ale) than
those within IHS organizations after controlling for the participants
individual characteristics.
Hypotheses 2a-d build upon a number of studies which have focused on the
conditions under which sustained, self-determined social and economic
development and effective healthcare is achieved on American Indian reservations.
These studies have shown that when tribes exercise self-determination and manage
55


their own affairs (Deci & Ryan, 1985; Senecal, et al., 2000; Sheldon, et al., 2003;
Williams, et ah, 1998), they consistently out-perform non-tribal decision-makers
(Cornell, et ah, 2002; Cornell & Kalt, 1992, 1995, 1998). For this study, the
exercise of self-determination is operationalized as a tribe entering into 638
contracting with the IHS or a tribe funding and managing its own health care.
Contracting allows the tribe to assume full responsibility for planning,
conducting, and administering health services, including hiring personnel,
delivering services, record keeping, and other administrative functions. Thus,
tribes were designated as either IHS or self-determination based upon whether
services were provided directly by the IHS or were managed by the tribe, urban
program or non-profit under a contract with IHS.
Study Population/Sample
The study population for this research was organizations that received
funding from the Indian Health Service Special Diabetes Program (SDPI),
Competitive Grant Program to implement preventive programming with pre-
diabetics and diabetics (see Appendix B for a Program Description) and the
individual who participated in these programs. The purpose of the SDPI
Competitive Grants Program is to evaluate a demonstration project to implement a
defined set of activities in each of two intervention areas: primary prevention of
diabetes or prevention of cardiovascular disease in Al with diabetes. There are 36
56


organizations that are implementing primary prevention of diabetes programs and
30 organizations that are implementing cardiovascular disease risk reduction
programs for diabetics. These organizations are Indian Health Service hospitals or
clinics; Federally recognized tribes; Title V Urban Indian Health Programs and a
consortium of any of the above. If the grantee organization represented a
consortium, each organization in the consortium was assessed as a separate
operational entity providing it received funding from the primary grantee and was
not considered to be a satellite site of the primary grantee organization. Including
the additional consortium sites, there were a total of 45 organizations implementing
the diabetes prevention program and 37 organizations implementing the
cardiovascular disease risk reduction program that were included in the study.
Thus, a total of 82 organizations were included in the study.
Organizational Survey Respondents
Because the CVF survey is subjective in nature, researchers who have used
the survey in the past have collected data from the entire staff of the organizations
studied (Rohrbaugh, 1981). However, because of limited resources and grantee
data collection burden, targeting the entire staff population of each organization
was not feasible for this research. Therefore, a purposive sampling strategy of the
staff population at each organization was employed identifying and targeting 10
respondents from each organization for a total of 820 respondents targeted.
57


The SDPI CGP grantee organizations are quite diverse in terms of their
organizational structure, larger institutional contexts and personnel. Therefore, it
was necessary to develop a purposive sampling strategy for each organization
independently. This involved examining the structure of each grantee organization
within its own context to determine in a systematic way the different functional
types of respondents needed within each individual grantee organization to get an
adequate sample. After information was collected from each grantee site regarding
its organizational structure, staffing patterns, and larger institutional context to
determine appropriate sampling strategies, the following functional types were
targeted for the sample: hospital/clinic/department administrators/directors;
medical directors; physicians/care providers; nurses; nurse managers/clinical
coordinators; pharmacists; health educators; nutritionists/dieticians; physical
therapists/exercise physiologists; social workers; project directors/coordinators;
data collection coordinators; lifestyle coaches/case managers; and
clerical/administrative support personnel.
Given that this study was considered part of the evaluation requirements of
the Indian Health Service Special Diabetes Program for Indians, Competitive
Grants Program, a relatively high response rate was expected (approximately 80%).
58


