Evidence map›Paper›PMID 33179145›Full record

ArticleJournal of general internal medicine2021

Validity of Incident Opioid Use Disorder (OUD) Diagnoses in Administrative Data: a Chart Verification Study.

Benjamin A Howell, Erica A Abel, Dongchan Park, Sara N Edmond, Leah J Leisch, William C Becker

Open access · bronzeAbstract read
In one paragraph

Article in Journal of general internal medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 4 pooled it
7.6field-weighted citation impact, top 2% 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

58 citing papers in PubMed, 4 syntheses or guidelines pooled it, 73 citations in OpenAlex.

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  17. Use of Medications for Opioid Use Disorder in Older Adults.American journal of preventive medicine · 2025
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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

6 authors at 2 institutions in 1 country.

Benjamin A HowellNational Clinician Scholars Program, Yale School of Medicine, New Haven, CT, 06511, USA. benjamin.howell@yale.edu.ORCID 0000-0001-6938-8347
Erica A AbelVA Connecticut Healthcare System, West Haven, CT, USA.
Dongchan ParkEdith Nourse Rogers Veterans Memorial Hospital, Bedford, MA, USA.
Sara N EdmondVA Connecticut Healthcare System, West Haven, CT, USA.
Leah J LeischSection of General Internal Medicine, Yale School of Medicine, New Haven, CT, USA.
William C BeckerVA Connecticut Healthcare System, West Haven, CT, USA.
Yale University · USEdith Nourse Rogers Memorial Veterans Hospital · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Yale Drug use, Addiction and HIV Research Scholars (DAHRS)K12DA033312 · NIDA · YALE UNIVERSITY · PI Gail D'Onofrio, Patrick O'Connor · 2013 to 2026
$7.2M
NCATS NIH HHS UL1 TR001863NIDA NIH HHS 5K12DA033312NIDA NIH HHS K12 DA033312VA QUE PII 18-180
6 · The paper itself

Abstract

backgroundAn important strategy to address the opioid overdose epidemic involves identifying people at elevated risk of overdose, particularly those with opioid use disorder (OUD). However, it is unclear to what degree OUD diagnoses in administrative data are inaccurate.

objectiveTo estimate the prevalence of inaccurate diagnoses of OUD among patients with incident OUD diagnoses. SUBJECTS: A random sample of 90 patients with incident OUD diagnoses associated with an index in-person encounter between October 1, 2016, and June 1, 2018, in three Veterans Health Administration medical centers.

designDirect chart review of all encounter notes, referrals, prescriptions, and laboratory values within a 120-day window before and after the index encounter. Using all available chart data, we determined whether the diagnosis of OUD was likely accurate, likely inaccurate, or of indeterminate accuracy. We then performed a bivariate analysis to assess demographic or clinical characteristics associated with likely inaccurate diagnoses. KEY

resultsWe identified 1337 veterans with incident OUD diagnoses. In the chart verification subsample, we assessed 26 (29%) OUD diagnoses as likely inaccurate; 20 due to systems error and 6 due to clinical error; additionally, 8 had insufficient information to determine accuracy. Veterans with likely inaccurate diagnoses were more likely to be younger and prescribed opioids for pain. Clinical settings associated with likely inaccurate diagnoses were non-mental health clinical settings, group visits, and non-patient care settings.

conclusionsOur study identified significant levels of likely inaccurate OUD diagnoses among veterans with incident OUD diagnoses. The majority of these cases reflected readily addressable systems errors. The smaller proportion due to clinical errors and those with insufficient documentation may be addressed by increased training for clinicians. If these inaccuracies are prevalent throughout the VHA, they could complicate health services research and health systems responses.

Indexed as

Drug OverdoseOpioid-Related DisordersVeteransAnalgesics, OpioidHumansPainAnalgesics, Opioidadministrative datachart verificationopioid use disordervalidation study

Identifiers

PMID33179145
PMCPMC8131432
OpenAlexW3105791171

What OpenQuestion holds

Textmetadata
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.