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Best practices for data visualization: creating and evaluating a report for an evidence-based fall prevention program.
Khasnabish, Srijesa; Burns, Zoe; Couch, Madeline; Mullin, Mary; Newmark, Randall; Dykes, Patricia C.
Afiliação
  • Khasnabish S; Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
  • Burns Z; Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
  • Couch M; Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
  • Mullin M; Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
  • Newmark R; Research Computing, Partners Healthcare, Boston, Massachusetts, USA.
  • Dykes PC; Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
J Am Med Inform Assoc ; 27(2): 308-314, 2020 02 01.
Article em En | MEDLINE | ID: mdl-31697326
ABSTRACT
This case report applied principles from the data visualization (DV) literature and feedback from nurses to develop an effective report to display adherence with an evidence-based fall prevention program. We tested the usability of the original and revised reports using a Health Information Technology Usability Evaluation Scale (Health-ITUES) customized for this project. Items were rated on a 5-point Likert scale, strongly disagree (1) to strongly agree (5). The literature emphasized that the ideal display maximizes the information communicated, minimizes the cognitive efforts involved with interpretation, and selects the correct type of display (eg, bar versus line graph). Semi-structured nurse interviews emphasized the value of simplified reports and meaningful data. The mean (standard deviation [SD]) Health-ITUES score for the original report was 3.86 (0.19) and increased to 4.29 (0.11) in the revised report (Mann Whitney U Test, z = -12.25, P < 0.001). Lessons learned from this study can inform report development for clinicians in implementation science.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Acidentes por Quedas / Gráficos por Computador / Gestão da Segurança / Visualização de Dados Tipo de estudo: Evaluation_studies / Guideline / Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Acidentes por Quedas / Gráficos por Computador / Gestão da Segurança / Visualização de Dados Tipo de estudo: Evaluation_studies / Guideline / Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article