Time Series Modeling of Trends in Medication Prescribing

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DESCRIPTION: Physician decisions regarding medication prescribing have a large impact on health care costs and clinical outcomes. Surprisingly little is known, however, about the relative impact of a range of factors that may influence physician behavior in the prescribing of medications. By extension, the ability to explain and project trends in medication prescribing is currently limited. This study will develop a novel economic model of the simultaneous influence of multiple determinants on trends in medication prescribing. Econometric time-series regression techniques will be used to estimate the relative influence of temporally varying predictor variables and discrete temporal events on observed national trends in the prescribing of pharmaceuticals for hypertension, depression, asthma, and congestive heart failure. Nationally representative quarterly data on 1978 through 2000 trends in drug prescribing for these conditions will come from the National Disease and Therapeutic Index survey available through IMS Health. Quarterly patient sample sizes in 1998 are about 1,700 for depression, 550 for congestive heart failure, 5,100 for hypertension and 2,000 for asthma. Data on potential predictors of trends will be developed from a variety of sources. Drug-specific trend information on pharmaceutical promotion and wholesale drug prices also will be available from IMS Health. Other predictors will include information on drug dosing, other drug characteristics, clinical trial results publication, media reporting on medications, and clinical guideline publication. By constructing a comprehensive model of the temporal determinants of prescribing behavior, this study will assess the relative influence of these factors. Econometric time series regression models built on the theory of demand for differentiated products will be employed to test specific hypotheses regarding the role of these factors. A key hypothesis will be that promotional influences are more potent than scientific influences. In addition, the research will evaluate hypotheses related to the influence of drug prices, the interaction of science and promotion, and the impact of brand name expiration. Results from the analysis will be relevant to efforts to design and implement clinical and health policies to encourage the effective and cost-effective use of medications.