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Developing a sampling method and preliminary taxonomy for classifying COVID-19 public health guidance for healthcare organizations and the general public.
Taber, Peter; Staes, Catherine J; Phengphoo, Saifon; Rocha, Elisa; Lam, Adria; Del Fiol, Guilherme; Maviglia, Saverio M; Rocha, Roberto A.
Afiliação
  • Taber P; Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States. Electronic address: peter.taber@hsc.utah.edu.
  • Staes CJ; Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States; College of Nursing, University of Utah, Salt Lake City, UT, United States.
  • Phengphoo S; Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States; College of Nursing, University of Utah, Salt Lake City, UT, United States.
  • Rocha E; University of Massachusetts Medical School, Worcester, MA, United States.
  • Lam A; Albany Medical College, Albany, NY, United States.
  • Del Fiol G; Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States.
  • Maviglia SM; Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Semedy, Inc, Needham, MA, United States.
  • Rocha RA; Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Semedy, Inc, Needham, MA, United States.
J Biomed Inform ; 120: 103852, 2021 08.
Article em En | MEDLINE | ID: mdl-34192573
BACKGROUND: Development and dissemination of public health (PH) guidance to healthcare organizations and the general public (e.g., businesses, schools, individuals) during emergencies like the COVID-19 pandemic is vital for policy, clinical, and public decision-making. Yet, the rapidly evolving nature of these events poses significant challenges for guidance development and dissemination strategies predicated on well-understood concepts and clearly defined access and distribution pathways. Taxonomies are an important but underutilized tool for guidance authoring, dissemination and updating in such dynamic scenarios. OBJECTIVE: To design a rapid, semi-automated method for sampling and developing a PH guidance taxonomy using widely available Web crawling tools and streamlined manual content analysis. METHODS: Iterative samples of guidance documents were taken from four state PH agency websites, the US Center for Disease Control and Prevention, and the World Health Organization. Documents were used to derive and refine a preliminary taxonomy of COVID-19 PH guidance via content analysis. RESULTS: Eight iterations of guidance document sampling and taxonomy revisions were performed, with a final corpus of 226 documents. The preliminary taxonomy contains 110 branches distributed between three major domains: stakeholders (24 branches), settings (25 branches) and topics (61 branches). Thematic saturation measures indicated rapid saturation (≤5% change) for the domains of "stakeholders" and "settings", and "topic"-related branches for clinical decision-making. Branches related to business reopening and economic consequences remained dynamic throughout sampling iterations. CONCLUSION: The PH guidance taxonomy can support public health agencies by aligning guidance development with curation and indexing strategies; supporting targeted dissemination; increasing the speed of updates; and enhancing public-facing guidance repositories and information retrieval tools. Taxonomies are essential to support knowledge management activities during rapidly evolving scenarios such as disease outbreaks and natural disasters.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Saúde Pública / COVID-19 Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: J Biomed Inform Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Saúde Pública / COVID-19 Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: J Biomed Inform Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article