Evidence map›Paper›PMID 29402676›Full record

Observational studyDrug and alcohol dependence2018

Features of prescription drug monitoring programs associated with reduced rates of prescription opioid-related poisonings.

N J Pauly, S Slavova, C Delcher, P R Freeman, J Talbert

Abstract readObservational Study
In one paragraph

Observational study in Drug and alcohol dependence, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 6 pooled it
–field-weighted citation impact
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

32 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Systematic Literature Review of Prescription Drug Monitoring Programs.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018
    Pooled it
  6. Pooled it
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

5 authors.

N J PaulyInstitute for Pharmaceutical Outcomes and Policy, University of Kentucky College of Pharmacy, 789 South Limestone, Lexington, KY 40536, United States. Electronic address: Nathan.Pauly@uky.edu.
S SlavovaDepartment of Biostatistics, University of Kentucky College of Public Health, 333 Waller Avenue, Suite 242, Lexington, KY 40504, United States.
C DelcherDepartment of Health Outcomes and Policy, University of Florida, 2004 Mowry Road, Suite 2237, P.O. Box 100177, Gainesville, FL 32610, United States.
P R FreemanInstitute for Pharmaceutical Outcomes and Policy, University of Kentucky College of Pharmacy, 789 South Limestone, Lexington, KY 40536, United States.
J TalbertInstitute for Pharmaceutical Outcomes and Policy, University of Kentucky College of Pharmacy, 789 South Limestone, Lexington, KY 40536, United States.

Funding

Kentucky Center for Clinical and Translational ScienceUL1TR001998 · NCATS · UNIVERSITY OF KENTUCKY · PI HARTMANN, KATHERINE E, KERN, PHILIP A · 2016 to 2025
$34.2M
NCATS NIH HHS UL1 TR001998
6 · The paper itself

Abstract

backgroundThe United States is in the midst of an opioid epidemic. In addition to other system-level interventions, all states have responded during the crisis by implementing prescription drug monitoring programs (PDMPs). This study examines associations between specific administrative features of PDMPs and changes in the risk of prescription opioid-related poisoning (RxORP) over time.

methodsThis longitudinal, observational study utilized a 'natural experiment' design to assess associations between PDMP features and risk of RxORP in a nationally-representative population of privately-insured adults from 2004 to 2014. Administrative health claims data were used to identify inpatient hospital admissions and emergency department visits related to RxORP. Generalized estimating equation Poisson regression models were used to examine associations between specific PDMP features and changes in relative risk (RR) of RxORP over time.

resultsIn adjusted analyses, states without PDMPs experienced an average annual increase in the rate of RxORP of 9.51% over the study period, while states with operational PDMPs experienced an average annual increase of 3.17%. The increase in RR of RxORP over time in states with operational PDMPs was significantly less than increases in states without PDMPs. States with specific features, including those that monitored more schedules or required more frequent data reporting, experienced stronger protective effects on the RR of RxORP over time.

conclusionThis study examined associations between specific PDMP features and RxORP rates in a nationally-representative population of privately-insured adults. Results of this study may be used as empirical evidence to guide PDMP best practices.

Indexed as

AdultAnalgesics, OpioidDrug OverdoseEmergency Service, HospitalFemaleHumansLongitudinal StudiesMalePrescription Drug MisusePrescription Drug Monitoring ProgramsUnited StatesAnalgesics, OpioidEvaluationOpioidPoisoningPolicyPrescription drug monitoring program

Identifiers

PMID29402676
PMCPMC5854200

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.