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The potential of virtual triage AI to improve early detection, care acuity alignment, and emergent care referral of life-threatening conditions.
Gellert, George A; Kabat-Karabon, Aleksandra; Gellert, Gabriel L; Raslawska-Socha, Joanna; Gorski, Stanislaw; Price, Tim; Kuszczynski, Kacper; Marcjasz, Natalia; Palczewski, Mateusz; Jaszczak, Jakub; Loh, Irving K; Orzechowski, Piotr M.
Afiliación
  • Gellert GA; Infermedica, Inc, San Antonio, TX, United States.
  • Kabat-Karabon A; Infermedica, Inc, Wroclaw, Poland.
  • Gellert GL; Infermedica, Inc, Toronto, Canada.
  • Raslawska-Socha J; Infermedica, Inc, Wroclaw, Poland.
  • Gorski S; Department of Medical Education, Jagiellonian University Medical College, Kraków, Poland.
  • Price T; Infermedica Inc, London, United Kingdom.
  • Kuszczynski K; Infermedica, Inc, Wroclaw, Poland.
  • Marcjasz N; Infermedica, Inc, Wroclaw, Poland.
  • Palczewski M; Infermedica, Inc, Wroclaw, Poland.
  • Jaszczak J; Pediatric Surgery and Urology Department, Wroclaw Medical University, Wroclaw, Poland.
  • Loh IK; Infermedica, Inc, Wroclaw, Poland.
  • Orzechowski PM; Infermedica, Inc, Wroclaw, Poland.
Front Public Health ; 12: 1362246, 2024.
Article en En | MEDLINE | ID: mdl-38807993
ABSTRACT

Objective:

To evaluate the extent to which patient-users reporting symptoms of five severe/acute conditions requiring emergency care to an AI-based virtual triage (VT) engine had no intention to get such care, and whose acuity perception was misaligned or decoupled from actual risk of life-threatening symptoms.

Methods:

A dataset of 3,022,882 VT interviews conducted over 16 months was evaluated to quantify and describe patient-users reporting symptoms of five potentially life-threatening conditions whose pre-triage healthcare intention was other than seeking urgent care, including myocardial infarction, stroke, asthma exacerbation, pneumonia, and pulmonary embolism.

Results:

Healthcare intent data was obtained for 12,101 VT patient-user interviews. Across all five conditions a weighted mean of 38.5% of individuals whose VT indicated a condition requiring emergency care had no pre-triage intent to consult a physician. Furthermore, 61.5% intending to possibly consult a physician had no intent to seek emergency medical care. After adjustment for 13% VT safety over-triage/referral to ED, a weighted mean of 33.5% of patient-users had no intent to seek professional care, and 53.5% had no intent to seek emergency care.

Conclusion:

AI-based VT may offer a vehicle for early detection and care acuity alignment of severe evolving pathology by engaging patients who believe their symptoms are not serious, and for accelerating care referral and delivery for life-threatening conditions where patient misunderstanding of risk, or indecision, causes care delay. A next step will be clinical confirmation that when decoupling of patient care intent from emergent care need occurs, VT can influence patient behavior to accelerate care engagement and/or emergency care dispatch and treatment to improve clinical outcomes.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Derivación y Consulta / Triaje Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Front Public Health Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Derivación y Consulta / Triaje Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Front Public Health Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza