Literature DB >> 10752974

Comparison of risk-adjustment systems for the medicaid-eligible disabled population.

S M Payne1, R D Cebul, M E Singer, J Krishnaswamy, K Gharrity.   

Abstract

OBJECTIVE: The objective of this study was to compare 2 approaches for subjecting capitation rates for disabled Medicaid-eligible patients in managed care plans to risk adjustment, the Disability Payment System (DPS) and the Ohio Prior Expenditure System (OPES).
DESIGN: This was a retrospective cohort. SETTING AND
SUBJECTS: The subjects were 157,142 nonelderly disabled individuals eligible for > or =1 month during state fiscal year 1995 (SFY95) for a 3-county Ohio Medicaid managed care demonstration project. DATA SOURCE: Data were from the Ohio Medicaid eligibility and fee-for-service claims files. ANALYSIS: As per OPES policy, individuals were classified by the duration of their eligibility in SFY93 as "old" eligibles (> or =6 months) or "new" eligibles (<6 months). Published relative payment weights for each system were adjusted and used to predict SFY95 expenditures in a budget-neutral comparison. Measures were variance in SFY95 expenditures explained by predicted payments (R2) and predictive ratios (predicted payment/actual SFY95 expenditure). Individuals with HIV/AIDS and hematological conditions, who enrolled disproportionately across the demonstration counties, were analyzed separately.
RESULTS: Of the 157,142 individuals, 56.4% were new eligibles; 40.1% of the old eligibles had no claims-documented chronic disease diagnosis in the baseline year. The overall R2 was 0.091 with OPES and 0.057 with DPS. Neither system predicted >1% of individual-level expenditures for new eligibles. OPES severely underpaid for eligibles in the top percentile of predicted expenditures; DPS had mixed results. DPS predicted SFY95 expenditures substantially better than OPES for the enrollment bias categories.
CONCLUSIONS: Before Medicaid programs move to full-risk capitation for disabled populations, better risk-adjustment methods are needed, especially for eligible patients with little claims experience, high predicted expenditures, or enrollment-bias conditions.

Entities:  

Mesh:

Year:  2000        PMID: 10752974     DOI: 10.1097/00005650-200004000-00009

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  3 in total

1.  Disease burden profiles: an emerging tool for managing managed care.

Authors:  Yang Zhao; Arlene S Ash; Randall P Ellis; James P Slaughter
Journal:  Health Care Manag Sci       Date:  2002-08

2.  Honesty as good policy: evaluating Maryland's Medicaid managed care program.

Authors:  Debbie I Chang; Alice Burton; John O'Brien; Robert E Hurley
Journal:  Milbank Q       Date:  2003       Impact factor: 4.911

3.  Managed care for the Medicaid disabled: effect on utilization and costs.

Authors:  R D Cebul; I Solti; N H Gordon; M E Singer; S M Payne; K A Gharrity
Journal:  J Urban Health       Date:  2000-12       Impact factor: 3.671

  3 in total

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