Domains of Measurement
Independent Variables
Based on the Competing Values Framework, a total of eight independent
variables were used as predictors of diabetes program performance. The survey
items and subsequent variables identified in Table 3.1 are from the Competing
Values survey instrument developed by Rohrbaugh (Rohrbaugh, 1981) and have
coefficient alphas ranging from .82 to .87. Table 3.1 displays the independent
variables and corresponding survey item numbers for each variable (see Appendix
A for the survey instrument).
Survey items were scored using 5-point Likert scales whereas 1 = strongly
agree; 2 = agree; 3 = neither agree nor disagree; 4 = disagree and 5 = strongly
disagree. For analytic purposes the scores were reverse coded so that higher scores
represent agreement rather than disagreement.
After data collection, confirmatory factor analysis with varimax rotation
was conducted using SPSS 16.0 to ensure that composite variables were grouping
as designed. Additionally, Cronbachs alpha scores were calculated to ensure scale
reliability. Scales with alphas of > .7 were deemed reliable. Based on factor
loadings identified through the factor analysis, composite variables were created
using the mean of the total respondent scores on each of the eight organizational
effectiveness variables for each organization.
59


Table 3.1
Independent Variables; Survey Items
Independent Variables Survey Items/Factor Loadings
Stability and control -Generally the supervisors plan their work in advance and are well organized (.70) -Our organization has a reputation of not being managed very well (reverse coded) (.60) -Weekly activities are well scheduled in our organization (.57) -Our work efforts during the day are well organized (.45) -There is a feeling of staff cohesion and teamwork (.44) -There is adequate coordination between our jobs (.41) -In this office, it seems to matter if I do a good job (.38) -When change is required, the organization adjusts (.33) -Outsiders respect the quality of our work (.29) Coefficient alpha:. 85
Documentation, information management -My co-workers provide me with good, usable information (.77) -Information given to me by other staff members is usually helpful in my work (.72) -I get useful information from my co-workers (.69) Coefficient alpha:. 85
60


Table 3.1 (Cont.)
Independent Variables Survey Items/Factor Loadings
Management of individuals, cohesion, morale -Employees seem to get along well with each other (.72) -Employees trust each other (.65) -There is an atmosphere of friendship at work (.64) -There are serious conflicts among employees (reverse coded) (.52) Coefficient alpha: .87
Human resources, smooth functioning group -Employees possess skills adequate to their assignments (.68) -Members of the staff are well qualified for their jobs (.63) -Staff members have the capacity to do their work (.52) Coefficient alpha:. 84
Planning and Goal Setting -It is easy to give a precise explanation of the goals of our organization (.64) -Members of our organization have a clear understanding of its goals (62) -The organization has objectives that are very well defined (.60) -It is hard to understand the organizations direction and purpose (reverse coded) (.56) Coefficient alpha:. 85
Productivity and accomplishment -This organization is highly productive (.63) -The volume of work accomplished is quite large (.57) -We deserve a solid reputation for doing our jobs well (.49) -The organization generates a large amount of output (.49) -The work done in the organization is high caliber (.49) Coefficient alpha:. 85
61


Table 3.1 (Cont.)
Independent Variables Survey Items/Factor Loadings
Flexibility, innovation and adaptation -In a crisis we are usually able to get our work done (.69) -We are flexible enough to take on new tasks (.60) -Our responses to emergencies are usually adequate (.56) -We adapt well to new demands on our organization (.55) Coefficient alpha: .86
Growth and resource acquisition -The size of our organization is steadily increasing (.87) -Each year we have a larger staff than the year before (.86) -In terms of the number of personnel, our organization has not been growing recently (reverse coded) (.61) -We keep hiring new employees to fill new positions (.58) Coefficient alpha:. 82
Organization types (IHS vs. self-determination i.e., 638 contracting, urban
and non-profit) were also designated as independent variables and were analyzed
independently of the CVF variables to determine if organization type predicts
diabetes program performance.
Dependent Vari ablets)
Table 5 lists the targeted outcome (dependent) variables for both the
diabetes prevention and cardiovascular disease risk reduction programs. These
outcomes are the performance measures for the Special Diabetes Program for
62


Indians (SDPI) demonstration project. They were identified based on the Diabetes
Quality Improvement Project (DQIP) performance indicators and comparable IHS
diabetes care measures by the SDPI steering committee and data core members.
63


