Table 3.

Ranked as important^a by respondents for prioritization of machine learning.

Attributes considered important	SickKids (n=195), n (%)	Lucile Packard Children’s Hospital (n=80), n (%)	P-value	Median importance score (IQR)b
The clinical problem being solved is common	66 (33.8)	35 (43.8)	.16	3 (2-3)
The clinical problem causes substantial morbidity or mortality	133 (68.2)	44 (55.0)	.05	2 (2-3)
Risk stratification would lead to different clinical actions that could reasonably improve patient outcomes	145 (74.4)	60 (75.0)	>.99	1 (1-2)
Implementing the model could reduce physician workload	29 (14.9)	11 (13.8)	.96	4 (3-4)
Implementing the model could save money	11 (5.6)	2 (2.5)	.42	5 (4-5)

^aImportant defined as attributes ranked as most important or second most important (rank of 1 or 2) in terms of whether a machine learning model would be useful.

^bAcross both institutions.