3248.0: Monday, November 13, 2000 - 8:50 PM

Abstract #11890

Risk adjustment of capitation payments for Medicaid HIV enrollees

S. Hamid Fakhraei, PhD1, John J Kaelin, MPA1, and Richard Conviser, PhD2. (1) Center for Health Program Development & Management, University of Maryland Baltimore County, Social Sciences 309, 1000 Hilltop Circle, Baltimore, MD 21250, (410)455-6860, fakhraei@chpdm.umbc.edu, (2) HIV/AIDS Bureau, Health Resources & Services Administration, Office of Science & Epidemiology, 5600 Fishers Lane, Room 7C-07, Rockville, MD 20857

Although Maryland's Medicaid program has an AIDS-specific capitation rate, persons living with HIV (PLWH) are included in the general risk-adjusted rates. However, care costs are as variable among PLWH as in the AIDS population; 10% account for more than 50% of total payments. There are concerns that managed care organizations (MCOs) are incurring financial losses from PLWH, potentially compromising access to quality care. Treatment of comorbidities accounts for some of the variation in costs among PLWH; this study examines which specific comorbidities are important contributors to these costs. Diagnoses and drug codes used to identify PLWH eligible for enrollment in managed care in Maryland's Medicaid program yielded 4,382 in FY 96 and 4,136 in FY 97. Their cost data were used to determine which comorbidity diagnoses should be included in a statistical model. Some comorbidities were excluded; the others were grouped according to cost. Among the most costly comorbidities for PLWH were these diagnoses: lymphosarcoma and reticulosarcoma, lymphoid leukemia, non-bacterial meningitis, acute and sub-acute endocarditis, bronchopneumonia, and pneumonia in cytomegalic inclusion disease. We classified individuals in high and low cost groups to simulate biased selection in MCOs. For each group we compared predicted with actual capitation payments and the actual costs under the fee-for-service system. The model closely matched payments with the actual costs of care. Capitation payments based on this model will do a better job than traditional risk adjustment methods of protecting MCOs with disproportionate shares of HIV/AIDS enrollees from adverse financial risk.

Learning Objectives: At the end of this presentation, participants will be able to identify high cost HIV comorbidities, and to evaluate different methods of risk adjustment of payments

Keywords: Medicaid, Economic Analysis

Presenting author's disclosure statement:
Organization/institution whose products or services will be discussed: Center for Health Program Development & Management University of Maryland Baltimore County
I have a significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.
Relationship: employment

The 128th Annual Meeting of APHA