Table 3.2
Special Diabetes Program for Indians, Competitive Grant Program Outcomes by
Program Type
DIABETES PREVENTION DIABETES CARDIOVASCULAR
PROGRAMS RISK REDUCTION PROGRAMS
Program Outcomes
Number of pre-diabetics recruited
Percent of participants to
complete baseline assessment, 16
week intensive activities, post
program assessment, and annual
follow up assessment
Knowledge Outcomes
Post-intervention knowledge
about diabetes and health literacy
Lifestyle Outcomes*
Post-intervention consumption of
healthy foods
Post-intervention consumption of
unhealthy foods
Post-intervention physical
activity (minutes per month)
Program Outcomes
Number of diabetics recruited
Percent of participants to complete
baseline assessment, intensive
activities, and annual follow up
assessment
Knowledge Outcomes
Post-intervention knowledge about
diabetes and health literacy
Lifestyle Outcomes*
Post-intervention consumption of
healthy foods
Post-intervention consumption of
unhealthy foods
Post-intervention physical activity
(minutes per month)_______________
64


Table 3.2 (Cont.)
DIABETES PREVENTION DIABETES CARDIOVASCULAR
PROGRAMS RISK REDUCTION PROGRAMS
Clinical Outcomes *
Post-intervention systolic BP
Post-intervention diastolic BP
Post-intervention LDL
Post-intervention HDL
Post-intervention total cholesterol
Post-intervention triglycerides
Post-intervention waist size
Post-intervention hip size
Post-intervention waist/hip ratio
Post-intervention weight
Post-intervention BMI
Clinical Outcomes*
Post-intervention systolic BP
Post-intervention diastolic BP
Post-intervention LDL
Post-intervention HDL
Post-intervention total cholesterol
Post-intervention triglycerides
Post-intervention waist size
Post-intervention hip size
Post-intervention waist/hip ratio
Post-intervention weight
Post-intervention BMI
Post-intervention HbAlc
*Values for these outcomes were obtained from the follow-up (DP) and annual
(CVD) assessment of core elements. Baseline values were used a covariates in the
regression analyses.
65






Covariates
To establish that the independent variables are truly associated with the
observed effect in the dependent variable, researchers introduce control variables or
covariates. If the introduction of the control variable does not change the original
relationship between the independent and dependent variables, then the claim of
non-spuriousness is strengthened.
Covariates introduced in the multivariate linear and logistic regression and
mixed model, multi-level analyses included participant age, highest level of
education and gender. Additionally, baseline values for all clinical outcomes were
introduced as covariates in the regression models with annual and follow-up values
serving as the dependent variables. This ANCOVA approach is considered to be
superior to creating change scores as dependent variables, which has been criticized
by methodologists because that method assumes the regression slope predicting the
posttest from the pretest to be 1, which is not true for most cases (Rausch,
Maxwell, & Kelley, 2003).
Data Collection Procedures for the Organizational Survey
This study utilized a pencil and paper survey formatted for optiscan data
entry administered to a sample of the general managers, diabetes program managers
and general staff of organizations implementing IHS diabetes programs (10
66


respondents targeted per organization for a total of 820 respondents). Data
collection was conducted by the local data coordinator at each organization.
Survey respondents were asked to provide their title and the name of their
organization but their personal name was not collected. A paragraph explaining this
and the purpose of the study was included as an introduction to the survey (see
Appendix A). Given that this survey asked only about opinions regarding the
respondents organization, and therefore the risk was minimal, consent was not
required per Federal guidelines (45 CFR, Part 46). Also, respondents were
informed that their personal information was kept confidential. Only the primary
investigator had access to disaggregated data. All data were stored in a password
protected, secure database.
The rationale for use of optiscan, paper surveys included the ease of
administration (i.e., no technological expertise was needed), the efficiency of data
collection (i.e., the data were collected by the local data coordinator); ease of data
entry (data were scanned directly into a SAS SQL server) and the continuity of
administration (i.e., all surveys were administered in exactly the same manner).
Surveys were administered and collected by the local data collection
coordinator at each grantee site. Data collection coordinators then sent the optiscan
paper surveys to the SDPI data coordinators at the coordinating center in Denver.
Then data managers scanned the surveys and the data were automatically entered
into a SAS SQL server database and were ready for cleaning and analysis.
67


