Evidence map›Paper›PMID 40242073›Full record

ArticleOpen forum infectious diseases2025

Leveraging Natural Language Processing to Identify Veterans Who Inject Drugs to Assess Preexposure Prophylaxis and Sexually Transmitted Infection Testing Services at the Veterans Health Administration.

Minh Q Ho, Colin O'Connor, Karine Rozenberg-Ben-Dror, Mohammed S Ahmed, Karen Slazinski

Abstract read
In one paragraph

Article in Open forum infectious diseases, 2025. 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

5 authors.

Minh Q HoDepartment of Internal Medicine, College of Medicine, University of Central Florida, Orlando, Florida, USA.ORCID https://orcid.org/0000-0001-7509-6156
Colin O'ConnorDepartment of Internal Medicine, Section Infectious Disease, Orlando VA Healthcare System, Orlando, Florida, USA.
Karine Rozenberg-Ben-DrorVISN 12 Pharmacy Benefit Management, Veterans Affairs Great Lakes Health Care System, Westchester, Illinois, USA.ORCID https://orcid.org/0000-0002-4056-0737
Mohammed S AhmedDepartment of Internal Medicine, Section Infectious Disease, Orlando VA Healthcare System, Orlando, Florida, USA.
Karen SlazinskiDepartment of Internal Medicine, Section Infectious Disease, Orlando VA Healthcare System, Orlando, Florida, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: People who inject drugs (PWID) face disproportionate risks for infectious diseases yet remain difficult to identify within health care systems. Natural language processing (NLP) offers potential solutions for identifying PWID to improve access to harm reduction services. Methods: We evaluated an NLP dashboard designed to identify Veterans with evidence of injection drug use across 6 Veterans Health Administration facilities between August and October 2024. Four independent reviewers assessed electronic health records to confirm recent injection drug use and evaluated preventive care delivery, including HIV/hepatitis screening, sexually transmitted infection testing, preexposure prophylaxis usage, and harm reduction services. Results: Among 502 075 veterans, the dashboard identified 507 potential PWID, with 78 (15%) confirmed through chart review. Of confirmed PWID, 49% injected opiates, 41% cocaine, and 37% methamphetamines. HIV prevalence was 6%, hepatitis C antibody positivity 45% (28% viremic), and hepatitis B exposure 13%. Despite 94% engaging with mental health services and 82% with social work, only 29% saw infectious disease specialists. Most PWID (88%) had not received syringes, 74% lacked recent gonorrhea/chlamydia screening, and only 1 received HIV preexposure prophylaxis. Independent reviewers completed most chart reviews within 1 to 2 minutes. Conclusions: The NLP dashboard efficiently identified PWID within an extensive health care system, revealing significant gaps in preventive care delivery despite high engagement with mental health services. Findings suggest opportunities to leverage existing therapeutic relationships while enhancing collaboration among mental health, social work, and infectious disease services to improve care for this vulnerable population.

Indexed as

Human immunodeficiency virusnatural language processingpeople who inject drugsPre-exposure prophylaxisveterans health care system

Identifiers

PMID40242073
PMCPMC12001329

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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.