Opioid prescribing patterns in a commercially insured population

An Exploratory Analysis of Differential Prescribing of High-Risk Opioids by Insurance Type Among Patients Seen by the Same Clinician

BACKGROUND

Insurance status may influence quality of opioid analgesic (OA) prescribing among patients seen by the same clinician.

OBJECTIVE

To explore how high-risk OA prescribing varies by payer type among patients seeing the same prescriber and identify clinician characteristics associated with variable prescribing DESIGN: Retrospective cohort study using the 2016-2018 IQVIA Real World Data - Longitudinal Prescription PARTICIPANTS: New OA treatment episodes for individuals ≥ 12 years, categorized by payer and prescriber. We created three dyads: prescribers with ≥ 10 commercial insurance episodes and ≥ 10 Medicaid episodes; ≥ 10 commercial insurance episodes and ≥ 10 self-pay episodes; and ≥ 10 Medicaid episodes and ≥ 10 self-pay episodes.

MAIN OUTCOME(S) AND MEASURE(S)

Rates of high-risk episodes (initial opioid episodes with > 7-days' supply or prescriptions with a morphine milliequivalent daily dose >90) and odds of being an unbalanced prescriber (prescribers with significantly higher percentage of high-risk episodes paid by one payer vs. the other payer) KEY RESULTS: There were 88,352 prescribers in the Medicaid/self-pay dyad, 172,392 in the Medicaid/commercial dyad, and 122,748 in the self-pay/commercial dyad. In the Medicaid/self-pay and the commercial-self-pay dyads, self-pay episodes had higher high-risk episode rates than Medicaid (16.1% and 18.4%) or commercial (22.7% vs. 22.4%). In the Medicaid/commercial dyad, Medicaid had higher high-risk episode rates (21.1% vs. 20.4%). The proportion of unbalanced prescribers was 11-12% across dyads. In adjusted analyses, surgeons and pain specialists were more likely to be unbalanced prescribers than adult primary care physicians (PCPs) in the Medicaid/self-paydyad (aOR 1.2, 95% CI 1.16-1.34 and aOR 1.2, 95% CI 1.03-1.34). For Medicaid/commercial and self-pay/commercial dyads, surgeons had lower odds of being unbalanced compared to PCPs (aOR 0.6, 95% CI 0.57-0.66 and aOR 0.6, 95% CI 0.61-0.68).

CONCLUSIONS

Clinicians prescribe high-risk OAs differently based on insurance type. The relationship between insurance and opioid prescribing quality goes beyond where patients receive care.