ClinicalPath: a Visualization tool to Improve the Evaluation of Electronic Health Records in Clinical Decision-Making

Claudio D. G. Linhares, Daniel M. Lima, Jean R. Ponciano, Mauro M. Olivatto, Marco A. Gutierrez, Jorge Poco, Caetano Traina Jr., Agma J. M. Traina

View presentation:2022-10-21T14:00:00ZGMT-0600Change your timezone on the schedule page
2022-10-21T14:00:00Z
Exemplar figure, described by caption below
Example of the Clinical path visualization divided into the main features: (A) Categorization of the tests; (B) Timestamp information with color codding, note that the dates follow the date format (dd/MM/yyyy); (C) Color and shape codding (symbols) for the test results; and (D) Line chart with the test result variation over time; (E) Line chart combining different test results over time; (F) Automatic highlighting relevant changes in tests results over time; (G) Patient global and local information over time; (H) Line chart showing patient information over time.

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Keywords

Information Visualization, Interactive Visualizations, Human-Computer Interaction, Electronic Health Records

Abstract

Physicians work at a very tight schedule and need decision-making support tools to help on improving and doing their work in a timely and dependable manner. Examining piles of sheets with test results and using systems with little visualization support to provide diagnostics is daunting, but that is still the usual way for the physicians' daily procedure, especially in developing countries. Electronic Health Records systems have been designed to keep the patients' history and reduce the time spent analyzing the patient's data. However, better tools to support decision-making are still needed. In this paper, we propose \systemname, a visualization tool for users to track a patient's clinical path through a series of tests and data, which can aid in treatments and diagnoses. Our proposal is focused on patient's data analysis, presenting the test results and clinical history longitudinally. Both the visualization design and the system functionality were developed in close collaboration with experts in the medical domain to ensure a right fit of the technical solutions and the real needs of the professionals. We validated the proposed visualization based on case studies and user assessments through tasks based on the physician's daily activities. Our results show that our proposed system improves the physicians' experience in decision-making tasks, made with more confidence and better usage of the physicians' time, allowing them to take other needed care for the patients.