Evidence map›Paper›PMID 31447562›Full record

ArticleSubstance abuse : research and treatment2019

Evidence of Modeling Impact in Development of Policies for Controlling the Opioid Epidemic and Improving Public Health: A Scoping Review.

Nasser Sharareh, Shabnam S Sabounchi, Mary McFarland, Rachel Hess

Open access · goldAbstract readScoping Review
In one paragraph

Article in Substance abuse : research and treatment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Economic Evaluation in Opioid Modeling: Systematic Review.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2021
    Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. A Scoping Review of Drug Epidemic Models.International journal of environmental research and public health · 2022
    Article
  8. Article
  9. Article
  10. The opioid crisis: need for systems science research.Health research policy and systems · 2020
    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

4 authors at 2 institutions in 1 country.

Nasser ShararehHealth System Innovation and Research Division, Population Health Sciences Department, School of Medicine, University of Utah, Salt Lake City, UT, USA.ORCID https://orcid.org/0000-0001-9552-2028
Shabnam S SabounchiCollege of Community and Public Affairs, the State University of New York at Binghamton, Binghamton, NY, USA.
Mary McFarlandEccles Health Science Library, University of Utah, Salt Lake City, UT, USA.
Rachel HessHealth System Innovation and Research Division, Population Health Sciences Department, School of Medicine, University of Utah, Salt Lake City, UT, USA.ORCID https://orcid.org/0000-0003-2545-8504
University of Utah · USBinghamton University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOpioid addiction and overdose rates are reaching unprecedented levels in the U.S., with around 47,736 overdose deaths in 2017. Many stakeholders affect the opioid epidemic, including government entities, healthcare providers and policymakers, and opioid users. Simulation and conceptual modeling can help us understand the dynamics of the opioid epidemic by simplifying the real world and informing policymakers about different health interventions that could reduce the deaths caused by opioid overdose in the United States every year.

objectivesTo conduct a scoping review of simulation and conceptual models that propose policies capable of controlling the opioid epidemic. We demonstrate the strengths and limitations of these models and provide a framework for further improvement of future decision support tools.

methodsUsing the methodology of a scoping review, we identified articles published after 2000 from eight electronic databases to map the literature that uses simulation and conceptual modeling in developing public health policies to address the opioid epidemic.

resultsWe reviewed 472 papers of which 14 were appropriate for inclusion. Each used either system dynamics simulation modeling, mathematical modeling, conceptual modeling, or agent-based modeling. All included studies tested and proposed strategies to improve health outcomes related to the opioid epidemic. Factors considered in the models included physicians prescribing opioids, trafficking, users recruiting new users, and doctor shopping; no model investigated the impact of age and spatial factors on the dynamics of the epidemic. Key findings from these studies were (1) prevention of opioid initiation is better than treatment of opioid addiction, (2) the analysis of an intervention's impact should include both benefits and harms, and (3) interventions with short-term benefits might have a counterproductive impact on the epidemic in long run.

conclusionsWhile most studies examined the role of prescription opioids and trafficking on this epidemic, the transition of patients from prescription opioid use to nonprescription use including heroin and synthetic opioids such as fentanyl impacts the system significantly and results in an epidemic with quite different characteristics than what it had a decade ago. We recommend including the impact of age and geographic location on the opioid epidemic using modeling methods.

Indexed as

fentanylhealth policyheroinopioidsimulation and conceptual modeling

Identifiers

PMID31447562
PMCPMC6689912
OpenAlexW2967391811

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.