title: Comparison of risk-adjustment systems for the medicaid-eligible disabled population.
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).
  
  
  METHODS
  This was a retrospective cohort.
  
  
  METHODS
  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.
  
  
  METHODS
  Data were from the Ohio Medicaid eligibility and fee-for-service claims files.
  
  
  METHODS
  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.
authors.affiliation: Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA. spayne@usm.maine.edu
authors.forename: S M
authors.initials: SM
authors.lastname: Payne
authors.forename: R D
authors.initials: RD
authors.lastname: Cebul
authors.forename: M E
authors.initials: ME
authors.lastname: Singer
authors.forename: J
authors.initials: J
authors.lastname: Krishnaswamy
authors.forename: K
authors.initials: K
authors.lastname: Gharrity
mesh_terms: D000293:Adolescent; D000328:Adult; D002204:Capitation Fee / Q000706:statistics & numerical data*; D002648:Child; D002675:Child, Preschool; D015331:Cohort Studies; D006233:Persons with Disabilities / Q000706:statistics & numerical data*; D004608:Eligibility Determination / Q000191:economics*; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D008329:Managed Care Programs / Q000191:economics; D008484:Medicaid / Q000191:economics*; D008875:Middle Aged; D009820:Ohio; D012189:Retrospective Studies; D020379:Risk Adjustment; D014481:United States