Chile´s primary health care (PHC) payment system uses income of the municipalities and the geographic location of health centres (HCs) to adjust current capitation payments. Concerns over the ability of the formula to direct health resources where greater health needs are discussed. We uses a sample of 10,000 individuals was drawn and two years data was collected from a region in Chile. Three models were tested: i) age and gender, ii) age, gender and the presence of two key diagnoses and iii) age, gender and the presence of seven key diagnoses, to estimate how significant their effects were on utilization and per-capita expenditures. Regression analysis was performed to calculate the predictive values of the independent variables and two tests applied to select the best and next best model. The main results are the following. First, the use of services by age and gender confirmed international trends, where children under five, women and elderly were the main users of PHC services. Second, women consulted twice as much as men. Thrid, clear difference by SES were observed, indigents aged 65+ under-utilised PHC services. From the three models simulated, the major improvement in the predictive power took place from the demographic to the demographic plus two diagnoses model. Improvements were limited when five other diagnoses were added (Rsquare= 28%). The conclusion is that the current normative formula used by the MOH provides little incentives to care appropriately for indigents and people with chronic conditions such as diabetes and hypertension. A capitation payment that adjusts for age, gender, and presence of hypertension and diabetes will better guide resources to those with poorer health and lower SES. Keywords: Primary health care, Payment system, Risk adjustment
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Arlene Ash & Randall P. Ellis & Gregory Pope & John Ayanian & David Bates & Helen Burstin & Lisa Iezzoni & Elizabeth McKay & Wei Yu, 2000.
"Using Diagnoses to Describe Populations and Predict Costs,"
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