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Integrating patient voices into the extraction of social determinants of health from clinical notes: ethical considerations and recommendations.
Hartzler, Andrea L; Xie, Serena Jinchen; Wedgeworth, Patrick; Spice, Carolin; Lybarger, Kevin; Wood, Brian R; Duber, Herbert C; Hsieh, Gary; Singh, Angad P.
Afiliación
  • Hartzler AL; Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.
  • Xie SJ; Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.
  • Wedgeworth P; Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.
  • Spice C; Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.
  • Lybarger K; Department of Information Sciences and Technology, George Mason University, Fairfax, Virginia, USA.
  • Wood BR; Department of Medicine, University of Washington, Seattle, Washington, USA.
  • Duber HC; Department of Health, Washington State, Olympia, Washington, USA.
  • Hsieh G; Department of Emergency Medicine, University of Washington, Seattle, Washington, USA.
  • Singh AP; Human Centered Design and Engineering, University of Washington, Seattle, Washington, USA.
J Am Med Inform Assoc ; 30(8): 1456-1462, 2023 07 19.
Article en En | MEDLINE | ID: mdl-36944091
Identifying patients' social needs is a first critical step to address social determinants of health (SDoH)-the conditions in which people live, learn, work, and play that affect health. Addressing SDoH can improve health outcomes, population health, and health equity. Emerging SDoH reporting requirements call for health systems to implement efficient ways to identify and act on patients' social needs. Automatic extraction of SDoH from clinical notes within the electronic health record through natural language processing offers a promising approach. However, such automated SDoH systems could have unintended consequences for patients, related to stigma, privacy, confidentiality, and mistrust. Using Floridi et al's "AI4People" framework, we describe ethical considerations for system design and implementation that call attention to patient autonomy, beneficence, nonmaleficence, justice, and explicability. Based on our engagement of clinical and community champions in health equity work at University of Washington Medicine, we offer recommendations for integrating patient voices and needs into automated SDoH systems.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Equidad en Salud / Determinantes Sociales de la Salud Tipo de estudio: Guideline Aspecto: Determinantes_sociais_saude / Equity_inequality / Ethics Límite: Humans Idioma: En Revista: J Am Med Inform Assoc Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Equidad en Salud / Determinantes Sociales de la Salud Tipo de estudio: Guideline Aspecto: Determinantes_sociais_saude / Equity_inequality / Ethics Límite: Humans Idioma: En Revista: J Am Med Inform Assoc Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido