TABLE 2.

Prediction model performance.

	Critical care outcome		Inpatient care outcome
	Derivation cohort	Validation cohort	Derivation cohort	Validation cohort
Spatial method
Model 1	0.86(0.84–0.88)	0.89(0.86–0.91)	0.86(0.84–0.88)	0.83(0.81–0.86)
Model 2	0.89(0.87–0.91)	0.89(0.87–0.92)	0.88(0.87–0.90)	0.86(0.83–0.88)
Model 3	0.90(0.89–0.92)	0.9(0.87–0.92)	0.90(0.88–0.91)	0.86(0.84–0.89)
Temporal method
Model 1	0.87(0.84–0.89)	0.87(0.83–0.91)	0.85(0.83–0.86)	0.86(0.83–0.88)
Model 2	0.88(0.86–0.90)	0.90(0.87–0.93)	0.87(0.86–0.89)	0.88(0.85–0.90)
Model 3	0.89(0.86–0.91)	0.89(0.86–0.93)	0.89(0.87–0.90)	0.90(0.88–0.93)

For each method, three models of increasing complexity were tested. Model 1 included predictors available at emergency department (ED) triage only (demographics, triage vitals, chief complaint, active medical problems). ED laboratory results were added to model 2. ED oxygen requirements, last vital signs measured prior to disposition decision and vital sign trends were added to model 3. Model prediction performance is shown as area under the receiver operating characteristic curve (AUC) with 95% confidence intervals in parentheses.