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Implementation of a digital chatbot to screen health system employees during the COVID-19 pandemic.
Judson, Timothy J; Odisho, Anobel Y; Young, Jerry J; Bigazzi, Olivia; Steuer, David; Gonzales, Ralph; Neinstein, Aaron B.
  • Judson TJ; Department of Medicine, University of California, San Francisco, San Francisco, California, USA.
  • Odisho AY; Clinical Innovation Center, University of California, San Francisco, San Francisco, California, USA.
  • Young JJ; Center for Digital Health Innovation, University of California, San Francisco, San Francisco, California, USA.
  • Bigazzi O; Department of Urology, University of California, San Francisco, San Francisco, California, USA.
  • Steuer D; Center for Digital Health Innovation, University of California, San Francisco, San Francisco, California, USA.
  • Gonzales R; Center for Digital Health Innovation, University of California, San Francisco, San Francisco, California, USA.
  • Neinstein AB; Center for Digital Health Innovation, University of California, San Francisco, San Francisco, California, USA.
J Am Med Inform Assoc ; 27(9): 1450-1455, 2020 07 01.
Article in English | MEDLINE | ID: covidwho-766656
ABSTRACT
The screening of healthcare workers for COVID-19 (coronavirus disease 2019) symptoms and exposures prior to every clinical shift is important for preventing nosocomial spread of infection but creates a major logistical challenge. To make the screening process simple and efficient, University of California, San Francisco Health designed and implemented a digital chatbot-based workflow. Within 1 week of forming a team, we conducted a product development sprint and deployed the digital screening process. In the first 2 months of use, over 270 000 digital screens have been conducted. This process has reduced wait times for employees entering our hospitals during shift changes, allowed for physical distancing at hospital entrances, prevented higher-risk individuals from coming to work, and provided our healthcare leaders with robust, real-time data for make staffing decisions.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Health Personnel / Coronavirus Infections / Clinical Laboratory Techniques / Mobile Applications / Betacoronavirus Type of study: Case report / Diagnostic study / Observational study / Prognostic study Limits: Humans Country/Region as subject: North America Language: English Journal: J Am Med Inform Assoc Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: Jamia

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Health Personnel / Coronavirus Infections / Clinical Laboratory Techniques / Mobile Applications / Betacoronavirus Type of study: Case report / Diagnostic study / Observational study / Prognostic study Limits: Humans Country/Region as subject: North America Language: English Journal: J Am Med Inform Assoc Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: Jamia