PREDICTION OF TIME TO HEMODYNAMIC STABILIZATION OF UNSTABLE INJURED PATIENT ENCOUNTERS USING ELECTRONIC MEDICAL RECORD DATA.

Background

This study sought to predict time to patient hemodynamic stabilization during trauma resuscitations of hypotensive patient encounters using electronic medical record (EMR) data.

Methods

This observational cohort study leveraged EMR data from a nine-hospital academic system composed of Level I, Level II, and nontrauma centers. Injured, hemodynamically unstable (initial systolic blood pressure, <90 mm Hg) emergency encounters from 2015 to 2020 were identified. Stabilization was defined as documented subsequent systolic blood pressure of >90 mm Hg. We predicted time to stabilization testing random forests, gradient boosting, and ensembles using patient, injury, treatment, EPIC Trauma Narrator, and hospital features from the first 4 hours of care.

Results

Of 177,127 encounters, 1,347 (0.8%) arrived hemodynamically unstable; 168 (12.5%) presented to Level I trauma centers, 853 (63.3%) to Level II, and 326 (24.2%) to nontrauma centers. Of those, 747 (55.5%) were stabilized with a median of 50 min (interquartile range, 21-101 min). Stabilization was documented in 94.6% of unstable patient encounters at Level I, 57.6% at Level II, and 29.8% at nontrauma centers ( P < 0.001). Time to stabilization was predicted with a C-index of 0.80. The most predictive features were EPIC Trauma Narrator measures, documented patient arrival, provider examination, and disposition decision. In-hospital mortality was highest at Level I, 3.0% vs. 1.2% at Level II, and 0.3% at nontrauma centers ( P < 0.001). Importantly, nontrauma centers had the highest retriage rate to another acute care hospital (12.0%) compared to Level II centers (4.0%, P < 0.001).

Conclusion

Time to stabilization of unstable injured patients can be predicted with EMR data.