title: Enrollment choices in different types of HMOs: a multivariate analysis.
abstract: Enrollment decisions of a sample of an employed population choosing among open-panel and closed-panel HMOs and Blue Cross/Blue Shield are analyzed. This report, unlike previous ones, overcomes some of the difficulties of bivariate analysis by the use of the multivariate logistic probability model, logit. The results show that there are four consistent predictors of enrollment choice: previous source of care as the measure of access; family life stage and chronic conditions per family member as indicators of health risk; per capita income as the measure of economic vulnerability; and health concern. Having a private physician as the source of care is the best single predictor, its absence predicting a higher probability of enrollment in the closed, and its presence in the open-panel HMO. Higher risk life stage families, younger and with more children, are more likely to join the open-panel plan than the closed or retain BC/BS; higher incomes and larger numbers of chronic conditions appear to have the same effects. Higher levels of health concern, on the other hand, predict a greater probability of choosing the closed-panel plan. The probability of enrollment in any HMO is predicted with more than 50 per cent accuracy for 60 per cent of the sample. Choice between open and closed-panel plans is predicted with an accuracy in excess of 50 per cent for 80 per cent, and with an accuracy greater than 90 per cent for over 10 per cent of potential enrollees. The applicability of this approach to HMO feasibility analysis and planning is clearly indicated.
mesh_terms: D000704:Analysis of Variance; D054598:Blue Cross Blue Shield Insurance Plans / Q000706:statistics & numerical data; D002755:Choice Behavior; D006264:Health Benefit Plans, Employee / Q000706:statistics & numerical data*; D006279:Health Maintenance Organizations / Q000458:organization & administration / Q000706:statistics & numerical data*; D006801:Humans; D007348:Insurance, Health / Q000706:statistics & numerical data*; D009518:New York