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Use of a Digital Assistant to Report COVID-19 Rapid Antigen Self-test Results to Health Departments in 6 US Communities.
Herbert, Carly; Shi, Qiming; Kheterpal, Vik; Nowak, Chris; Suvarna, Thejas; Durnan, Basyl; Schrader, Summer; Behar, Stephanie; Naeem, Syed; Tarrant, Seanan; Kalibala, Ben; Singh, Aditi; Gerber, Ben; Barton, Bruce; Lin, Honghuang; Cohen-Wolkowiez, Michael; Corbie-Smith, Giselle; Kibbe, Warren; Marquez, Juan; Baek, Jonggyu; Hafer, Nathaniel; Gibson, Laura; O'Connor, Laurel; Broach, John; Heetderks, William; McManus, David; Soni, Apurv.
Afiliación
  • Herbert C; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester.
  • Shi Q; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester.
  • Kheterpal V; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester.
  • Nowak C; Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester.
  • Suvarna T; CareEvolution, Ann Arbor, Michigan.
  • Durnan B; CareEvolution, Ann Arbor, Michigan.
  • Schrader S; CareEvolution, Ann Arbor, Michigan.
  • Behar S; CareEvolution, Ann Arbor, Michigan.
  • Naeem S; CareEvolution, Ann Arbor, Michigan.
  • Tarrant S; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester.
  • Kalibala B; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester.
  • Singh A; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester.
  • Gerber B; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester.
  • Barton B; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester.
  • Lin H; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester.
  • Cohen-Wolkowiez M; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester.
  • Corbie-Smith G; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester.
  • Kibbe W; Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina.
  • Marquez J; Center for Health Equity Research, Department of Social Medicine, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill.
  • Baek J; Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina.
  • Hafer N; Washtenaw County Health Department, Washtenaw, Michigan.
  • Gibson L; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester.
  • O'Connor L; Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester.
  • Broach J; Division of Infectious Disease, Department of Medicine, University of Massachusetts Chan Medical School, Worcester.
  • Heetderks W; Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester.
  • McManus D; Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester.
  • Soni A; National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, via contract with Kelly Services, Bethesda, Maryland.
JAMA Netw Open ; 5(8): e2228885, 2022 08 01.
Article en En | MEDLINE | ID: mdl-36018589
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Observational_studies / Risk_factors_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: JAMA Netw Open Año: 2022 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Observational_studies / Risk_factors_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: JAMA Netw Open Año: 2022 Tipo del documento: Article