title: Predictability of prescription drug expenditures for Medicare beneficiaries.
abstract: MCBS data are used to analyze the predictability of drug expenditures by Medicare beneficiaries. Predictors include demographic characteristics and measures of health status, the majority derived using CMS' diagnosis cost group/hierarchical condition category (DCG/HCC) risk-adjustment methodology. In prospective models, demographic variables explained 5 percent of the variation in drug expenditures. Adding health status measures raised this figure between 10 and 24 percent of the variation depending on the model configuration. Adding lagged drug expenditures more than doubled predictive power to 55 percent. These results are discussed in the context of forecasting, and risk adjustment for the proposed new Medicare drug benefit.
authors.affiliation: University of Pennsylvania School of Medicine, USA. marian_wrobel@abtassoc.com
authors.forename: Marian V
authors.initials: MV
authors.lastname: Wrobel
authors.forename: Jalpa
authors.initials: J
authors.lastname: Doshi
authors.forename: Bruce C
authors.initials: BC
authors.lastname: Stuart
authors.forename: Becky
authors.initials: B
authors.lastname: Briesacher
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003625:Data Collection; D011307:Drug Prescriptions / Q000191:economics* / Q000706:statistics & numerical data; D004363:Drug Utilization / Q000191:economics*; D018588:Fee-for-Service Plans / Q000706:statistics & numerical data; D005260:Female; D005544:Forecasting; D005102:Health Expenditures / Q000706:statistics & numerical data / Q000639:trends*; D006801:Humans; D007356:Insurance, Pharmaceutical Services / Q000706:statistics & numerical data*; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data*; D015233:Models, Statistical; D014481:United States