Multiple performance measures are needed to evaluate triage systems in the emergency department
Objectives: Emergency department triage systems can be considered prediction rules with an ordinal outcome, where different directions of misclassification have different clinical consequences. We evaluated strategies to compare the performance of triage systems and aimed to propose a set of performance measures that should be used in future studies. Study Design and Setting: We identified performance measures based on literature review and expert knowledge. Their properties are illustrated in a case study evaluating two triage modifications in a cohort of 14,485 pediatric emergency department visits. Strengths and weaknesses of the performance measures were systematically appraised. Results: Commonly reported performance measures are measures of statistical association (34/60 studies) and diagnostic accuracy (17/60 studies). The case study illustrates that none of the performance measures fulfills all criteria for triage evaluation. Decision curves are the performance measures with the most attractive features but require dichotomization. In addition, paired diagnostic accuracy measures can be recommended for dichotomized analysis, and the triage-weighted kappa and Nagelkerke's R2 for ordinal analyses. Other performance measures provide limited additional information. Conclusion: When comparing modifications of triage systems, decision curves and diagnostic accuracy measures should be used in a dichotomized analysis, and the triage-weighted kappa and Nagelkerke's R2 in an ordinal approach.
|Keywords||Decision curve, Diagnostic accuracy measures, Kappa, Nagelkerke's R2, Performance measures, Triage|
|Persistent URL||dx.doi.org/10.1016/j.jclinepi.2017.11.004, hdl.handle.net/1765/104552|
|Journal||Journal of Clinical Epidemiology|
Zachariasse, J.M, Nieboer, D, Oostenbrink, R, Moll, H.A. (Henriëtte A.), & Steyerberg, E.W. (2018). Multiple performance measures are needed to evaluate triage systems in the emergency department. Journal of Clinical Epidemiology, 94, 27–34. doi:10.1016/j.jclinepi.2017.11.004