Early Prediction of Code Blue using Electronic Medical Records

摘要

Code Blue is an emergency code in a hospital that is used to indicate when a patient goes into cardiac arrest and needs resuscitation. When Code Blue is called, an on-call medical team staffed by physicians and nurses is paged and rushes in to try to save the patient's life. It is an intense, chaotic, and resource-intensive process, and despite the considerable effort, survival rates are still less than 20% [4]. Research indicates that patients actually start showing clinical signs of deterioration some time before going into cardiac arrest[1][2][3], making early prediction, and possibly intervention, feasible. In this paper, we describe our work in partnership with NorthShore University HealthSystem that preemptively flags patients who are likely to go into cardiac arrest, using signals extracted from demographic information, hospitalization history, vitals and laboratory measurements in patient-level electronic medical records. We find that early prediction of Code Blue is possible and when compared with state of the art existing method used by hospitals (MEWS - Modified Early Warning Score) [4], our methods perform significantly better. Based on these results, this system is now being considered for deployment in NorthShore Health Systems and University of Chicago Hospital.