Data Collection Procedures for SDPI Participant Baseline, Follow-Up and Annual
Assessment of Core Elements
In order to understand whether or not the Intensive Activities helped the
SDPI program participants, their health status was assessed before, during and after
the intervention activities through the administration of a baseline, follow-up (DP
only) and annual assessment of core elements. The baseline assessment was
completed a month prior to the date the participant began Intensive Activities to
ensure that the participants health status did not change prior to initiation. The
Participant Follow-up Assessment Form was scheduled within one month of the
completion of the 16-session DPP Curriculum. Timing for administration of the
annual assessment was as follows:
For DP: The Participant Annual Assessment of Core Elements was
scheduled within one month of the yearly anniversary of the participants first DPP
Curriculum Class. For example, if a participant started the DPP Curriculum in
February 2006, the first Participant Annual Assessment would be scheduled for
February 2007. Subsequent Annual Assessments occurred yearly thereafter.
For CVD: The Participant Annual Assessment of Core Elements was
scheduled within one month of the yearly anniversary of the participant starting the
case management visits. For example, if the participant started case management
visits in February 2006, his/her first Participant Annual Assessment would be
scheduled for February 2007. Subsequent Annual Assessments occurred yearly.
68


In the Diabetes Prevention component, the Intensive Activities consisted of
two major activitiesDPP Lifestyle Balance Curriculum classes and monthly
Lifestyle Coaching. For the purposes of determining when the Baseline
Assessment should be scheduled, the first class of the DPP Curriculum was
considered the first official activity. Lifestyle coaching visits were concurrent with
the curriculum classes and were not started prior to the first class of the DPP
Curriculum.
In the Healthy Heart component, the Intensive Activities primarily
consisted of monthly visits with the case manager. The Intensive Activities also
included teaching the participant about cardiovascular disease risk using the
Honoring the Gift of Heart Health (HGHH) Curriculum.
The baseline, follow-up and annual assessment of core elements were
completed during scheduled appointments. The case manager (CVD) and lifestyle
coach (DP) met with the participant for the appointment and completed the
Assessment of Core Elements forms. This pencil and paper form was not given to
the participantthe form was filled out by the case manager/lifestyle coach and/or
the licensed primary care provider who conducts the physical exam.
For both the DP and CVD projects, the assessment of core elements
included a comprehensive assessment of each participants health at baseline,
follow-up (after intensive activities for DP only) and annually and asks questions
for information about the following general topics:
69


Physical measurements, such as baseline weight and body mass index
Clinical measurements, such as blood pressure
Documentation of a physical exam
Clinical lab test results, such as glucose status and lipids
Health behaviors, such as degree of physical activity, use of journals or
pedometers
Documentation of any education given to the participant about participant
goals in the project
Consent to participate in the Assessment of Core Elements Form was included
in the participants written consent to participate in the program. Once the form
were completed by the case manager or lifestyle coach hard copies of the forms
were de-identified and sent to the coordinating center in Denver for data entry and
analysis.
Validity. Reliability and Limitations
Validity and Reliability of Survey Instrument. In order to maximize the
validity of the instrument, scales with established validity and reliability were used
(i.e., the Competing Values organizational effectiveness measures). In addition,
after data collection, confirmatory factor analysis with varimax rotation was
conducted using SPSS 16.0 to ensure that composite variables were grouping as
70


designed. Cronbachs alpha scores were also calculated to ensure scale reliability.
Scales with alphas of > .7 were deemed reliable.
Statistical Validity. Threats to statistical validity were addressed by
checking the assumptions of the various statistical tests utilized to ensure that none
were violated. All assumptions were met.
Internal Validity. The major threat to internal validity in this study was
inherent in the cross-sectional design. This design cannot capture change over time
and therefore cannot answer questions of causality (Kumar, 1996). Thus, as a
result of the use of a cross-sectional design, no definitive inferences can be made
about a causal relationship between the independent and dependent variables
without controlling for all potential competing explanatory variables.
External Validity. External validity may have been threatened by the fact
that organizations that received a grant through the competitive grant process of the
Indian Health Service Special Diabetes Program for Indians were the focus of this
research. Given that organizations had to compete for this funding and only those
that received high score through the peer review process received funding, the
organizations studied may be more capable organizations than IHS, tribal and
urban Indian health programs in general.
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Data analysis
Following data scrubbing and construction of composite variables,
exploratory analysis was conducted to determine if there were problems with the
data, such as outliers, non-normal distributions, problems with coding and/or errors
in inputting of data, and to check assumptions of linear multivariate and mixed
model regression, such as multicollinearity between independent variables. Where
non-normal distributions were identified (e.g., triglycerides and physical activity),
log transformations were conducted. Additionally, descriptive statistics
(frequencies, means, standard deviations, correlations) were run on all data
collected and are presented in tabular and graphical format in the following chapter.
Inferential Statistics
Figure 3.1 illustrates the analytical framework that was used to guide the
inferential analyses. Analyses were conducted separately for both the DP and CVD
program components for each hypothesis because of variance in program
emphases, goals, and differences in program outcomes between the two SDPI
components.
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Figure 3.1
Analytical Framework for Inferential Analyses
Individual Status
Baseline Status
Knowledge
Lifestyle
Clinical
Covariates
Age
Gender
Education
Organizational Characteristics
Effectiveness Variables
Stability, control
Innovation, Adaptation
Planning, Goal Setting
Documentation,
information management
Growth, Resource
Acquisition
Human Resources
Productivity
Management of
Individuals, Cohesion,
Morale
Organization Type
(IHS vs. Self-
Determination)
I
Outcomes
Individual Outcomes H2b
j Knowledge M
h2c
1 Lifestyle H
H2d
i j ^
Clinical

