title: Taking health status into account when setting capitation rates: a comparison of risk-adjustment methods.
abstract: OBJECTIVE
  To compare performance of different health status measures for risk-adjusting capitation rates.
  
  
  METHODS
  Cross-sectional study. Health status measures derived from 1 year were used to predict resources for that year and the next.
  
  
  METHODS
  Group-network health maintenance organization in Minnesota.
  
  
  METHODS
  Sample of 18- to 64-year-old (n=3825) and elderly (aged > or = 65 years; n=1955) members enrolled in a network-model health maintenance organization in Minnesota.
  
  
  METHODS
  Total expenditures in the year concurrent with the health status survey (July 1991 through June 1992) and total expenditures in the year following the survey (July 1992 through June 1993).
  
  
  RESULTS
  Capitation adjustment based on demographic measures performed least well. Both self-reported health status measures and diagnoses predicted future expenditures twice as well as demographics. When predicting costs for groups of patients rather than individuals, the demographic model worked well for average groups but tended to overpredict healthier groups and underpredict sicker groups. Ambulatory Care Groups based on diagnoses performed better than self-reported health status both in the retrospective models and across healthier and sicker groups.
  
  
  CONCLUSIONS
  Without risk adjustment, capitation rates are likely to overpay or underpay physicians for certain patient groups. It is possible to improve prediction using health status measures for risk adjustment. When selection bias is suspected and administrative data are available, we recommend a risk-adjustment method based on diagnostic information. If diagnostic data are not available, we recommend a system based on simple self-reported measures, such as chronic conditions, rather than complex functional status measures.
authors.affiliation: Health Research Center, Institute for Research and Education, HealthSystem Minnesota, Minneapolis 55416, USA.
authors.forename: J B
authors.initials: JB
authors.lastname: Fowles
authors.forename: J P
authors.initials: JP
authors.lastname: Weiner
authors.forename: D
authors.initials: D
authors.lastname: Knutson
authors.forename: E
authors.initials: E
authors.lastname: Fowler
authors.forename: A M
authors.initials: AM
authors.lastname: Tucker
authors.forename: M
authors.initials: M
authors.lastname: Ireland
mesh_terms: D000328:Adult; D000368:Aged; D002204:Capitation Fee; D002908:Chronic Disease; D003430:Cross-Sectional Studies; D003710:Demography; D003953:Diagnosis-Related Groups / Q000191:economics; D005102:Health Expenditures; D006279:Health Maintenance Organizations / Q000191:economics; D006302:Health Services Research; D006304:Health Status; D006801:Humans; D008875:Middle Aged; D012189:Retrospective Studies; D018570:Risk Assessment; D014481:United States