Opioid prescribing patterns in a commercially insured population

Abstract

BackgroundClaims data evaluations have advanced our understanding about patient risk factors and predictors for opioid misuse and aid in patient identification. However, less evidence is available to guide the identification of prescribers with at-risk prescribing practices. Thus, an algorithm was developed to identify prescribers with outlying patterns of opioid prescriptions in a managed care organization. MethodsA retrospective analysis used enrollment, prescription, and medical claims data from September-December 2019 to identify prescribers of schedule II, III or IV opioid analgesic medications. Criteria were used to characterize these prescribers as frequent, continuous, and/or high-dose prescribers of opioids. ResultsFor prescribers with > 25 patients with any prescriptions, the algorithm identified 5136 prescribers who had prescribed at least one opioid. This group of prescribers accounted for 53.9% of the total opioids prescribed and wrote an average of 6.5 opioid prescriptions per prescriber during a 3-month period. There were 629 prescribers (12.2%) that had prescribed an opioid to ≥ 50% of their population (frequent prescribers); 493 prescribers (9.6%) that had prescribed >185 day-supply of opioids within 6 months to 10% or more of their population (continuous prescribers); 147 prescribers (2.9%) that had prescribed an average daily MME > 90 mg to ≥ 10% of their population in the most recent 90 days (high-dose prescribers); and 47 prescribers (0.9%) that met all three criteria. ConclusionsThe algorithm identified a targeted prescriber group to employ resources to mitigate opioid misuse and abuse. Flexible criteria for frequent, continuous, and/or high-dose prescribing allows tailoring to the needs of different managed care organizations.