A dataset quantifying polypharmacy in the United States

Abstract

Polypharmacy is increasingly common in the United States, and contributes to the substantial burden of drug-related morbidity. Yet real-world polypharmacy patterns remain poorly characterized. We have counted the incidence of multi-drug combinations observed in four billion patient-months of outpatient prescription drug claims from 2007-2014 in the Truven Health MarketScan® Databases. Prescriptions are grouped into discrete windows of concomitant drug exposure, which are used to count exposure incidences for combinations of up to five drug ingredients or ATC drug classes. Among patients taking any prescription drug, half are exposed to two or more drugs, and 5% are exposed to 8 or more. The most common multi-drug combinations treat manifestations of metabolic syndrome. Patients are exposed to unique drug combinations in 10% of all exposure windows. Our analysis of multi-drug exposure incidences provides a detailed summary of polypharmacy in a large US cohort, which can prioritize common drug combinations for future safety and efficacy studies.

Figure 1. Data analysis workflow to generate drug combination exposure incidences from prescription drug claims.

Prescription drug claims (a) are scanned to create discrete exposure windows (c) for the set of drugs (b). These windows are summarized to produce ‘exact’ exposure incidences at the drug ingredient level (d). This table is the substrate for counting the incidence of exposure to ‘at least’ drug combinations (e). Exposure counts for combinations of N=1 to 5 drug ingredients are published in Data Record 1. Exact drug ingredient combinations (d) are translated to drug class combinations (f), keeping only unique classes. Again, these are used to count the exposure incidence of ‘at least’ drug class combinations (g). Exposure counts for combinations of N=1 to 5 drug classes are published in Data Record 2.

Figure 2. Illustration of conversion of drug prescription date of service and days of supply into discrete exposures.

(a) Shows three typical prescription patterns, converted to exposure in three windows, using non-overlapping 30-day windows. (b) Shows uncommon prescription patterns that introduce error in interpretation of concomitant exposure: While A and B are separated by only a few days, and may be considered concomitant, they are not counted as concomitant exposures; While Drugs C and D are separated by many days, they are recorded as concomitant exposures in Window 2.

Figure 3. Distributions of the number of unique concomitant drug exposures per patient-months.

Distributions are for concomitant exposures to (a) drug ingredients and (b) drug classes, truncated at 10, across the 3.0 billion observed patient-months, including 1.7 billion with prescription drug exposures. (The 43% (=1.3/3 billion) of patient-months with no drug exposures are not shown on these plots.) Patients taking any prescription drugs are exposed to a median of 2 and 95th-percentile of 8 drug ingredients, and a median of 2 and 95th-percentile of 7 unique drug classes.