Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Jul 2, 2024
Date Accepted: Jan 23, 2025
Expectations of intensive care physicians regarding an artificial intelligence-based decision support system for weaning from continuous renal replacement therapy: a pre-development survey study
ABSTRACT
Background:
Critically ill patients in Intensive Care Units (ICU) require continuous monitoring, generating vast amounts of data. Clinical decision support systems (CDSS) leveraging artificial intelligence (AI) technologies have shown promise in improving diagnostic, prognostic, and therapeutic decision-making. However, these models are rarely implemented in clinical practice.
Objective:
The aim of this study was to survey ICU physicians to understand their expectations, opinions, and level of knowledge regarding a proposed AI-based CDSS for continuous renal replacement therapy (CRRT) weaning, a clinical decision-making process that is still complex and lacking in guidelines. This will be used to guide the development of a CDSS on which our team is working to ensure user-centered design and successful integration into clinical practice.
Methods:
A prospective cross-sectional survey of French-speaking physicians with clinical activity in intensive care was conducted between December 2023 and April 2024. The questionnaire consisted of 20 questions structured around four axes: overview of the problem and current practices concerning weaning from CRRT, opinion on clinical decision support systems, implementation in daily clinical practice, and real-life operation and willingness to adopt the CDSS in everyday practice.
Results:
A total of 171 complete responses were received. Physicians expressed an interest in a CDSS for CRRT weaning, with 70.2% (120/171) viewing AI tools favorably. Clinicians were divided on the difficulty of the weaning decision (79/171, 46.2% disagreeing and 54/171, 31.6% agreeing), but 66% (113/171) agreed on the value of a CDSS to assist them in this decision with greater adherence in university hospitals (78/102, 76.5% vs. 35/69, 50.7%; P<.001). Most respondents (163/171, 95.3%) emphasized the importance of understanding the model's criteria for predictions.
Conclusions:
Our findings highlight an optimistic attitude among ICU physicians towards AI-based CDSS for CRRT weaning. The results underscore the need for transparency, integration into existing workflows, and alignment with clinicians' decision-making processes. These insights will guide the user-centered development of the CDSS for CRRT weaning. The methodology of this survey may help the development of further pre-development studies accompanying AI-based CDSS projects. Clinical Trial: https://osf.io/u259f
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