Examining Costs of Chronic Conditions In a Medicaid Population


Purpose: To compare health care costs and their components in patients with chronic illnesses.

Design: Quasi-experimental retrospective database analysis of an integrated state-Medicaid dataset.

Methods: Nine chronic illnesses and 28 two-disease combinations were evaluated in 284,060 patients. Dependent variables were total cost and the component costs (hospital, physician, home health and medical supplies, and pharmacy). Statistical analysis included analysis of variance (ANOVA) and multiple analysis of variance (MANOVA).

Results: The nine chronic illnesses studied were: psychosis, depression, cardiovascular illness, congestive heart failure, diabetes, acid peptic illness, respiratory illness/ asthma, hypertension, and anxiety. Psychosis and depression patients had the highest mean yearly costs at $6,964 and $5,505, respectively. Highest component costs were mental health practitioners for psychosis and hospital costs for depression. All other conditions had significantly lower yearly costs. Component costs consisted primarily of pharmacy and hospital costs. Psychosis was a component in 5 of the 7 most costly chronic-disease concurrences. The highest disease-concurrence mean cost was for psychosis and depression ($18,318).

Conclusions: The unique resource needs of different chronic illnesses should be considered in benchmarking and evaluating chronic-disease management programs.

Key terms: comorbidity, Medicaid program, disease management, cost analysis.

Author correspondence:
Robert I. Garis, RPh, PhD
Creighton University
School of Pharmacy and Allied Health Professions
Omaha, NE 68178
E-mail: [email protected]

Sources of financial support: This manuscript was written while the corresponding author was a graduate student at the University of Oklahoma, School of Pharmacy. The work was supported by the University of Oklahoma, the American Foundation for Pharmaceutical Education, and a grant from the Graduate Student Association of the University of Oklahoma.

This paper has undergone peer review by appropriate members of Managed Care’s Editorial Advisory Board.