Evidence map›Paper›PMID 40028905›Full record

ArticleJournal of addiction medicine

Stigmatizing Language in Substance Use-related International Classification of Diseases Codes.

Neeraj Chhabra, Huiyi Hu, Rebecca T Feinstein, Niranjan S Karnik

Abstract read
In one paragraph

Article in Journal of addiction medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Huiyi Hu
Rebecca T Feinstein
Niranjan S Karnik

Funding

Chicago Data-driven OUD Screening, Engagement, Treatment and Planning (C-DOSETaP) SystemR61DA057629 · NIDA · UNIVERSITY OF ILLINOIS AT CHICAGO · PI KARNIK, NIRANJAN SUBHASH · 2023 to 2023
$1.1M
Machine learning approaches for the detection of emergency department patients with opioid misuseK23DA055061 · NIDA · UNIVERSITY OF ILLINOIS AT CHICAGO · PI Neeraj Chhabra · 2022 to 2026
$993k
NIDA NIH HHS K23 DA055061NIDA NIH HHS R61 DA057629
6 · The paper itself

Abstract

objectivesHealthcare-associated stigma is a critical barrier for treatment engagement for patients with substance use disorders. Although there are efforts to combat stigmatizing language in clinical documentation, little is known about the presence of substance use-related stigmatizing language in structured diagnosis codes ubiquitous in clinical medicine.

methodsWe examined the presence of substance use-related stigmatizing terms contained within the International Classification of Diseases, 10th revision, clinical modification (ICD-10-CM) diagnosis code descriptions. Stigmatizing terms were compiled from guidelines authored by the National Institute on Drug Abuse, while ICD-10-CM codes were obtained from the United States Centers for Disease Control and Prevention.

resultsWe evaluated 74,259 ICD-10-CM code descriptions and identified 173 substance use-related codes with stigmatizing language. The stigmatizing terms detected were "abuse" (157 code descriptions), "alcoholic" (16), and "drug abuser" (2). The term "abuse" was used in relation to multiple substances including alcohol, opioids, cannabis, sedatives, hypnotics and anxiolytics, cocaine, stimulants, hallucinogens, inhalants, other psychoactive substances, tobacco, and other medicinal products.

conclusionsStigmatizing language is used in multiple ICD-10-CM code descriptions. Subsequent iterations should bring ICD-10-CM code descriptions in line with current recommendations for destigmatized descriptors to avoid the perpetuation of stigma in healthcare.

Indexed as

International Classification of DiseasesSocial StigmaStereotypingSubstance-Related DisordersTerminology as TopicHumansLanguageUnited Statesdiagnosis codeICD codestigmastigmatizing languagesubstance use

Identifiers

PMID40028905
PMCPMC12353857

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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.