Literature DB >> 26077605

High mortality rate of unintentional poisoning due to prescription opioids in adults enrolled in Medicaid compared to those not enrolled in Medicaid in Montana.

Jessie C Fernandes1, David Campana2, Todd S Harwell3, Steven D Helgerson1.   

Abstract

BACKGROUND: Unintentional death due to prescription drug-related poisoning has been a growing problem nationally. Some sub-populations have been shown to be at higher risk than others.
METHODS: In 2014, we matched death records to Medicaid eligibility files to determine enrollment status at the time of unintentional death from prescription opioid poisoning from 2003 to 2012 in Montana. Medicaid prescription claims for decedents were used to assess prescribing patterns and time between refills.
RESULTS: The age-adjusted mortality rate per 100,000 from opioid poisoning for adults aged 18-64 years and enrolled in Medicaid at the time of death was eight times higher than the rate for non-Medicaid Montana adults (38.2 [95% CI (30.7-45.7)] vs. 4.7 [95% CI (4.1-5.3)]). Twenty-eight percent of unintentional poisoning deaths during this time frame were among Medicaid members. Only 33% of the Medicaid decedents had a claim for an opioid prescription during the month before their death.
CONCLUSION: Our findings suggest that more needs to be done to address prescription opioid use in Montana. Adults enrolled in Medicaid continue to be at high risk for prescription opioid unintentional poisoning deaths. Data on prescribing practices suggest that there are opportunities to intervene and provide education on use of opioid medications for Medicaid members and prescribing providers.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Deaths; Epidemiology; Medicaid; Opioid; Prescription drug

Mesh:

Substances:

Year:  2015        PMID: 26077605     DOI: 10.1016/j.drugalcdep.2015.05.032

Source DB:  PubMed          Journal:  Drug Alcohol Depend        ISSN: 0376-8716            Impact factor:   4.492


  10 in total

1.  High-Risk Prescribing to Medicaid Enrollees Receiving Opioid Analgesics: Individual- and County-Level Factors.

Authors:  Sara E Heins; Mark J Sorbero; Christopher M Jones; Andrew W Dick; Bradley D Stein
Journal:  Subst Use Misuse       Date:  2018-01-05       Impact factor: 2.164

2.  Use and Opinions of Prescription Opioids Among Older American Adults: Sociodemographic Predictors.

Authors:  Hanna Grol-Prokopczyk
Journal:  J Gerontol B Psychol Sci Soc Sci       Date:  2019-08-21       Impact factor: 4.077

3.  Health Care Utilization and Comorbidity History of North Carolina Medicaid Beneficiaries in a Controlled Substance "Lock-in" Program.

Authors:  Rebecca B Naumann; Stephen W Marshall; Jennifer L Lund; Asheley C Skinner; Christopher Ringwalt; Nisha C Gottfredson
Journal:  N C Med J       Date:  2019 May-Jun

Review 4.  The Association of State Opioid Misuse Prevention Policies With Patient- and Provider-Related Outcomes: A Scoping Review.

Authors:  Amanda I Mauri; Tarlise N Townsend; Rebecca L Haffajee
Journal:  Milbank Q       Date:  2019-12-04       Impact factor: 4.911

5.  Are North Carolina clinicians delivering opioid use disorder treatment to Medicaid beneficiaries?

Authors:  Lexie R Grove; Nikhil Rao; Marisa Elena Domino
Journal:  Addiction       Date:  2022-03-07       Impact factor: 7.256

Review 6.  Health harms of non-medical prescription opioid use: A systematic review.

Authors:  Dan Werb; Ayden I Scheim; Ayorinde Soipe; Samantha Aeby; Indhu Rammohan; Benedikt Fischer; Scott E Hadland; Brandon D L Marshall
Journal:  Drug Alcohol Rev       Date:  2022-04-18

7.  The Harnessing Online Peer Education (HOPE) Intervention for Reducing Prescription Drug Abuse: A Qualitative Study.

Authors:  Sean D Young; Keith Heinzerling
Journal:  J Subst Use       Date:  2017-01-31

8.  A population-based examination of trends and disparities in medication treatment for opioid use disorders among Medicaid enrollees.

Authors:  Bradley D Stein; Andrew W Dick; Mark Sorbero; Adam J Gordon; Rachel M Burns; Douglas L Leslie; Rosalie Liccardo Pacula
Journal:  Subst Abus       Date:  2018-06-22       Impact factor: 3.716

9.  Integrating human services and criminal justice data with claims data to predict risk of opioid overdose among Medicaid beneficiaries: A machine-learning approach.

Authors:  Wei-Hsuan Lo-Ciganic; Julie M Donohue; Eric G Hulsey; Susan Barnes; Yuan Li; Courtney C Kuza; Qingnan Yang; Jeanine Buchanich; James L Huang; Christina Mair; Debbie L Wilson; Walid F Gellad
Journal:  PLoS One       Date:  2021-03-18       Impact factor: 3.240

Review 10.  Socioeconomic marginalization and opioid-related overdose: A systematic review.

Authors:  Jenna van Draanen; Christie Tsang; Sanjana Mitra; Mohammad Karamouzian; Lindsey Richardson
Journal:  Drug Alcohol Depend       Date:  2020-06-20       Impact factor: 4.492

  10 in total

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