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Hospital coronavirus disease 2019 (COVID-19) public health reporting: Lessons from validation of an automated surveillance tool to facilitate data collection.
Gamage, Shantini D; Evans, Martin E; McCauley, Brian P; Lipscomb, Karen R; Flarida, Linda; Jones, Makoto M; Baza, Michael; Barraza, Jeremy; Simbartl, Loretta A; Roselle, Gary A.
Afiliação
  • Gamage SD; National Infectious Diseases Service, Specialty Care Services, Veterans Health Administration, US Department of Veterans Affairs, Washington, DC.
  • Evans ME; Division of Infectious Diseases, Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, Ohio.
  • McCauley BP; National Infectious Diseases Service, Specialty Care Services, Veterans Health Administration, US Department of Veterans Affairs, Washington, DC.
  • Lipscomb KR; Lexington Veterans Affairs (VA) Healthcare System, Lexington, Kentucky.
  • Flarida L; Division of Infectious Diseases, Department of Internal Medicine, University of Kentucky School of Medicine, Lexington, Kentucky.
  • Jones MM; National Infectious Diseases Service, Specialty Care Services, Veterans Health Administration, US Department of Veterans Affairs, Washington, DC.
  • Baza M; National Infectious Diseases Service, Specialty Care Services, Veterans Health Administration, US Department of Veterans Affairs, Washington, DC.
  • Barraza J; National Infectious Diseases Service, Specialty Care Services, Veterans Health Administration, US Department of Veterans Affairs, Washington, DC.
  • Simbartl LA; VA Salt Lake City Healthcare System, Salt Lake City, Utah.
  • Roselle GA; Divison of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah.
Infect Control Hosp Epidemiol ; 44(5): 802-804, 2023 05.
Article em En | MEDLINE | ID: mdl-35351223
A comparison of computer-extracted and facility-reported counts of hospitalized coronavirus disease 2019 (COVID-19) patients for public health reporting at 36 hospitals revealed 42% of days with matching counts between the data sources. Miscategorization of suspect cases was a primary driver of discordance. Clear reporting definitions and data validation facilitate emerging disease surveillance.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Saúde Pública / COVID-19 Tipo de estudo: Screening_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Saúde Pública / COVID-19 Tipo de estudo: Screening_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article