Table 1.

Cohort characteristics and dataset splits used for model development and evaluation. After final model selection, the full dataset from 2020 to 2023 (model development) was used to train the Predictive Risk Identification for Mental Health Events, which was evaluated using 2024 (model evaluation) data to assess real-world performance.

			Model development (2020-2023)									Model evaluation (2024)—evaluation set (48,313)
			Held-out patients				Out-of-time patients
Data split (number of patient encounters)			Development set (281,022)		Test set (73,763)		Development set (259,257)		Test set (95,528)
Patients, n (%)			3000 (80)		751 (20)		2851 (70.3)		1202 (29.7)		900 (100)
Period			January 1, 2020, to December 31, 2023		January 1, 2020, to December 31, 2023		January 1, 2020, to December 31, 2022		January 1, 2023, to December 31, 2023		January 1, 2024, to August 19, 2024
LOSa, mean (SD)			629.22 (632.67)		530.41 (654.51)		708.04 (676.56)		336.90 (390.40)		134.99 (117.83)
Sex, n (%)
	Female	839 (27.98)		231 (30.81)		845 (29.63)		310 (25.75)		235 (26.05)
	Male	2045 (68.17)		502 (66.82)		1912 (67.08)		842 (70.05)		633 (70.37)
	Other	116 (3.85)		18 (2.37)		94 (3.29)		50 (4.20)		32 (3.58)
Sexual orientation, n (%)
	Heterosexual	1878 (62.59)		472 (62.90)		1833 (64.31)		699 (58.15)		541 (60.14)
	Other	1122 (37.41)		279 (37.10)		1018 (35.69)		503 (41.85)		359 (39.86)
Race, n (%)
	Black	273 (9.10)		36 (4.73)		224 (7.85)		109 (9.03)		73 (8.10)
	First Nations	61 (2.05)		18 (2.45)		63 (2.21)		23 (1.92)		19 (2.13)
	White	1987 (66.23)		572 (76.20)		2000 (70.15)		763 (63.49)		570 (63.28)
	Other races	679 (22.62)		125 (16.62)		564 (19.78)		307 (25.57)		238 (26.49)
Incident prevalence
	Total number of incidents	11,744		2569		10,688		3625		2106
	Patients, n (%)	762		209		766		342		266

^aLOS: length of stay in days.