The diagnostic and triage accuracy of digital and online symptom checker tools: a systematic review

Abstract

Digital and online symptom checkers are an increasingly adopted class of health technologies that enable patients to input their symptoms and biodata to produce a set of likely diagnoses and associated triage advice. However, concerns regarding the accuracy and safety of these symptom checkers have been raised. This systematic review evaluates the accuracy of symptom checkers in providing diagnoses and appropriate triage advice. MEDLINE and Web of Science were searched for studies that used either real or simulated patients to evaluate online or digital symptom checkers. The primary outcomes were the diagnostic and triage accuracy of the symptom checkers. The QUADAS-2 tool was used to assess study quality. Of the 177 studies retrieved, 10 studies met the inclusion criteria. Researchers evaluated the accuracy of symptom checkers using a variety of medical conditions, including ophthalmological conditions, inflammatory arthritides and HIV. A total of 50% of the studies recruited real patients, while the remainder used simulated cases. The diagnostic accuracy of the primary diagnosis was low across included studies (range: 19-37.9%) and varied between individual symptom checkers, despite consistent symptom data input. Triage accuracy (range: 48.8-90.1%) was typically higher than diagnostic accuracy. Overall, the diagnostic and triage accuracy of symptom checkers are variable and of low accuracy. Given the increasing push towards adopting this class of technologies across numerous health systems, this study demonstrates that reliance upon symptom checkers could pose significant patient safety hazards. Large-scale primary studies, based upon real-world data, are warranted to demonstrate the adequate performance of these technologies in a manner that is non-inferior to current best practices. Moreover, an urgent assessment of how these systems are regulated and implemented is required.

Fig. 1

Preferred reporting items for Systematic Reviews and Meta-Analysis (PRISMA) flow diagram showing the process of study selection for this systematic review of symptom checker diagnostic and triage accuracy.

Fig. 2. Risk of bias summary using QUADAS-2 risk assessment tool.

Authors’ judgement regarding each domain of bias of each study synthesised on the accuracy of symptom checkers. Risk was categorised into one of three categories: low risk (+), unclear risk (?) and high risk (−). The table shows possible items to consider in future work involving symptom checkers to achieve a low risk of bias or applicability concerns.

Fig. 3. Mean primary diagnostic accuracy of symptom checkers in each study.

Error bars signify the range of accuracy of different symptom checkers for the same patient/vignette population. An overall accuracy value was not given in Berry (2019).

Fig. 4. Mean accuracy of triage information given by symptom checkers in each study.

Error bars signify the range of accuracy of different symptom checkers for the same patient/vignette population.