Best practices for data visualization: creating and evaluating a report for an evidence-based fall prevention program
Author(s) -
Srijesa Khasnabish,
Zoe Burns,
Madeline Couch,
Mary Mullin,
Randall E. Newmark,
Patricia C. Dykes
Publication year - 2019
Publication title -
journal of the american medical informatics association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.614
H-Index - 150
eISSN - 1527-974X
pISSN - 1067-5027
DOI - 10.1093/jamia/ocz190
Subject(s) - bar chart , usability , likert scale , computer science , visualization , scale (ratio) , test (biology) , medical education , psychology , applied psychology , medicine , artificial intelligence , human–computer interaction , statistics , mathematics , quantum mechanics , developmental psychology , biology , paleontology , physics
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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