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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
Importance: Widespread distribution of rapid antigen tests is integral to the US strategy to address COVID-19; however, it is estimated that few rapid antigen test results are reported to local departments of health. Objective: To characterize how often individuals in 6 communities throughout the United States used a digital assistant to log rapid antigen test results and report them to their local departments of health. Design, Setting, and Participants: This prospective cohort study is based on anonymously collected data from the beneficiaries of the Say Yes! Covid Test program, which distributed more than 3 000 000 rapid antigen tests at no cost to residents of 6 communities (Louisville, Kentucky; Indianapolis, Indiana; Fulton County, Georgia; O'ahu, Hawaii; Ann Arbor and Ypsilanti, Michigan; and Chattanooga, Tennessee) between April and October 2021. A descriptive evaluation of beneficiary use of a digital assistant for logging and reporting their rapid antigen test results was performed. Interventions: Widespread community distribution of rapid antigen tests. Main Outcomes and Measures: Number and proportion of tests logged and reported to the local department of health through the digital assistant. Results: A total of 313 000 test kits were distributed, including 178 785 test kits that were ordered using the digital assistant. Among all distributed kits, 14 398 households (4.6%) used the digital assistant, but beneficiaries reported three-quarters of their rapid antigen test results to their state public health departments (30 965 tests reported of 41 465 total test results [75.0%]). The reporting behavior varied by community and was significantly higher among communities that were incentivized for reporting test results vs those that were not incentivized or partially incentivized (90.5% [95% CI, 89.9%-91.2%] vs 70.5%; [95% CI, 70.0%-71.0%]). In all communities, positive tests were less frequently reported than negative tests (60.4% [95% CI, 58.1%-62.8%] vs 75.5% [95% CI, 75.1%-76.0%]). Conclusions and Relevance: These results suggest that application-based reporting with incentives may be associated with increased reporting of rapid tests for COVID-19. However, increasing the adoption of the digital assistant may be a critical first step.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base 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 Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base 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 Pais de publicación: Estados Unidos