PREDICTION OF TIME TO HEMODYNAMIC STABILIZATION OF UNSTABLE INJURED PATIENT ENCOUNTERS USING ELECTRONIC MEDICAL
Allison Carroll1, Ravi Garg1, Alona Furmanchuk1
1Feinberg School of Medicine, Northwestern University, Chicago, Illinois.
Abstract:
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.