H,
Program Outcomes Recruitment Retention Il2a




Analyses for H!a: Analyses for recruitment outcomes were conducted at the
organizational level using multiple linear regression with SPSS 16.0. Recruitment
scores (dependent variable) were calculated for each organization (DP: N = 45;
CVD: N = 37) using the total number of baseline assessments received for each
organization.
Multiple linear regression allows the researcher to predict a scale dependent
variable from a combination of several scale and/or dichotomous
independent/predictors variables. Multiple linear regression was conducted for Hia
to determine the best linear combination of stability and control, information
management, cohesion/morale, human resources, planning, productivity, flexibility,
and growth and resource acquisition for predicting the program outcomes for
recruitment and participation. Regression analysis was conducted with an alpha of
.05. The regression equation for the multiple regression analyses was as follows:
y ~fio ~fi\Xl +J32X2 + fiXl + + fJyXj +fi-]X7+fi% Xfi+fiq X9 +fi\o X10X12
+ 8
whereas: fio = intercept; fi\ = slope; Xi -X# = CVF variables; Xio -Xn = covariates
and s = error
Analyses for retention were conducted using multiple linear regression.
Retention scores for organizational level analyses were calculated using the percent
of individuals retained at follow-up assessment for DP and at annual assessment for
CVD for each organization.
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Analyses for H\b, Hic, and Hid'. Analyses for these hypotheses were
conducted using hierarchal linear modeling (HLM), also known as multi-level
analysis. Multi-level analysis is an advanced form of multiple linear regression. It
allows variance in outcome variables to be analyzed at multiple hierarchical levels,
whereas in simple linear and multiple linear regression all effects are modeled to
occur at a single level. Thus, HLM is appropriate for use with nested data, such as
individual participants who are nested within an SDPI grantee organization.
There are several statistical and conceptual advantages in using multi-level
analysis. First, variables are analyzed at the level that they were defined and
measured. For example, if blood pressure is measured at the individual level, it is
theoretically correct to analyze the variable at the individual level not at the higher
institutional level (Cho, 2003; Nezlek, 2008; Sullivan, Dukes, & Losina, 1999).
Thus, the traditional approach of aggregating individual level data at the higher
level and/or creating dummy variables for each level 2 unit at level 1 can be
avoided.
Statistical literature has reported several problems related to aggregated
data, such as the ecological fallacy. The ecological fallacy occurs when
relationships between variables are examined using aggregated data at the group
level but conclusions are drawn at the individual level (Cho, 2003). The problem
of shift of meaning can also occur with aggregated data. Shift of meaning refers
to the issue when a variable of individuals is aggregated to the group level, the
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meaning of the variable does not directly refer to the individual but rather to the
group (Snijders & Bosker, 1999).
Problems with using the dummy variable approach have also been reported.
Using this approach one rapidly gets an unmanageable number of variables when
the number of units is large. One also does not get any information about the
overall variation between level 2 units which is often referred to as the atomistic
fallacy Additionally, when there are natural clusters in the data, standard errors
are underestimated and there is a greater risk for errors in hypothesis testing
(Snijders & Bosker, 1999).
Given that data for this study are hierarchal in nature (i.e., individuals
nested with health care organizations) two-level multilevel modeling was used to
conduct analyses for all individual level outcome data using SAS Proc MIXED
statistical software (SAS Institute, 2008).
Analyses for fya, H2b, fyc, H2d'- In order to test these hypotheses,
organizations were first designated as either IHS, tribal, urban or non-profits.
Organizational survey respondents were asked to choose one of the following
organizational types when completing the survey: 1) IHS hospital or clinic; 2)
tribe/tribal organization/tribally run hospital or clinic; 3) Title V Urban Indian
program; or 4) non-profit. However, there was inconsistency in the responses to
this question by survey respondents. After consultation with the SDPI program
director, it was agreed that the organization type listed by the SDPI program
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manager at each organization would be used as the organization type. However,
after these determinations were made, the sample sizes among the different types
were too small for meaningful analysis. Therefore, the decision was made to
aggregate the types into only two designations either IHS or self-determination
(i.e., 638, urban, non-profit, and tribal) and combine the DP and HH datasets to
increase the sample size. Thus, 19 sites designated as IHS sites were compared to
63 sites designated as self-determination sites in the analyses.
Analyses for these hypotheses included comparing IHS to self-
determination organizations in their performance on the program, knowledge,
lifestyle and clinical outcomes. Mixed model, multi-level regression analyses were
conducted using organization type (a dichotomous variable in which IHS was
coded as 0 and self-determination was coded as 1) as the predictor to test the
program outcomes (i.e., recruitment and retention at the organization level);
knowledge outcomes (i.e., diabetes knowledge and health literacy); lifestyle
outcomes (i.e., physical activity, consumption of health and unhealthy foods) and
clinical outcomes. Gender, age and education levels of individual participants were
used was covariates in the models.
77


