OBJECTIVES: To explore the ability of claims-based utilization measures – including traditional adherence measures, a novel measure of overlapping days supply, and measures of asymmetrical use within a population – to detect non-medical prescription drug use. METHODS:  Prescription claims from a large employer-based administrative claims database (MarketScan) were used to evaluate drug utilization during the first year after an index prescription for 6 classes of drugs with a known abuse potential and 3 classes without.  Population-level measures of traditional adherence metrics (i.e., MPR and PDC) and a novel measure of overlapping days supply (MPR:PDC ratio) were calculated for all medications. Measures of asymmetrical use within a population were evaluated with the Lorenz curve, representing the total drug supply used by the heaviest 1%, 5% and 50% of all users.  Each measure was used to rank order (high to low) agents across and within classes. The resulting lists were qualitatively compared on their ability to rank order similar or dissimilar patterns.  RESULTS:  The study cohort included 6,840,355 patients, mean age 48.1 years, 56.5% female.  The mean MPR for drugs with known abuse potential (0.13-0.53) was lower than for drugs without (0.72-0.84). The MPR and PDC ranking across drugs was consistent, but the MPR:PDC and Lorenz curve ranking showed a different pattern.  In addition, several abusable drugs had the highest mean MPR:PDC ratios (i.e., 1.14 for morphine, 1.13 for oxycodone, 1.11 for dextroamphetamine).  Percent drug use by the heaviest users was also higher for abusable drugs (e.g., Lorenz 1% of 29.1% for acetaminophen with codeine, 21.5% for acetaminophen with oxycodone, and 18.4% for oxycodone).  CONCLUSIONS:  Patients taking drugs with a known abuse potential exhibited different utilization patterns compared to drugs without.  Measures accounting for overlapping days supply and asymmetrical drug use within a population may be better suited to detecting non-medical prescription drug use.