%0 Journal Article
%@ 2292-9495
%I JMIR Publications
%V 10
%N 
%P e39114
%T Intensive Care Unit Physicians’ Perspectives on Artificial Intelligence–Based Clinical Decision Support Tools: Preimplementation Survey Study
%A van der Meijden,Siri L
%A de Hond,Anne A H
%A Thoral,Patrick J
%A Steyerberg,Ewout W
%A Kant,Ilse M J
%A Cinà,Giovanni
%A Arbous,M Sesmu
%+ Department of Intensive Care Medicine, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, Netherlands, 31 71 526 9111, S.L.van_der_meijden@lumc.nl
%K intensive care unit
%K hospital
%K discharge
%K artificial intelligence
%K AI
%K clinical decision support
%K clinical support
%K acceptance
%K decision support
%K decision-making
%K digital health
%K eHealth
%K survey
%K perspective
%K attitude
%K opinion
%K adoption
%K prediction
%K risk
%D 2023
%7 5.1.2023
%9 Original Paper
%J JMIR Hum Factors
%G English
%X 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. 
%M 36602843
%R 10.2196/39114
%U https://humanfactors.jmir.org/2023/1/e39114
%U https://doi.org/10.2196/39114
%U http://www.ncbi.nlm.nih.gov/pubmed/36602843