Human Subjects Protection
A human subjects protocol application was submitted to the Colorado
Multiple Institutional Review Board (COMIRB) for review and approval since this
project was conducted under the auspices of the University of Colorado Health
Sciences Center, School of Medicine, Department of Psychiatry, American Indian
and Alaska Native Programs. The University of Colorado at Denver (UCD) IRB
accepts COMIRB approval of protocols.
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CHAPTER 4
RESULTS
This chapter presents the results for this study aimed at determining if
higher organizational effectiveness score predict the success of tribal diabetes
programs. The sample characteristics are presented first and include characteristics
for the organizations implementing the diabetes programs, the respondents of the
organizational survey and the diabetes program participants. Next, the
organizational survey characteristics are presented including validity and reliability
testing results. The independent, dependent and control variable characteristics are
presented next and includes frequencies, distributions and correlations for each
variable type. Finally, the results for the hypothesis testing are provided.
Sample Characteristics
Special Diabetes Program for Indians, Demonstration Project, Grantee
Organizations.
The 82 organizations participating in this study represent organizations that
are receiving funding from the Indian Health Service (IHS) Special Diabetes
Program for Indians Demonstration Project through a competitive grant process.
Through these grants, the organizations implement either diabetes prevention (DP)
79


programs (N = 45) or cardiovascular disease risk reduction (CVD) programs with
individuals who have already been diagnosed with diabetes (N = 37). These
organizations are located in 19 different states across the nation spanning from
Alaska to New York. The communities served by these organizations are diverse
in regard to their cultural and geographical environments with most of them serving
a distinct, American Indian or Alaska Native tribal group. There are four different
types of organizations represented: 1) IHS clinics or hospitals; 2) tribal programs
which include tribally owned and operated hospitals and clinics and tribally
managed health care facilities that receive funding through IHS contracts and
compacts; 3) urban Indian programs; and 4) non-profit organizations serving
AI/AN populations. Table 4.1 lists the DP and CVD organizations by type based on
the SDPI program managers designations.
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Table 4.1
Organization Type (N = 82)
CVD DP
Organization Type Organization Type
IHS 14 IHS 5
Tribe/tribal organization/tribally run hospital or clinic 19 Tribe/tribal organization/tribally run hospital or clinic 35
Urban 2 Urban 5
Non-Profit 2 Non-Profit 0
Total 37 45
The SDPI grantee organizations are also diverse in regard to their size and
structure. The diabetes prevention program organizations range from one to 900
employees and have annual operating budgets ranging from $150,000 to
$90,000,000. The CVD programs range from one to 999 employees and have
annual operating budgets ranging from $142,000 to over $89,000,000. Additional
organizational characteristics of the organizations participating in this study are
provided in Tables 4.2 and 4.3.
81