Testing and improving the acceptability of a web-based platform for collective intelligence to improve diagnostic accuracy in primary care clinics.

Fontil, Valy; Radcliffe, Kate; Lyson, Helena C; Ratanawongsa, Neda; Lyles, Courtney; Tuot, Delphine; Yuen, Kaeli; Sarkar, Urmimala

Fontil, Valy; Radcliffe, Kate; Lyson, Helena C; Ratanawongsa, Neda; Lyles, Courtney; Tuot, Delphine; Yuen, Kaeli; Sarkar, Urmimala.

Afiliação

Fontil V; UCSF Division of General Internal Medicine, San Francisco, California, USA.
Radcliffe K; UCSF Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital, San Francisco, California, USA.
Lyson HC; UCSF Division of General Internal Medicine, San Francisco, California, USA.
Ratanawongsa N; UCSF Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital, San Francisco, California, USA.
Lyles C; UCSF Division of General Internal Medicine, San Francisco, California, USA.
Tuot D; UCSF Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital, San Francisco, California, USA.
Yuen K; UCSF Division of General Internal Medicine, San Francisco, California, USA.
Sarkar U; UCSF Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital, San Francisco, California, USA.

JAMIA Open ; 2(1): 40-48, 2019 Apr.

Article em En | MEDLINE | ID: mdl-31984344

Palavras-chave

clinical reasoning; collective intelligence; diagnostic accuracy; diagnostic error; human diagnosis project

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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies / Qualitative_research Idioma: En Revista: JAMIA Open Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos

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