Literature DB >> 28383713

Unsolicited Reporting to Prescribers of Opioid Analgesics by a State Prescription Drug Monitoring Program: An Observational Study with Matched Comparison Group.

Leonard D Young1, Peter W Kreiner2, Lee Panas2.   

Abstract

Objective: State prescription drug monitoring programs (PDMPs) can help detect individuals with multiple provider episodes (MPEs; also referred to as doctor/pharmacy shopping), an indicator of prescription drug abuse and/or diversion. Although unsolicited reporting by PDMPs to prescribers of opioid analgesics is thought to be an important practice in reducing MPEs and the potential harm associated with them, evidence of its effectiveness is mixed. This exploratory research evaluates the impact of unsolicited reports sent by Massachusetts' PDMP to the prescribers of persons with MPEs.
Methods: Individuals with MPEs were identified from PDMP records between January 2010 and July 2011 as individuals having Schedule II prescriptions (at least one prescription being an opioid) from four or more distinct prescribers and four or more distinct pharmacies within six months. Based on available MA-PDMP resources, an unsolicited report containing the patient's 12-month prescription history was sent to prescribers of a subset of patients who met the MPE threshold; a comparison group closely matched on demographics and baseline prescription history, whose prescribers were not sent a report, was generated using propensity score matching. The prescription history of each group was examined for 12 months before and after the intervention.
Results: There were eighty-four patients (intervention group) whose prescribers received an unsolicited report and 504 matched patients (comparison group) whose prescribers were not sent a report. Regression analyses indicated significantly greater decreases in the number of Schedule II opioid prescriptions (P < 0.01), number of prescribers visited (P < 0.01), number of pharmacies used (P < 0.01), dosage units (P < 0.01), total days' supply (P < 0.01), total morphine milligram equivalents (MME; P < 0.01), and average daily MME (P < 0.05) for the intervention group relative to the comparison group. A post hoc analysis suggested that the observed intervention effects were greater for individuals with an average daily dose of less than 100 MMEs. Conclusions: This study suggests that PDMP unsolicited reporting to prescribers can help reduce risk measures in patients' prescription histories, which may improve health outcomes for patients receiving opioid analgesics from multiple providers.

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Year:  2018        PMID: 28383713     DOI: 10.1093/pm/pnx044

Source DB:  PubMed          Journal:  Pain Med        ISSN: 1526-2375            Impact factor:   3.750


  12 in total

1.  Systematic Literature Review of Prescription Drug Monitoring Programs.

Authors:  Aditya Ponnapalli; Adela Grando; Anita Murcko; Pete Wertheim
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

2.  Measuring Relationships Between Proactive Reporting State-level Prescription Drug Monitoring Programs and County-level Fatal Prescription Opioid Overdoses.

Authors:  Magdalena Cerdá; William R Ponicki; Nathan Smith; Ariadne Rivera-Aguirre; Corey S Davis; Brandon D L Marshall; David S Fink; Stephen G Henry; Alvaro Castillo-Carniglia; Garen J Wintemute; Andrew Gaidus; Paul J Gruenewald; Silvia S Martins
Journal:  Epidemiology       Date:  2020-01       Impact factor: 4.822

3.  Validation and threshold identification of a prescription drug monitoring program clinical opioid risk metric with the WHO alcohol, smoking, and substance involvement screening test.

Authors:  Gerald Cochran; Jennifer Brown; Ziji Yu; Stacey Frede; M Aryana Bryan; Andrew Ferguson; Nadia Bayyari; Brooke Taylor; Margie E Snyder; Elizabeth Charron; Omolola A Adeoye-Olatunde; Udi E Ghitza; T Winhusen
Journal:  Drug Alcohol Depend       Date:  2021-09-24       Impact factor: 4.492

4.  A Rapid Review of the Impact of Systems-Level Policies and Interventions on Population-Level Outcomes Related to the Opioid Epidemic, United States and Canada, 2014-2018.

Authors:  Bahareh Ansari; Katherine M Tote; Eli S Rosenberg; Erika G Martin
Journal:  Public Health Rep       Date:  2020 Jul/Aug       Impact factor: 2.792

5.  Effect of Automated Prescription Drug Monitoring Program Queries on Emergency Department Opioid Prescribing.

Authors:  Benjamin C Sun; Christina J Charlesworth; Nicoleta Lupulescu-Mann; Jenny I Young; Hyunjee Kim; Daniel M Hartung; Richard A Deyo; K John McConnell
Journal:  Ann Emerg Med       Date:  2017-12-13       Impact factor: 5.721

6.  Variations in prescription drug monitoring program use by prescriber specialty.

Authors:  Benjamin C Sun; Nicoleta Lupulescu-Mann; Christina J Charlesworth; Hyunjee Kim; Daniel M Hartung; Richard A Deyo; K John McConnell
Journal:  J Subst Abuse Treat       Date:  2018-08-17

7.  Advances in prescription drug monitoring program research: a literature synthesis (June 2018 to December 2019).

Authors:  Chris Delcher; Nathan Pauly; Patience Moyo
Journal:  Curr Opin Psychiatry       Date:  2020-07       Impact factor: 4.787

8.  Brief intervention medication therapy management: Establishment of an opioid misuse intervention model delivered in a community pharmacy.

Authors:  Amy Kenney; Nicholas Cox; M Aryana Bryan; Gerald Cochran
Journal:  Am J Health Syst Pharm       Date:  2021-02-08       Impact factor: 2.637

9.  "Doctor and pharmacy shopping": A fading signal for prescription opioid use monitoring?

Authors:  Chris Delcher; Daniel R Harris; Changwe Park; Gail K Strickler; Jeffery Talbert; Patricia R Freeman
Journal:  Drug Alcohol Depend       Date:  2021-02-15       Impact factor: 4.492

10.  Provider Characteristics Associated With Outpatient Opioid Prescribing After Surgery.

Authors:  David C Cron; Jay S Lee; James M Dupree; John D Syrjamaki; Hsou Mei Hu; William C Palazzolo; Michael J Englesbe; Chad M Brummett; Jennifer F Waljee
Journal:  Ann Surg       Date:  2020-04       Impact factor: 13.787

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