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Appl Clin Inform 2024; 15(02): 250-264
DOI: 10.1055/a-2269-0995
Research Article

HistoriView: Implementation and Evaluation of a Novel Approach to Review a Patient Using a Scalable Space-Efficient Timeline without Zoom Interactions

Heekyong Park
1   Department of Research Information Science and Computing, Mass General Brigham, Somerville, Massachusetts, United States
,
Taowei David Wang
1   Department of Research Information Science and Computing, Mass General Brigham, Somerville, Massachusetts, United States
2   Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States
,
Nich Wattanasin
1   Department of Research Information Science and Computing, Mass General Brigham, Somerville, Massachusetts, United States
,
Victor M. Castro
1   Department of Research Information Science and Computing, Mass General Brigham, Somerville, Massachusetts, United States
,
Vivian Gainer
1   Department of Research Information Science and Computing, Mass General Brigham, Somerville, Massachusetts, United States
,
Shawn Murphy
1   Department of Research Information Science and Computing, Mass General Brigham, Somerville, Massachusetts, United States
2   Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States
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Abstract

Background Timelines have been used for patient review. While maintaining a compact overview is important, merged event representations caused by the intricate and voluminous patient data bring event recognition, access ambiguity, and inefficient interaction problems. Handling large patient data efficiently is another challenge.

Objective This study aims to develop a scalable, efficient timeline to enhance patient review for research purposes. The focus is on addressing the challenges presented by the intricate and voluminous patient data.

Methods We propose a high-throughput, space-efficient HistoriView timeline for an individual patient. For a compact overview, it uses nonstacking event representation. An overlay detection algorithm, y-shift visualization, and popup-based interaction facilitate comprehensive analysis of overlapping datasets. An i2b2 HistoriView plugin was deployed, using split query and event reduction approaches, delivering the entire history efficiently without losing information. For evaluation, 11 participants completed a usability survey and a preference survey, followed by qualitative feedback. To evaluate scalability, 100 randomly selected patients over 60 years old were tested on the plugin and were compared with a baseline visualization.

Results Most participants found that HistoriView was easy to use and learn and delivered information clearly without zooming. All preferred HistoriView over a stacked timeline. They expressed satisfaction on display, ease of learning and use, and efficiency. However, challenges and suggestions for improvement were also identified. In the performance test, the largest patient had 32,630 records, which exceeds the baseline limit. HistoriView reduced it to 2,019 visual artifacts. All patients were pulled and visualized within 45.40 seconds. Visualization took less than 3 seconds for all.

Discussion and Conclusion HistoriView allows complete data exploration without exhaustive interactions in a compact overview. It is useful for dense data or iterative comparisons. However, issues in exploring subconcept records were reported. HistoriView handles large patient data preserving original information in a reasonable time.

Keywords

data visualization - analytics - electronic health records - chart review - user interaction - scalable timeline

Protection of Human and Animal Subjects

This study was approved by the Institutional Review Board (IRB) of Mass General Brigham under protocols Mass General Brigham Biobank (2009P002312). The Mass General Brigham Institutional Review Board approved for a waiver of patient informed consent.




Publication History

Received: 08 September 2023

Accepted: 08 November 2023

Accepted Manuscript online:
15 February 2024

Article published online:
03 April 2024

© 2024. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

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