Literature DB >> 28722211

Using prescription monitoring program data to characterize out-of-pocket payments for opioid prescriptions in a state Medicaid program.

Daniel M Hartung1, Sharia M Ahmed1, Luke Middleton1, Joshua Van Otterloo2, Kun Zhang3, Shellie Keast4, Hyunjee Kim5, Kirbee Johnston1, Richard A Deyo5.   

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.
Copyright © 2017 John Wiley & Sons, Ltd.

Entities:  

Keywords:  Medicaid; drug abuse; drug utilization; pharmacoepidemiology; substance abuse

Mesh:

Substances:

Year:  2017        PMID: 28722211     DOI: 10.1002/pds.4254

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  10 in total

1.  Factors Influencing Judgments to Consult Prescription Monitoring Programs: A Factorial Survey Experiment.

Authors:  Matthew J Witry; Barbara J St Marie; Brahmendra Reddy Viyyuri; Paul D Windschitl
Journal:  Pain Manag Nurs       Date:  2019-05-24       Impact factor: 1.929

2.  Inappropriate Opioid Prescribing in Oregon's Coordinated Care Organizations.

Authors:  Amanda J Abraham; Traci Rieckmann; Yifan Gu; Bonnie K Lind
Journal:  J Addict Med       Date:  2020 Jul/Aug       Impact factor: 3.702

3.  National Variation in Opioid Prescribing and Risk of Prolonged Use for Opioid-Naive Patients Treated in the Emergency Department for Ankle Sprains.

Authors:  M Kit Delgado; Yanlan Huang; Zachary Meisel; Sean Hennessy; Michael Yokell; Daniel Polsky; Jeanmarie Perrone
Journal:  Ann Emerg Med       Date:  2018-07-24       Impact factor: 5.721

4.  Prescription Opioid Dispensing Patterns Prior to Heroin Overdose in a State Medicaid Program: a Case-Control Study.

Authors:  Daniel M Hartung; Kirbee A Johnston; Sara Hallvik; Gillian Leichtling; Jonah Geddes; Christi Hildebran; Shellie Keast; Brian Chan; P Todd Korthuis
Journal:  J Gen Intern Med       Date:  2020-09-15       Impact factor: 5.128

5.  Do Injured Workers Receive Opioid Prescriptions Outside the Workers' Compensation System?: The Case of Private Group Health Insurances.

Authors:  Abay Asfaw; Brian Quay; Chia-Chia Chang
Journal:  J Occup Environ Med       Date:  2020-09       Impact factor: 2.162

6.  Patient outcomes after opioid dose reduction among patients with chronic opioid therapy.

Authors:  Sara E Hallvik; Sanae El Ibrahimi; Kirbee Johnston; Jonah Geddes; Gillian Leichtling; P Todd Korthuis; Daniel M Hartung
Journal:  Pain       Date:  2022-01-01       Impact factor: 7.926

7.  Identifying opioid dose reductions and discontinuation among patients with chronic opioid therapy.

Authors:  Sara E Hallvik; Kirbee Johnston; Jonah Geddes; Gillian Leichtling; P Todd Korthuis; Daniel M Hartung
Journal:  Pharmacoepidemiol Drug Saf       Date:  2020-08-26       Impact factor: 2.732

8.  A comparison of trends in opioid dispensing patterns between Medicaid pharmacy claims and prescription drug monitoring program data.

Authors:  Sanae El Ibrahimi; Sara Hallvik; Kirbee Johnston; Gillian Leichtling; Esther Choo; Daniel M Hartung
Journal:  Pharmacoepidemiol Drug Saf       Date:  2020-08-10       Impact factor: 2.732

9.  Prevalence of and Factors Associated With Long-term Concurrent Use of Stimulants and Opioids Among Adults With Attention-Deficit/Hyperactivity Disorder.

Authors:  Yu-Jung Jenny Wei; Yanmin Zhu; Wei Liu; Regina Bussing; Almut G Winterstein
Journal:  JAMA Netw Open       Date:  2018-08-03

10.  Patterns of Prescription Opioid Use Prior to Self-reported Heroin Initiation.

Authors:  Daniel M Hartung; Jonah Geddes; Kirbee A Johnston; Gillian Leichtling; Sara Hallvik; Christi Hildebran; P Todd Korthuis
Journal:  J Addict Med       Date:  2021-04-01       Impact factor: 4.647

  10 in total

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