Evidence map›Paper›PMID 31372990›Full record

ArticleHealth services research2019

Prescription drug monitoring programs: Assessing the association between "best practices" and opioid use in Medicare.

Patience Moyo, Linda Simoni-Wastila, Beth Ann Griffin, Donna Harrington, G Caleb Alexander, Francis Palumbo, Eberechukwu Onukwugha

Open access · greenAbstract readComparative Study
In one paragraph

Article in Health services research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
2.2field-weighted citation impact, top 13% of its field
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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Patience MoyoBrown University School of Public Health, Providence, Rhode Island.ORCID 0000-0003-1323-4554
Linda Simoni-WastilaSchool of Pharmacy, Pharmaceutical Health Services Research, University of Maryland Baltimore, Baltimore, Maryland.
Beth Ann GriffinRAND Corporation, Arlington, Virginia.
Donna HarringtonUniversity of Maryland School of Social Work, Baltimore, Maryland.
G Caleb AlexanderDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Francis PalumboSchool of Pharmacy, Pharmaceutical Health Services Research, University of Maryland Baltimore, Baltimore, Maryland.
Eberechukwu OnukwughaDepartment of Pharmaceutical Health Services Research, University of Maryland School of Pharmacy, Baltimore, Maryland.
University of Maryland, Baltimore · USBrown University · USJohns Hopkins University · USRAND Corporation · US

Funding

Optimal Methods for Estimating Policy Effect Heterogeneity in Opioid Policy ResearchP50DA046351 · NIDA · RAND CORPORATION · PI BRADLEY D STEIN · 2018 to 2026
$20.8M
NIDA NIH HHS P50 DA046351NIDA NIH HHS P50DA046351
6 · The paper itself

Abstract

objectiveTo estimate the impact of implementing prescription drug monitoring program (PDMP) best practices on prescription opioid use. DATA SOURCES: 2007-2012 Medicare claims for noncancer pain patients, and PDMP attributes from the Prescription Drug Abuse Policy System. STUDY

designWe derived PDMP composite scores using the number of best practices adopted by states (range: 0-14), classifying states as either no PDMP, low strength (0 < score < median), or high strength (score ≥ median). Using generalized linear models, we quantified the association between the PDMP score category and opioid use measures-overall and stratified by disability/age. Sensitivity analyses assessed the general Medicare sample regardless of pain diagnoses, individual PDMP characteristics, and compared GEE model findings to models with state fixed effects. PRINCIPAL

findingsCompared to non-PDMP states, strong PDMP states had lower opioid cumulative doses (-296 mg; 95% CI: -512, -132), days supplied (-7.84; 95% CI: -10.6, -5.04), prescription fill rates (0.97; 95% CI: 0.95, 0.98), and mean daily doses (-2.31 mg; 95% CI: -3.14, -1.48) but greater prevalence of high opioid doses in disabled adults, whereas there was little or no change in older adults. Findings in states with weak PDMPs were substantively similar to those of strong PDMPs. Results from sensitivity analyses were mostly consistent with main findings except there was a null relationship with mean daily doses and high doses in models with state fixed effects.

conclusionsComprehensive or minimal adoption of PDMP best practices was associated with mostly comparable effects on Medicare beneficiaries' opioid use; however, these effects were concentrated among nonelderly disabled adults.

Indexed as

Practice Guidelines as TopicAgedAged, 80 and overAnalgesics, OpioidDrug UtilizationFemaleHumansMaleMedicareOpioid-Related DisordersPainPrescription Drug Monitoring ProgramsUnited StatesAnalgesics, Opioiddrug utilizationmedicareopioidsprescription drug monitoring programsstate health policy

Identifiers

PMID31372990
PMCPMC6736920
OpenAlexW2966851568

What OpenQuestion holds

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Registered trials

None linked

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.