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 - Takeaways - MDSpire

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

  • By

  • Minh Q Ho

  • Colin O’Connor

  • Karine Rozenberg-Ben-Dror

  • Mohammed S Ahmed

  • Karen Slazinski

  • March 5, 2025

  • 0 min

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  • 1

    Natural language processing (NLP) effectively identifies veterans engaged in injection drug use within the Veterans Health Administration.

  • 2

    Among 502,075 veterans, the NLP dashboard identified 507 potential people who inject drugs (PWID), with 78 confirmed through chart review.

  • 3

    Confirmed PWID showed high rates of infectious diseases: 6% HIV prevalence and 45% hepatitis C antibody positivity.

  • 4

    Despite high engagement with mental health services, only 29% of PWID consulted infectious disease specialists.

  • 5

    The study highlights significant gaps in preventive care delivery for PWID, indicating a need for improved health service collaboration.

Original Source(s)

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

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

  • March 5, 2025

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