title: Adjusting employer group capitation premiums by Community Rating by class factors.
abstract: Community rating of employer group health maintenance organization (HMO) capitation premiums results in low premiums for some groups and high premiums for other groups, as compared with the marginal costs of providing services. In effect, low health risk groups are cross subsidizing high health-risk groups in an HMO. This has caused several inefficiencies in the health plan marketplace, which have directly benefited higher-risk groups. For this reason, certain low-risk groups are searching for new strategies to improve market efficiency. One strategy is Community Rating by Class (CRC), a system which adjusts community rated capitation premiums by broad-based risk factors. This article examines CRC as a strategy to help reduce the inefficiencies caused by current federal regulations. In regressions predicting future year total family health expenditures, the CRC Model achieved an R2 value of 0.211. This value was over half the R2 value of an experience rated approach, based on prior year utilization and expenditure variables. Family size accounted for 80% of the variance explained by the CRC Model. The results indicate that the CRC rating approach may be a good mechanism to correct for cross subsidization of employer group capitation premiums.
authors.affiliation: Department of Health Services, School of Public Health, University of California, Los Angeles 90024.
authors.forename: D G
authors.initials: DG
authors.lastname: Cave
authors.forename: S O
authors.initials: SO
authors.lastname: Schweitzer
authors.forename: P A
authors.initials: PA
authors.lastname: Lachenbruch
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D002140:California; D002204:Capitation Fee; D002648:Child; D002675:Child, Preschool; D003365:Costs and Cost Analysis; D005190:Family; D005249:Fees and Charges; D005260:Female; D006264:Health Benefit Plans, Employee / Q000191:economics*; D005102:Health Expenditures / Q000706:statistics & numerical data; D006279:Health Maintenance Organizations / Q000191:economics* / Q000706:statistics & numerical data; D006801:Humans; D007223:Infant; D015273:Insurance Selection Bias; D007348:Insurance, Health / Q000191:economics*; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D012044:Regression Analysis; D012307:Risk Factors