Enhancing Clinical Decision Support: A Heuristic Evaluation of Explainable AI in Healthcare Dashboards

Explainable Artificial Intelligence (XAI) is crucial for enhancing transparency, interpretability and actionability of AI systems, particularly in healthcare. The SAD XAI Dashboard, a clinical decision support (CDS) tool for sepsis-associated delirium (SAD), assists physicians in understanding AI-driven predictions for SAD. Our study aimed to evaluate the XAI dashboard's compliance with an XAI usability heuristics checklist. Three experts (human factors and health informatics) applied the heuristics checklist to the dashboard. The evaluation identified several usability issues, including unclear sequences of actions, non-standard icons, and inconsistent labelling. Key trust and transparency heuristics were also absent from the dashboard. This evaluation highlighted key usability gaps relevant for developers and implementers to be aware of in XAI dashboard design. Future research should focus on understanding the impact of usability heuristics on end-user adoption, particularly those relating to trust and transparency.

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Publication Details

Journal
Studies in health technology and informatics
Published
2025-05-15
DOI
https://doi.org/10.3233/shti250341
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
3.89
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article

Enhancing Clinical Decision Support: A Heuristic Evaluation of Explainable AI in Healthcare Dashboards

Romaric Marcilly, Danielle Sent, Bethany A. Van Dort, Linda Peute et al.
1 citations
Studies in health technology and informatics
Artificial Intelligence in Healthcare and Education
3.89
article

Enhancing Clinical Decision Support: A Heuristic Evaluation of Explainable AI in Healthcare Dashboards

Romaric Marcilly, Danielle Sent, Bethany A. Van Dort, Linda Peute, Jarell López Cañizares
article en
1 citations

Abstract

Explainable Artificial Intelligence (XAI) is crucial for enhancing transparency, interpretability and actionability of AI systems, particularly in healthcare. The SAD XAI Dashboard, a clinical decision support (CDS) tool for sepsis-associated delirium (SAD), assists physicians in understanding AI-driven predictions for SAD. Our study aimed to evaluate the XAI dashboard's compliance with an XAI usability heuristics checklist. Three experts (human factors and health informatics) applied the heuristics checklist to the dashboard. The evaluation identified several usability issues, including unclear sequences of actions, non-standard icons, and inconsistent labelling. Key trust and transparency heuristics were also absent from the dashboard. This evaluation highlighted key usability gaps relevant for developers and implementers to be aware of in XAI dashboard design. Future research should focus on understanding the impact of usability heuristics on end-user adoption, particularly those relating to trust and transparency.

Studies in health technology and informaticsVol. 327
Inserm (FR), Tilburg University (NL), Université de Lille (FR), Centre Hospitalier Universitaire de Lille (FR), Amsterdam University Medical Centers (NL), Eindhoven University of Technology (NL), University of Amsterdam (NL)
Peace, Justice and strong institutions
Openalex Percentile: Top 10%
Artificial Intelligence in Healthcare and Education
3.89
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Enhancing Clinical Decision Support: A Heuristic Evaluation of Explainable AI in Healthcare Dashboards — Romaric Marcilly, Danielle Sent, et al. · Studies in health technology and informatics (2025) | TGRS Research Map | TGRS