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Repurposing Clinical Decision Support System Data to Measure Dosing Errors and Clinician-Level Quality of Care.
Chin, David L; Wilson, Michelle H; Trask, Ashley S; Johnson, Victoria T; Neaves, Brittanie I; Gojova, Andrea; Hogarth, Michael A; Bang, Heejung; Romano, Patrick S.
Afiliação
  • Chin DL; Department of Health Promotion and Policy, School of Public Health and Health Sciences, University of Massachusetts Amherst, Arnold House 331 | 715 N. Pleasant Street, MA, 01003, Amherst, USA. dchin@umass.edu.
  • Wilson MH; Department of Internal Medicine, Santa Clara Valley Medical Center, San Jose, CA, USA.
  • Trask AS; Department of Pharmacy, University of California Davis Health System, Sacramento, CA, USA.
  • Johnson VT; Consultative Internal Medicine, for Group Health Physicians Washington Permanente Medical Group, Seattle, WA, USA.
  • Neaves BI; Department of Allergy and Immunology, Wilford Hall Ambulatory Surgical Center, San Antonio, TX, USA.
  • Gojova A; Department of Pharmacy, University of California Davis Health System, Sacramento, CA, USA.
  • Hogarth MA; Department of Internal Medicine, Division of Biomedical Informatics, University of California San Diego, School of Medicine, San Diego, CA, USA.
  • Bang H; Center for Healthcare Policy and Research, University of California, Davis, Sacramento, CA, USA.
  • Romano PS; Center for Healthcare Policy and Research, University of California, Davis, Sacramento, CA, USA.
J Med Syst ; 44(10): 185, 2020 Sep 08.
Article em En | MEDLINE | ID: mdl-32897483
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Médicos / Sistemas de Apoio a Decisões Clínicas / Sistemas de Registro de Ordens Médicas / Prescrição Eletrônica Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Médicos / Sistemas de Apoio a Decisões Clínicas / Sistemas de Registro de Ordens Médicas / Prescrição Eletrônica Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article