Date of Award

Spring 2001

Document Type


Degree Name

Doctor of Philosophy (PhD)


Urban Services--Health Services

Committee Director

Betty Alexy

Committee Member

Michael J. Doviak

Committee Member

Clare Houseman


Since 1863, outcomes measurement efforts have provided information to health care consumers, administrators, and policymakers in assessing concerns about access, quality and costs. With a growing population of older adults with chronic illnesses, cost-cutting strategies in health delivery systems, and federal endorsement of managed care systems, researchers have begun to evaluate the impact of different delivery system organizations on health. The current study combines two areas of health services research to provide the first published hierarchical analysis of the influence of delivery system factors, and a profile of population and community characteristics and utilization factors, on perceived health outcomes of a nationally representative sample of older adult Medicare beneficiaries with various chronic illnesses.

This study was designed to analyze the difference in health status outcomes across Medicare fee-for-service and health maintenance organization systems nationwide, and to explain health delivery system factors' effects on outcomes. Using a recently developed health outcomes classification scheme, a newly expanded Andersen and Aday Health System Model, and hierarchical multiple regression analysis methodology, health delivery system factors were found to have a significant impact on three of four client-centered outcome measures.

The results of this study suggest there are health delivery system factors affecting health outcomes of older adults with chronic illnesses. In addition, the findings imply that hierarchical regression analysis is a useful tool for explaining the unique contribution of several individual variables as well as several blocks of variables on perceived health outcomes. Information from this study can be used to monitor outcomes of health care in this vulnerable population, inform development of chronic illness-related health policy, and encourage use of high quality public data resources available for health services research.