Predictability of drug expenditures: An application using morbidity data
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.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Puig-Junoy, Jaume, 2004. "Incentives and pharmaceutical reimbursement reforms in Spain," Health Policy, Elsevier, vol. 67(2), pages 149-165, February.
- Van de ven, Wynand P.M.M. & Ellis, Randall P., 2000. "Risk adjustment in competitive health plan markets," Handbook of Health Economics,in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 14, pages 755-845 Elsevier.
- Lamers, Leida M. & van Vliet, Rene C. J. A., 2004. "The Pharmacy-based Cost Group model: validating and adjusting the classification of medications for chronic conditions to the Dutch situation," Health Policy, Elsevier, vol. 68(1), pages 113-121, April.
- Coulson, N. Edward & Stuart, Bruce, 1992. "Persistence in the use of pharmaceuticals by the elderly : Evidence from annual claims," Journal of Health Economics, Elsevier, vol. 11(3), pages 315-328, October.
- 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," Papers 0099, Boston University - Industry Studies Programme.