Data driven decision making to control pharmacy costs
Inpatient and Ancillary Services
Manager for Pharmacy Quality and Information Systems
James A Haley VAH
The session will describe factors that increase the cost of pharmaceuticals in the U.S. and how data mining and a data warehouse can be used with other techniques to minimize drug costs. This particular section will focus on the use of data systems.
The U.S. currently spends over 16 percent of its gross domestic product on health care. This is likely increase to over 20 percent by the end of the decade with prescription drugs being a significant factor in health care expenses. The percentage increase in medication cost has been in the double digits since the early 1990s. To control rising drug costs, health care organizations have formed pharmacy benefits management groups (PBM). Unfortunately, the tools available to the pharmacists providing pharmacoeconomic services are often limited to literature reviews and medication use evaluations (MUE). Literature reviews on newer agents often contain conflicting information and MUEs are a time-consuming process, taking up to three months. Data mining offers an opportunity for PBMs to enhance their ability to insure optimum pharmaceutical care. Optimum performance does not necessarily mean using the cheapest drug, but those that provide the best value, i.e best therapeutic outcome for minimal cost. Our organization has set up a data warehouse which has over 25 million records including drug, patient demographic, and laboratory data. Formulary policy decisions based on data mining have saved the organization over $500,000 per year and have been used to evaluate both medication safety and efficacy.