Predicting a Caller's Fate

What if a 911 operator and/or hospital emergency room staff could better assess whether an injured party is actually about to die? Could this additional critical information be used to determine whether an emergency medical services (EMS) helicopter should be sent or an ambulance?

Japanese researchers have developed a computer program which may be able tell from an emergency call if you are about to die. Research published in the open access journal BMC Emergency Medicine shows that a computer algorithm is able to predict the patient's risk of dying at the time of the emergency call.

Kenji Ohshige and a team of researchers from the Yokohama City University School of Medicine in Japan assessed the new Yokohama computer-based triage emergency system from its inception on 1st October 2008 until 31st March 2009, collecting information from over 60,000 emergency calls.

For each call, triage information was entered into the computer system, which then categorized patients according to the severity of their condition. The researchers then compared the computer-estimated threat of dying at the time of the emergency call with the actual patients' condition upon arrival at the hospital emergency department. They found that the algorithm was effective in assessing the life risk of a patient with over 80% sensitivity.

According to Ohshige, "A patient's life threat risk can be quantitatively expressed at the moment of the emergency call with a moderate level of accuracy. The algorithm for estimating a patient's like threat risk should be improved further as more data are collected."

The researchers said ambulance response time has risen rapidly with the increased demand for this service in developed countries such as Japan. This emphasizes the need to prioritize ambulance (and EMS helicopter) responses according to the severity of the patient's condition.

"As delayed response time reduces the number of patients who survive from sudden cardiac arrest priority dispatch of ambulances to patients in critical condition has become a matter of importance," says Ohshige.

According to an abstract of the paper: "Utilizing a computer algorithm, information from calls to an ambulance service was used to calculate the risk of patients being in a life-threatening condition (life threat risk), at the time of the call. If the estimated life threat risk was higher than 10%, the probability that a patient faced a risk of dying was recognized as very high and categorized as category A+. The present study aimed to review the accuracy of the algorithm."

Data collected for six months from the Yokohama new emergency system was used. In the system, emergency call workers interviewed ambulance callers to obtain information necessary to assess triage, which included consciousness level, breathing status, walking ability, position, and complexion. An emergency patient's life threat risk was then estimated by a computer algorithm applying logistic models.

The study compared the estimated life threat risk occurring at the time of the emergency call to the patients' state or severity of condition, i.e. death confirmed at the scene by ambulance crews, resulted in death at emergency departments, life-threatening condition with occurrence of cardiac and/or pulmonary arrest (CPA), life-threatening condition without CPA, serious but not life-threatening condition, moderate condition, and mild condition. The sensitivity, specificity, predictive values, and likelihood ratios of the algorithm for categorizing A+ were calculated.

The number of emergency dispatches over the six months totaled 73,992. Triage assessment was conducted for 68,692 of these calls. The study accounted for 88.8% of patients who were involved in triage calls. There were 2,349 cases where the patient had died or had suffered CPA. The sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio and negative likelihood ratio of the algorithm at predicting cases that would result in a death or CPA were 80.2% (95% confidence interval: 78.6% - 81.8%), 96.0% (95.8% - 96.1%), 42.6% (41.1% - 44.0%), 99.2% (99.2% - 99.3%), 19.9 (18.8 - 21.1), and 0.21 (0.19 - 0.22), respectively.

The researchers believe "a patient's life threat risk was quantitatively assessed at the moment of the emergency call with a moderate level of accuracy."