Best practices for data visualization: creating and evaluating a report for an evidence-based fall prevention program. (7th November 2019)

• Record Type: Journal Article
• Authors: Khasnabish, Srijesa; Burns, Zoe; Couch, Madeline; Mullin, Mary; Newmark, Randall; Dykes, Patricia C
• Is Part Of: Journal of the American Medical Informatics Association. Volume 27:Number 2(2020)
• Page Start: 308
• Page End: 314
• Publication Date: 2019-11-07
• Subjects: data visualization -- evidence-based -- fall prevention -- health-ITUES -- usability; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocz190
• Languages: English
• ISSNs: 1067-5027

Abstract

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.