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

Daniel M. Hartung, Sharia M. Ahmed, Luke Middleton, Joshua Van Otterloo, Kun Zhang, Shellie Keast, Hyunjee Kim, Kirbee Johnston, Richard (Rick) Deyo

Research output: Contribution to journalArticle

6 Citations (Scopus)

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.

Original languageEnglish (US)
JournalPharmacoepidemiology and Drug Safety
DOIs
StateAccepted/In press - 2017

Fingerprint

Medicaid
Health Expenditures
Opioid Analgesics
Prescriptions
Prescription Drugs
Drug Monitoring
Odds Ratio
Confidence Intervals
Controlled Substances
Hydromorphone
Pharmacies
Methadone
Fentanyl
Names
Epidemiology
Research Design
Cross-Sectional Studies

Keywords

  • Drug abuse
  • Drug utilization
  • Medicaid
  • Pharmacoepidemiology
  • Substance abuse

ASJC Scopus subject areas

  • Epidemiology
  • Pharmacology (medical)

Cite this

Using prescription monitoring program data to characterize out-of-pocket payments for opioid prescriptions in a state Medicaid program. / Hartung, Daniel M.; Ahmed, Sharia M.; Middleton, Luke; Van Otterloo, Joshua; Zhang, Kun; Keast, Shellie; Kim, Hyunjee; Johnston, Kirbee; Deyo, Richard (Rick).

In: Pharmacoepidemiology and Drug Safety, 2017.

Research output: Contribution to journalArticle

Hartung, Daniel M. ; Ahmed, Sharia M. ; Middleton, Luke ; Van Otterloo, Joshua ; Zhang, Kun ; Keast, Shellie ; Kim, Hyunjee ; Johnston, Kirbee ; Deyo, Richard (Rick). / Using prescription monitoring program data to characterize out-of-pocket payments for opioid prescriptions in a state Medicaid program. In: Pharmacoepidemiology and Drug Safety. 2017.
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title = "Using prescription monitoring program data to characterize out-of-pocket payments for opioid prescriptions in a state Medicaid program",
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.",
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T1 - Using prescription monitoring program data to characterize out-of-pocket payments for opioid prescriptions in a state Medicaid program

AU - Hartung, Daniel M.

AU - Ahmed, Sharia M.

AU - Middleton, Luke

AU - Van Otterloo, Joshua

AU - Zhang, Kun

AU - Keast, Shellie

AU - Kim, Hyunjee

AU - Johnston, Kirbee

AU - Deyo, Richard (Rick)

PY - 2017

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N2 - 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.

AB - 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.

KW - Drug abuse

KW - Drug utilization

KW - Medicaid

KW - Pharmacoepidemiology

KW - Substance abuse

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