Skip to main content
. 2023 Jan 5;10:e39114. doi: 10.2196/39114

Table 2.

Responses to statements. P values in italics represent a significant difference (P<.05) between the Leiden University Medical Center and Amsterdam University Medical Center respondents. Results are reported on a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Scores >3 indicate median agreement with the statement and results <3 median disagreement.

Question Total, median (IQR) Leiden University Medical Center, median (IQR) Amsterdam University Medical Center, median (IQR) P valuesa
Domain 1: Physicians’ current decision-making behavior with respect to discharging ICUb patients

Q1: “The decision to discharge a patient to a lower care ward is complex” 3 (2-4) 3 (2-3) 4 (2-4) .04

Q2: “A patient’s ICU readmission risk is an important factor in my decision to discharge” 4 (4-4) 4 (4-4) 4 (4-5) .09

Q3: “I take bed availability into account for my decision to discharge a patient” 4 (3-4) 4 (3-4) 4 (3.5-4) .43
Domain 2: Physicians’ perspectives on the use of artificial intelligence (AIc)–based clinical decision support tools in general

Q4: “I am familiar with the concept of AI” 4 (4-4.25) 4 (4-4) 4 (4-5) .004

Q5: “I believe AI could support me in my work as physician” 4 (4-4) 4 (4-4) 4 (4-4.5) .006

Q6: “I believe that AI will take over my job in the future” 2 (2-3) 2 (2-3) 2 (2-2.5) .22

Q7: “I believe AI understands my work sufficiently in order to support me” 3 (3-4) 3 (3-4) 3 (3-4) .39

Q8: “I believe in the added value of AI based decision support at the ICU” 4 (4-4) 4 (4-4) 4 (4-4) .41
Domain 3: Physicians’ willingness to incorporate the discharge decision support tool in daily clinical practice

Q9: “An AI based decision support for ICU readmission could be of positive value in the decision to discharge a patient” 4 (4-4) 4 (4-4) 4 (4-4) .02

Q10: “It is important for me to have insight in the contributing factors to the predicted chance of readmission” 4 (4-4.25) 4 (4-5) 4 (4-4) .03

Q18: “I assume that no readmission risk prediction score could influence my behavior” 2 (2-2) 2 (2-2) 2 (2-2) .11

Q19: “I’m willing to consult the prediction of the decision support tool before making my decision to discharge a patient” 4 (4-4) 4 (4-4) 4 (4-4) .47

Q20: “Taking into account the current workload at my department, I have time to take in the prediction score provided by the decision support tool and to take this into account for my decision to discharge a patient” 4 (4-4) 4 (3-4) 4 (4-4) .11

aP values were calculated with the Mann-Whitney U test.

bICU: intensive care unit.

cAI: artificial intelligence.