Data-driven approach to Early Warning Score-based alert management

Abstract

Background: Increasing adoption of electronic health records (EHRs) with integrated alerting systems is a key initiative for improving patient safety. Considering the variety of dynamically changing clinical information, it remains a challenge to design EHR-driven alerting systems that notify the right providers for the right patient at the right time while managing alert burden. The objective of this study is to proactively develop and evaluate a systematic alert-generating approach as part of the implementation of an Early Warning Score (EWS) at the study hospitals.

Methods: We quantified the impact of an EWS-based clinical alert system on quantity and frequency of alerts using three different alert algorithms consisting of a set of criteria for triggering and muting alerts when certain criteria are satisfied. We used retrospectively collected EHRs data from December 2015 to July 2016 in three units at the study hospitals including general medical, acute care for the elderly and patients with heart failure.

Results: We compared the alert-generating algorithms by opportunity of early recognition of clinical deterioration while proactively estimating alert burden at a unit and patient level. Results highlighted the dependency of the number and frequency of alerts generated on the care location severity and patient characteristics.

Conclusion: EWS-based alert algorithms have the potential to facilitate appropriate alert management prior to integration into clinical practice. By comparing different algorithms with regard to the alert frequency and potential early detection of physiological deterioration as key patient safety opportunities, findings from this study highlight the need for alert systems tailored to patient and care location needs, and inform alternative EWS-based alert deployment strategies to enhance patient safety.

Keywords: adverse events, epidemiology and detection; patient safety; trigger tools.

Figure 1

Three frameworks and associated alerts for a patient hospitalised in stepdown unit 1. Blue line represents the Christiana Early Warning Score (CEWS) observations from admission until 1 hour before the rapid response team activation. Vertical lines represent alerts where black represents critical, red represents high risk, yellow represent medium risk and green represent low risk alerts. Using framework 3 (liberal) would result all black, red, yellow and green alerts to be triggered. Using framework 2 (intermediate), only black, red and yellow alerts would have been triggered. Using framework 1 (conservative), only red and black alerts would have been triggered.