Predictability of drug expenditures: an application using morbidity data.
The growth of pharmaceutical expenditure and its prediction is a major concern for policymakers and healthcare managers. This paper explores different predictive models to estimate future drug expenses, using demographic and morbidity individual information from an integrated healthcare delivery organization in Catalonia for years 2002 and 2003. The morbidity information consists of codified health encounters grouped through the Clinical Risk Groups (CRGs). We estimate pharmaceutical costs using several model specifications, and CRGs as risk adjusters, providing an alternative way of obtaining high predictive power comparable to other estimations of drug expenditures in the literature. These results have clear implications for the use of risk adjustment and CRGs in setting the premiums for pharmaceutical benefits.
García-Goñi
Manuel
M
Departamento de Economía Aplicada II, Universidad Complutense de Madrid, Madrid, Spain. mggoni@ccee.ucm.es
Ibern
Pere
P
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D003710:Demography; D016527:Drug Costs / Q000706:statistics & numerical data*; D005260:Female; D006304:Health Status; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D018570:Risk Assessment; D013030:Spain; D013222:State Medicine / Q000191:economics* / Q000706:statistics & numerical data*