Understanding Expert Exploration in EHR Visualization Tools: The ParcoursVis Use Case

We introduce our ongoing work toward an insight-based evaluation methodology aimed at understanding practitioners’ mental models when exploring medical data. It is based on ParcoursVis, a Progressive Visual Analytics system designed to visualize event sequences derived from Electronic Health Records at scale (millions of patients, billions of events), developed in collaboration with the Emergency Departments of 16 Parisian hospitals and with the French Social Security. Building on prior usability validation, our current evaluation focuses on the insights generated by expert users and aims to better understand the exploration strategies they employ when engaging with exploration visualization tools. We describe our system and outline our evaluation protocol, analysis strategy, and preliminary findings. Building on this approach and our pilot results, we contribute a design protocol for conducting insight-based studies under real-world constraints, including the availability of health practitioners whom we were fortunate to interview. Our findings highlight a loop, where the use of the system helps refine data variables identification and the system itself. We aim to shed light on generated insights, to highlight the utility of exploratory tools in health data analysis contexts.

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Publication Details

Published
2025-11-02
DOI
https://doi.org/10.1109/vahc69430.2025.00005
Primary Topic
Data Visualization and Analytics
Type
article
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article

Understanding Expert Exploration in EHR Visualization Tools: The ParcoursVis Use Case

Jean‐Daniel Fekete, Ambre Assor
Data Visualization and Analytics
article

Understanding Expert Exploration in EHR Visualization Tools: The ParcoursVis Use Case

Jean‐Daniel Fekete, Ambre Assor
article en

Abstract

We introduce our ongoing work toward an insight-based evaluation methodology aimed at understanding practitioners’ mental models when exploring medical data. It is based on ParcoursVis, a Progressive Visual Analytics system designed to visualize event sequences derived from Electronic Health Records at scale (millions of patients, billions of events), developed in collaboration with the Emergency Departments of 16 Parisian hospitals and with the French Social Security. Building on prior usability validation, our current evaluation focuses on the insights generated by expert users and aims to better understand the exploration strategies they employ when engaging with exploration visualization tools. We describe our system and outline our evaluation protocol, analysis strategy, and preliminary findings. Building on this approach and our pilot results, we contribute a design protocol for conducting insight-based studies under real-world constraints, including the availability of health practitioners whom we were fortunate to interview. Our findings highlight a loop, where the use of the system helps refine data variables identification and the system itself. We aim to shed light on generated insights, to highlight the utility of exploratory tools in health data analysis contexts.

Centre National de la Recherche Scientifique (FR), Université Paris-Saclay (FR), Centre Inria de Saclay (FR)
Openalex Percentile: Top 62%
Data Visualization and Analytics
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