Software symptomcheckR: an R package for analyzing and visualizing symptom checker triage performance

Abstract Background A major stream of research on symptom checkers aims at evaluating the technology’s predictive accuracy , but apart from general trends, the results are marked by high variability. Several authors suggest that this variability might in part be due to different assessment methods and a lack of standardization. To improve the reliability of symptom checker evaluation studies, several approaches have been suggested, including standardizing input procedures, the generation of test vignettes, and the assignment of gold standard solutions for these vignettes. Recently, we suggested a third approach––test-theoretic metrics for standardized performance reporting–– to allow systematic and comprehensive comparisons of symptom checker performance. However, calculating these metrics is time-consuming and error prone, which could hamper the use and effectiveness of these metrics. Results We developed the R package symptomcheckR as an open-source software to assist researchers in calculating standard metrics to evaluate symptom checker performance individually and comparatively and produce publication-ready figures. These metrics include accuracy (by triage level), safety of advice (i.e., rate of correctly or overtriaged cases), comprehensiveness (i.e., how many cases could be entered or were assessed), inclination to overtriage (i.e., how risk-averse a symptom checker is) and a capability comparison score (i.e., a score correcting for case difficulty and comprehensiveness that enables a fair and reliable comparison of different symptom checkers). Each metric can be obtained using a single command and visualized with another command. For the analysis of individual or the comparison of multiple symptom checkers, single commands can be used to produce a comprehensive performance profile that complements the standard focus on accuracy with additional metrics that reveal strengths and weaknesses of symptom checkers. Conclusions Our package supports ongoing efforts to improve the quality of vignette-based symptom checker evaluation studies by means of standardized methods. Specifically, with our package, adhering to reporting standards and metrics becomes easier, simple, and time efficient. Ultimately, this may help users gain a more systematic understanding of the strengths and limitations of symptom checkers for different use cases (e.g., all-purpose symptom checkers for general medicine versus symptom checkers that aim at improving triage in emergency departments), which can improve patient safety and resource allocation.