JMIR Publications

ABSTRACT

Background:

Some hospitalized patients rapidly deteriorate due to either disease progression or imperfect triage and level of care assignment after their admission. An EWS to identify patients at high risk of subsequent intra-hospital death can be an effective tool to benefit patient safety and quality of care, and also reduce avoidable harm and costs.

Objective:

To prospectively validate a real-time early warning system (EWS) with the capacity to predict patients at high risk of in-hospital mortality during their inpatient episodes.

Methods:

Data were collected from the system-wide electronic medical record (EMR) of two acute Berkshire Health System hospitals, comprised of 54,246 inpatient admissions from January 01, 2015 to September 30, 2017, of which 3.97% resulted in intra-hospital deaths. After constructing the model using statistical methods and modern machine learning algorithms, we prospectively validated the algorithms as a real-time inpatient early warning system (EWS) for mortality.

Results:

Our EWS algorithm scored patients’ daily and long-term risk of in-hospital mortality probability after admission and stratified them into distinct risk groups. In the prospective validation, our EWS prospectively attained a c-statistic of 0.884, where 99 encounters were captured in the highest risk group, 68.69% of which died during the episodes. Furthermore, our real-time EWS successfully forecasted the top 13.33% of the expired patients at least 40.8 hours before death. Important clinical utilization features, together with coded diagnoses, vital signs and laboratory test results were recognized as impactful predictors in the final EWS.

Conclusions:

In this study, we prospectively demonstrated our new EWS’s capability of real-time monitoring and alerting clinicians to patients at high risk of in-hospital death, providing opportunities for timely interventions. This real-time EWS is able to assist clinical decision making and enable more actionable and effective individualized care for better patients’ health outcomes in target medical facilities.