The growth of pharmaceutical expenditure and its prediction is a major concern for policy makers and health care 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.
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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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0099, Boston University - Industry Studies Programme.