Current state of trauma care in China, tools to predict death and ICU admission after arrival to hospital

Abstract

Background: In China, a nationwide emergency system takes charge of pre-hospital emergency services, and it adopts a proximity principle to send trauma patients to the nearest hospitals. However, many severely injured patients have been sent to low level hospitals with no capability to treat severe trauma. Thus those patients with high probability of in-hospital death or intensive care unit (ICU) admission need to be identified in the emergency department (ED) for optimal utilisation of hospital resources and better patient outcomes. The purpose of the study was to develop a computerised tool to aid ED physicians' prediction of in-hospital death and ICU admission for trauma patients after arrival to hospital.

Methods: We reviewed a sample of 1,299 trauma patients who had been directly sent to the ED at Kailuan Hospital, North China. After excluding those cases with incomplete data entry, information of 1,195 patients was employed for analysis. The primary outcome was severe trauma that either resulted in death in hospital or in ICU admission. We proposed to use a complementary approach to combine the Pre-Hospital Index (PHI), the Trauma Index (TI), and the Glasgow Coma Score (GCS) in a decision support system (DSS) to assess trauma and predict in-hospital death and ICU admission. The sensitivity, specificity, over-triage rate, and under-triage rate were used as measurements to compare system performances of the DSS with the three scoring tools.

Results: Among the 1,195 patients, 30 (2.5%) had severe trauma. The proposed DSS showed the best sensitivity (66.7%; 95% CI: 49.8-83.6%) among all the four studied tools. The TI (sensitivity 50.0%, 95% CI: 32.2-67.8%) performed slightly better than the GCS (sensitivity 46.7%, 95% CI: 28.9-64.5%), while both the TI and GCS performed better than the PHI (sensitivity 30.0%, 95% CI: 13.5-46.5%). The performance differences between the DSS and the three extant scoring tools were statistically significant.

Conclusions: The proposed DSS outperformed the extant trauma scoring systems. It has a strong potential to help ED physicians identify severe trauma, optimally utilise hospital resources, and recommend appropriate triage and treatment strategies for trauma patients that have strong possibilities for in-hospital death and ICU admission.

Keywords: Decision support system; ICU admission; In-hospital death; Sensitivity; Specificity; Trauma.