Intensive Care Unit Physicians’ Perspectives on Artificial Intelligence–Based Clinical Decision Support Tools: Preimplementation Survey Study
JMIR Human Factors, vol. 10, pp. e39114
Abstract
BACKGROUND: Artificial intelligence-based clinical decision support (AI-CDS) tools have great potential to benefit intensive care unit (ICU) patients and physicians. There is a gap between the development and implementation of these tools. OBJECTIVE: We aimed to investigate physicians' perspectives and their current decision-making behavior before implementing a discharge AI-CDS tool for predicting readmission and mortality risk after ICU discharge. METHODS: We conducted a survey of physicians involved in decision-making on discharge of patients at two Dutch academic ICUs between July and November 2021. Questions were divided into four domains: (1) physicians' current decision-making behavior with respect to discharging ICU patients, (2) perspectives on the use of AI-CDS tools in general, (3) willingness to incorporate a discharge AI-CDS tool into daily clinical practice, and (4) preferences for using a discharge AI-CDS tool in daily workflows. RESULTS: Most of the 64 respondents (of 93 contacted, 69%) were familiar with AI (62/64, 97%) and had positive expectations of AI, with 55 of 64 (86%) believing that AI could support them in their work as a physician. The respondents disagreed on whether the decision to discharge a patient was complex (23/64, 36% agreed and 22/64, 34% disagreed); nonetheless, most (59/64, 92%) agreed that a discharge AI-CDS tool could be of value. Significant differences were observed between physicians from the 2 academic sites, which may be related to different levels of involvement in the development of the discharge AI-CDS tool. CONCLUSIONS: ICU physicians showed a favorable attitude toward the integration of AI-CDS tools into the ICU setting in general, and in particular toward a tool to predict a patient's risk of readmission and mortality within 7 days after discharge. The findings of this questionnaire will be used to improve the implementation process and training of end users.
Authors 7
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Siri Lise van der Meijden Aachen Clinical AI Implementation and Research Lab Department of Intensive Care Medicine
Leiden University Medical Center
Affiliation as printed
Clinical AI Implementation and Research Lab, Leiden University Medical Center, Leiden, Netherlands
Department of Intensive Care Medicine, Leiden University Medical Center, Leiden, Netherlands
Healthplus.ai, Amsterdam, Netherlands
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Anne de Hond Aachen Clinical AI Implementation and Research Lab Department of Biomedical Data Sciences
Leiden University Medical Center
Affiliation as printed
Clinical AI Implementation and Research Lab, Leiden University Medical Center, Leiden, Netherlands
Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
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Amsterdam University Medical Centers
Affiliation as printed
Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam University Medical Centers, Amsterdam, Netherlands
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Leiden University Medical Center
Affiliation as printed
Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
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Ilse M.J. Kant Aachen Clinical AI Implementation and Research Lab Department of Biomedical Data Sciences
Leiden University Medical Center
Affiliation as printed
Clinical AI Implementation and Research Lab, Leiden University Medical Center, Leiden, Netherlands
Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
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Amsterdam University Medical Centers · University of Amsterdam
Affiliation as printed
Department of Medical Informatics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
Institute for Logic, Language and Computation, University of Amsterdam, Amsterdam, Netherlands
Pacmed, Amsterdam, Netherlands
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Leiden University Medical Center
Affiliation as printed
Department of Intensive Care Medicine, Leiden University Medical Center, Leiden, Netherlands
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