Comparison of early warning scores utilising patient trends

Early Warning Scores are support tools intended to help clinicians recognise and intervene with in-hospital patient deterioration early on and thus prevent adverse patient outcomes (e.g. death). State-of-the-art early warning scores in use do not consider trends in the patient’s physiological changes, although their importance is widely known and acknowledged. Here, we compare a state-of-the-art early warning score with an existing, trend-based early warning score and two new trend based early warning scores to assess the performance difference between the trend-based early warning scores themselves and the static one. The newly developed early warning scores were created via logistic regression, as was the already existing trend-based early warning score. All considered trend-based early warning scores outperformed the National Early Warning Score, which served as our reference model, in terms of the area under the receiver operating curve. We were able to add to the evidence of the advantages gained in predictive performance when considering trend-values to early warning scores. Furthermore, our results emphasize that a high predictive performance can be achieved by means of a very small number of model predictors.