Prehospital Risk Score Predicting Critical Illness

We gathered EMS incident reports for each patient encounter from a computerized database (emsCharts, Inc; Warrendale, PA). Data included dispatch and response times, demographics, first recorded prehospital vital signs, and Glasgow Coma Scale (GCS). Data were used to calculate a validated prehospital risk score, a multivariable score that predicts development of in-hospital critical illness using prehospital clinical variables including age, systolic blood pressure, heart rate, pulse oximetry and GCS.^{15 (link),16 (link)} A Computer Aided Dispatch program integrated with 9-1-1 dispatch provided date and time data for medical contact and hospital arrival times.
We linked prehospital data with electronic health record data at UPMC hospitals using patient identifiers collected in the ED by research assistants (Cerner Powerchart; Cerner, Kansas City, MO) From the inpatient record, we determined intensive care unit (ICU) admission, hospital and ICU length of stay (LOS), and in-hospital mortality. International Classification of Diseases, 9^th Revision (ICD-9) codes determined the Elixhauser Comorbidity Index.^{17 (link)}