CC BY 4.0 · ACI Open 2020; 04(01): e35-e43
DOI: 10.1055/s-0040-1702213
Original Article
Georg Thieme Verlag KG Stuttgart · New York

Visualization of Electronic Health Record Data for Decision-Making in Diabetes and Congestive Heart Failure

Shira H. Fischer
1  RAND Corporation, Boston, Massachusetts, United States
2  Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States
3  Division of General Internal Medicine, Brigham & Women's Hospital, Boston, Massachusetts, United States
,
Charles Safran
4  Division of Clinical Informatics, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
,
Krzysztof Z. Gajos
5  Harvard Paulson School of Engineering and Applied Sciences, Cambridge, Massachusetts, United States
,
Adam Wright
6  Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
› Author Affiliations
Funding This work was supported by grant support from NIH training grant T15LM007092.
Further Information

Publication History

06 June 2019

18 December 2019

Publication Date:
25 March 2020 (online)

  

Abstract

Objective The aim of this study is to study the impact of graphical representation of health record data on physician decision-making to inform the design of health information technology.

Materials and Methods We conducted a within participants crossover design study using a simulated electronic health record (EHR) in which we presented cases with and without visualized data designed to highlight important clinical trends or relationships, followed by assessment of the impact on decision-making about next steps for patients with chronic diseases. We then asked whether trends were observed and about usability and satisfaction using validated usability questions and asked open-ended questions as well. Time to answer questions was also collected.

Results Twenty-one primary care providers participated in the study, including five for testing only and sixteen for the full study. Questions about clinical assessment or next actions were answered correctly 55% of the time. Regarding objective trends in the data, participants described noticing the trends 85% of the time. Differences in noticing trends or difficulty level of questions were not statistically significant. Satisfaction with the tool was high and participants agreed strongly that it helped them make better decisions without adding to the time it took.

Discussion The simulation allowed us to test the impact of a visualization on clinician practice in a realistic setting. Designers of EHRs should consider the ways information presentation can affect decision-making.

Conclusion Testing visualization tools can be done in a clinically realistic context. Providers desire visualizations and believe that they help them make better and faster decisions.

Protection of Human and Animal Subjects

This research was reviewed and deemed exempt by the hospital's institutional review board.


Supplementary Material