Estimates of preventive versus nonpreventive medical care demand in an HMO.
Multiple regression analysis is used to investigate whether medical services in a large HMO are distributed primarily on the basis of need and predisposing factors (such as health status, age and sex) or according to enabling characteristics (such as coinsurance and income) of the population. Equations are formulated to estimate the likelihood and volume of preventive visit demand, nonpreventive visit demand and hospital admissions for a sample of 3,892 individuals enrolled in the Kaiser Foundation Health Plan of Portland, Oregon. The results indicate that predisposing and need factors are the main determinants of nonpreventive visits and hospital utilization, while enabling characteristics are important determinants (along with age and education) of preventive utilization. There are marked differences in the impact of explanatory factors on utilization by dependents (children) versus nondependents (adults).
D000328:Adult; D000367:Age Factors; D002648:Child; D003669:Deductibles and Coinsurance; D005260:Female; D006279:Health Maintenance Organizations / Q000706:statistics & numerical data*; D006285:Health Planning; D006297:Health Services Accessibility; D006301:Health Services Needs and Demand; D006761:Hospitals / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D009922:Oregon; D011314:Preventive Health Services / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012737:Sex Factors; D012959:Socioeconomic Factors