Computerized Analysis of Patient Vitals During Trauma Transport Speeds up Diagnosis | Healthcare Informatics Magazine | Health IT | Information Technology Skip to content Skip to navigation

Computerized Analysis of Patient Vitals During Trauma Transport Speeds up Diagnosis

May 15, 2015
by Gabriel Perna
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Researchers in Boston recently determined that automated analysis of vital signs in a patient being transported to a trauma center could speed up diagnosis and potentially save their lives.
A research team from Massachusetts General Hospital (MGH), the U.S. Army, air ambulance service Boston MedFlight, and two other Boston trauma centers developed and tested a system that did just that. During emergency transport, it analyzed a patient's blood pressure, heart rate, and breathing patterns and sent that information to the receiving hospital. The researchers developed software based on statistical techniques currently used in stock market trading and manufacturing industries. 
The researchers collected data on more than 200 trauma patients transported to Boston hospitals from 2010 to 2012. The system, called APPRAISE (Automated Processing of the Physiological Registry for Assessment of Injury Severity), was able to accurately detect a high percentage of when a patient was suffering from life-threatening bleeding. It identified 75 to 80 percent of patients with life-threatening bleeding, compared with 50 percent who were identified by standard clinical practice. They found that notifications provided by the system would have been available within 10 minutes of initial monitoring and as much as 20 to 40 minutes before patients arrival at the trauma centers.
"Providing faster care to patients who are bleeding to death saves lives," Andrew Reisner, M.D., MGH Department of Emergency Medicine and senior author of the paper said in a statement. "While the clinical information that ambulance crews call in to trauma centers was sufficient to determine the presence of a life-threatening hemorrhage in about half the patients we studied, many other patients were in a 'grey area' and may or may not have been at risk of bleeding to death. Our study demonstrated that automated analysis of patients' vital signs during prehospital transport was significantly better at discriminating between patients who did and did not have life-threatening hemorrhage."
Findings from the study were published in the journal, Shock

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