Evidence map›Paper›PMID 33576816›Full record

ArticleJAMA network open2021

Systematic Evaluation of State Policy Interventions Targeting the US Opioid Epidemic, 2007-2018.

Byungkyu Lee, Wanying Zhao, Kai-Cheng Yang, Yong-Yeol Ahn, Brea L Perry

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 101 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
101citing papers in PubMed, 5 pooled it
29.2field-weighted citation impact, top 1% 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

101 citing papers in PubMed, 5 syntheses or guidelines pooled it, 180 citations in OpenAlex.

  1. Pooled it
  2. Guideline
  3. Pooled it
  4. Guideline
  5. CDC Clinical Practice Guideline for Prescribing Opioids for Pain - United States, 2022.MMWR. Recommendations and reports : Morbidity and mortality weekly report. Recommendations and reports · 2022
    Guideline
  6. Trial
  7. Trial
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Spatio-Temporal Modeling for Multi-County Opioid Overdose Surveillance: A Unified Graph Convolutional Framework.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026
    Article
  17. Review
  18. Article
  19. Article
  20. Article

41 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Byungkyu LeeDepartment of Sociology, Indiana University-Bloomington, Bloomington.
Wanying ZhaoLuddy School of Informatics, Computing, and Engineering, Indiana University-Bloomington, Bloomington.
Kai-Cheng YangLuddy School of Informatics, Computing, and Engineering, Indiana University-Bloomington, Bloomington.
Yong-Yeol AhnLuddy School of Informatics, Computing, and Engineering, Indiana University-Bloomington, Bloomington.
Brea L PerryNetwork Science Institute, Department of Sociology, Indiana University-Bloomington, Bloomington.
Indiana University Bloomington · US

Funding

Doctor Shopping for Controlled Substances: Insights from Two-Mode Social Network AnalysisR01DA039928 · NIDA · TRUSTEES OF INDIANA UNIVERSITY · PI PERRY, BREA LOUISE · 2016 to 2019
$1.4M
NIDA NIH HHS R01 DA039928
6 · The paper itself

Abstract

Importance: In response to the increase in opioid overdose deaths in the United States, many states recently have implemented supply-controlling and harm-reduction policy measures. To date, an updated policy evaluation that considers the full policy landscape has not been conducted. Objective: To evaluate 6 US state-level drug policies to ascertain whether they are associated with a reduction in indicators of prescription opioid abuse, the prevalence of opioid use disorder and overdose, the prescription of medication-assisted treatment (MAT), and drug overdose deaths. Design, Setting, and Participants: This cross-sectional study used drug overdose mortality data from 50 states obtained from the National Vital Statistics System and claims data from 23 million commercially insured patients in the US between 2007 and 2018. Difference-in-differences analysis using panel matching was conducted to evaluate the prevalence of indicators of prescription opioid abuse, opioid use disorder and overdose diagnosis, the prescription of MAT, and drug overdose deaths before and after implementation of 6 state-level policies targeting the opioid epidemic. A random-effects meta-analysis model was used to summarize associations over time for each policy and outcome pair. The data analysis was conducted July 12, 2020. Exposures: State-level drug policy changes to address the increase of opioid-related overdose deaths included prescription drug monitoring program (PDMP) access, mandatory PDMPs, pain clinic laws, prescription limit laws, naloxone access laws, and Good Samaritan laws. Main Outcomes and Measures: The outcomes of interests were quarterly state-level mortality from drug overdoses, known indicators for prescription opioid abuse and doctor shopping, MAT, and prevalence of drug overdose and opioid use disorder. Results: This cross-sectional study of drug overdose mortality data and insurance claims data from 23 million commercially insured patients (12 582 378 female patients [55.1%]; mean [SD] age, 45.9 [19.9] years) in the US between 2007 and 2018 found that mandatory PDMPs were associated with decreases in the proportion of patients taking opioids (-0.729%; 95% CI, -1.011% to -0.447%), with overlapping opioid claims (-0.027%; 95% CI, -0.038% to -0.017%), with daily morphine milligram equivalent greater than 90 (-0.095%; 95% CI, -0.150% to -0.041%), and who engaged in drug seeking (-0.002%; 95% CI, -0.003% to -0.001%). The proportion of patients receiving MAT increased after the enactment of mandatory PDMPs (0.015%; 95% CI, 0.002% to 0.028%), pain clinic laws (0.013%, 95% CI, 0.005%-0.021%), and prescription limit laws (0.034%, 95% CI, 0.020% to 0.049%). Mandatory PDMPs were associated with a decrease in the number of overdose deaths due to natural opioids (-518.5 [95% CI, -728.5 to -308.5] per 300 million people) and methadone (-122.7 [95% CI, -207.5 to -37.8] per 300 million people). Prescription drug monitoring program access policies showed similar results, although these policies were also associated with increases in overdose deaths due to synthetic opioids (380.3 [95% CI, 149.6-610.8] per 300 million people) and cocaine (103.7 [95% CI, 28.0-179.5] per 300 million people). Except for the negative association between prescription limit laws and synthetic opioid deaths (-723.9 [95% CI, -1419.7 to -28.1] per 300 million people), other policies were associated with increasing overdose deaths, especially those attributed to non-prescription opioids such as synthetic opioids and heroin. This includes a positive association between naloxone access laws and the number of deaths attributed to synthetic opioids (1338.2 [95% CI, 662.5 to 2014.0] per 300 million people). Conclusions and Relevance: Although this study found that existing state policies were associated with reduced misuse of prescription opioids, they may have the unintended consequence of motivating those with opioid use disorders to access the illicit drug market, potentially increasing overdose mortality. This finding suggests that there is no easy policy solution to reverse the epidemic of opioid dependence and mortality in the US.

Indexed as

Opioid EpidemicPublic PolicyState GovernmentAnalgesics, OpioidDrug and Narcotic ControlHarm ReductionHealth PolicyHealth Services AccessibilityHumansNaloxoneNarcotic AntagonistsOpiate OverdoseOpiate Substitution TreatmentOpioid-Related DisordersPain ClinicsPractice Patterns, Physicians'Analgesics, OpioidNaloxoneNarcotic Antagonists

Identifiers

PMID33576816
PMCPMC7881356
OpenAlexW3126362147

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.