Using prescription monitoring program data to characterize out‐of‐pocket payments for opioid prescriptions in a state Medicaid program. Issue 9 (19th July 2017)

• Record Type: Journal Article
• Authors: Hartung, Daniel M.; Ahmed, Sharia M.; Middleton, Luke; Van Otterloo, Joshua; Zhang, Kun; Keast, Shellie; Kim, Hyunjee; Johnston, Kirbee; Deyo, Richard A.
• Is Part Of: Pharmacoepidemiology and drug safety. Volume 26:Issue 9(2017)
• Page Start: 1053
• Page End: 1060
• Publication Date: 2017-07-19
• Subjects: drug abuse -- drug utilization -- Medicaid -- pharmacoepidemiology -- substance abuse; Pharmacoepidemiology -- Periodicals; Chemotherapy -- Periodicals; Epidemiology -- Periodicals; 615.705
• DOI: 10.1002/pds.4254
• Languages: English
• ISSNs: 1053-8569

Abstract

Abstract: Background: Out‐of‐pocket payment for prescription opioids is believed to be an indicator of abuse or diversion, but few studies describe its epidemiology. Prescription drug monitoring programs (PDMPs) collect controlled substance prescription fill data regardless of payment source and thus can be used to study this phenomenon. Objective: To estimate the frequency and characteristics of prescription fills for opioids that are likely paid out‐of‐pocket by individuals in the Oregon Medicaid program. Research Design: Cross‐sectional analysis using Oregon Medicaid administrative claims and PDMP data (2012 to 2013). Subjects: Continuously enrolled nondually eligible Medicaid beneficiaries who could be linked to the PDMP with two opioid fills covered by Oregon Medicaid. Measures: Patient characteristics and fill characteristics for opioid fills that lacked a Medicaid pharmacy claim. Fill characteristics included opioid name, type, and association with indicators of high‐risk opioid use. Results: A total of 33 592 Medicaid beneficiaries filled a total of 555 103 opioid prescriptions. Of these opioid fills, 74 953 (13.5%) could not be matched to a Medicaid claim. Hydromorphone (30%), fentanyl (18%), and methadone (15%) were the most likely to lack a matching claim. The 3 largest predictors for missing claims were opioid fills that overlapped with other opioids (adjusted odds ratio [aOR] 1.37; 95% confidence interval [CI], 1.34‐1.4), long‐acting opioids (aOR 1.52; 95% CI, 1.47‐1.57), and fills at multiple pharmacies (aOR 1.45; 95% CI, 1.39‐1.52). Conclusions: Prescription opioid fills that were likely paid out‐of‐pocket were common and associated with several known indicators of high‐risk opioid use.