Evidence map›Paper›PMID 36512356›Full record

ArticleJAMA network open2022

Assessment of the Accuracy of Firearm Injury Intent Coding at 3 US Hospitals.

Matthew Miller, Deborah Azrael, Ravali Yenduri, Catherine Barber, Andrew Bowen, Erin MacPhaul, Stephen J Mooney, Li Zhou, Eric Goralnick, Ali Rowhani-Rahbar

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
7.8field-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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.

  1. Pooled it
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  5. Review
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  12. Observational
  13. Machine learning classification of new firearm injury encounters in the St Louis region: 2010-2020.Journal of the American Medical Informatics Association : JAMIA · 2024
    Article
  14. Article
  15. Article
  16. The Health and Economic Impact of Youth Violence by Injury Mechanism.American journal of preventive medicine · 2024
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Matthew MillerDepartment of Health Sciences, Bouvé College of Health Sciences, Northeastern University, Boston, Massachusetts.
Deborah AzraelHarvard Injury Control Research Center, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.
Ravali YenduriDepartment of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Catherine BarberHarvard Injury Control Research Center, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.
Andrew BowenFirearm Injury and Policy Research Program, University of Washington, Seattle.
Erin MacPhaulDepartment of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Stephen J MooneyFirearm Injury and Policy Research Program, University of Washington, Seattle.
Li ZhouDepartment of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Eric GoralnickDepartment of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Ali Rowhani-RahbarFirearm Injury and Policy Research Program, University of Washington, Seattle.
Harvard University · USUniversity of Washington · USBrigham and Women's Hospital · USNortheastern University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: The absence of reliable hospital discharge data regarding the intent of firearm injuries (ie, whether caused by assault, accident, self-harm, legal intervention, or an act of unknown intent) has been characterized as a glaring gap in the US firearms data infrastructure. Objective: To use incident-level information to assess the accuracy of intent coding in hospital data used for firearm injury surveillance. Design, Setting, and Participants: This cross-sectional retrospective medical review study was conducted using case-level data from 3 level I US trauma centers (for 2008-2019) for patients presenting to the emergency department with an incident firearm injury of any severity. Exposures: Classification of firearm injury intent. Main Outcomes and Measures: Researchers reviewed electronic health records for all firearm injuries and compared intent adjudicated by team members (the gold standard) with International Classification of Diseases, Ninth and Tenth Revision, Clinical Modification (ICD-9-CM and ICD-10-CM) codes for firearm injury intent assigned by medical records coders (in discharge data) and by trauma registrars. Accuracy was assessed using intent-specific sensitivity and positive predictive value (PPV). Results: Of the 1227 cases of firearm injury incidents seen during the ICD-10-CM study period (October 1, 2015, to December 31, 2019), the majority of patients (1090 [88.8%]) were male and 547 (44.6%) were White. The research team adjudicated 837 (68.2%) to be assaults. Of these assault incidents, 234 (28.0%) were ICD coded as unintentional injuries in hospital discharge data. These miscoded patient cases largely accounted for why discharge data had low sensitivity for assaults (66.3%) and low PPV for unintentional injuries (34.3%). Misclassification was substantial even for patient cases described explicitly as assaults in clinical notes (sensitivity of 74.3%), as well as in the ICD-9-CM study period (sensitivity of 77.0% for assaults and PPV of 38.0% for unintentional firearm injuries). By contrast, intent coded by trauma registrars differed minimally from researcher-adjudicated intent (eg, sensitivity for assault of 96.0% and PPV for unintentional firearm injury of 93.0%). Conclusions and Relevance: The findings of this cross-sectional study underscore questions raised by prior work using aggregate count data regarding the accuracy of ICD-coded discharge data as a source of firearm injury intent. Based on our observations, researchers and policy makers should be aware that databases drawn from hospital discharge data (most notably, the Nationwide Emergency Department Sample) cannot be used to reliably count or characterize intent-specific firearm injuries.

Indexed as

FirearmsWounds, GunshotCross-Sectional StudiesFemaleHospitalsHumansMaleRetrospective Studies

Identifiers

PMID36512356
PMCPMC9856424
OpenAlexW4311310880

What OpenQuestion holds

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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.