Evidence map›Paper›PMID 41254524›Full record

ArticleBMC primary care2025

A panel management approach using prescription drug monitoring program data for primary care patients with chronic pain treated with opioids: a feasibility study.

Constance van Eeghen, Marianne Burke, Zoe Daudier, Amanda G Kennedy, Neil Korsen, Benjamin Littenberg, Moira Mulligan, Doug Pomeroy, Jennifer Raymond, Meagan E Stabler and 1 more

Abstract read
In one paragraph

Article in BMC primary care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Constance van EeghenDepartment of Medicine, Robert M. Larner College of Medicine, University of Vermont, C415 University of Vermont, 89 Beaumont Avenue, Given 4th Floor, Burlington, VT, 05405, USA. cvaneegh@med.uvm.edu.
Marianne BurkeDepartment of Medicine, Robert M. Larner College of Medicine, University of Vermont, C415 University of Vermont, 89 Beaumont Avenue, Given 4th Floor, Burlington, VT, 05405, USA.
Zoe DaudierNorthern New England CO-OP Practice and Community-Based Research Network, Department of Community and Family Medicine, Dartmouth Health, 1 Medical Center Drive, Lebanon, NH, 03756, USA.
Amanda G KennedyDepartment of Medicine, Robert M. Larner College of Medicine, University of Vermont, C415 University of Vermont, 89 Beaumont Avenue, Given 4th Floor, Burlington, VT, 05405, USA.
Neil KorsenCenter for Interdisciplinary Population and Health Research, MaineHealth 1 Riverfront Plaza, Fourth Floor, Westbrook, ME, 04092, USA.
Benjamin LittenbergDepartment of Medicine, Robert M. Larner College of Medicine, University of Vermont, C415 University of Vermont, 89 Beaumont Avenue, Given 4th Floor, Burlington, VT, 05405, USA.
Moira MulliganDepartment of Medicine, Robert M. Larner College of Medicine, University of Vermont, C415 University of Vermont, 89 Beaumont Avenue, Given 4th Floor, Burlington, VT, 05405, USA.
Doug PomeroyDepartment of Medicine, Robert M. Larner College of Medicine, University of Vermont, C415 University of Vermont, 89 Beaumont Avenue, Given 4th Floor, Burlington, VT, 05405, USA.
Jennifer RaymondNorthern New England CO-OP Practice and Community-Based Research Network, Department of Community and Family Medicine, Dartmouth Health, 1 Medical Center Drive, Lebanon, NH, 03756, USA.
Meagan E StablerNorthern New England CO-OP Practice and Community-Based Research Network, Department of Community and Family Medicine, Dartmouth Health, 1 Medical Center Drive, Lebanon, NH, 03756, USA.
Charles D MacLeanDepartment of Medicine, Robert M. Larner College of Medicine, University of Vermont, C415 University of Vermont, 89 Beaumont Avenue, Given 4th Floor, Burlington, VT, 05405, USA.

Funding

Understanding Factors Influencing COVID-19 Testing and Vaccination in Immigrant Low-income and Homeless Populations and Testing Targeted InterventionsU54GM115516 · NIGMS · MAINEHEALTH · PI CLIFFORD JAMES ROSEN · 2017 to 2026
$51.6M
NIGMS NIH HHS U54 GM115516NIH HHS U54 GM115516
6 · The paper itself

Abstract

backgroundThis feasibility study explored a process for primary care clinicians to improve chronic pain management related to opioid prescribing practices by using state-based Prescription Drug Monitoring Program (PDMP) data to create panel management reports on patients receiving long term opioid therapy.

methodsConducted across four rural primary care clinics in Northern New England, the study assessed the feasibility of downloading and utilizing PDMP data and the perceived value of panel management reports derived from both PDMP and electronic health record (EHR) data in the care of patients with chronic pain treated with opioids for more than one year.

resultsThe study found that downloading PDMP data was feasible and efficient across all sites. However, EHR review proved more challenging due to inconsistencies in data entry and the unstructured nature of some relevant data fields. Clinicians generally found PDMP data easy to generate and the panel management reports informative and useful for understanding opioid prescribing trends and identifying high-risk patients.

conclusionsThe findings suggest that while PDMPs are a potential source for panel management reports for patients with chronic pain who are treated with opioids, further study is needed to determine the effectiveness of such efforts to improve care for and safety of patients treated with opioids.

Indexed as

Analgesics, OpioidChronic PainPractice Patterns, Physicians'Prescription Drug Monitoring ProgramsPrimary Health CareElectronic Health RecordsFeasibility StudiesFemaleHumansMaleMiddle AgedNew EnglandAnalgesics, OpioidChronic painDrug prescriptionOpioidPanel managementPrimary Care

Identifiers

PMID41254524
PMCPMC12625535

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.