[From symptom to diagnosis-symptom checkers re-evaluated : Are symptom checkers finally sufficient and accurate to use? An update from the ENT perspective]

HNO. 2019 May;67(5):334-342. doi: 10.1007/s00106-019-0666-y.
[Article in German]


Background: Every seventh diagnosis is a misdiagnosis. Each year, 1.5 million lives could be saved worldwide with the correct diagnosis. Physicians have to consider over 20,000 diseases. A study from Harvard University published in 2015 tested 19 symptom checkers and found them to be insufficient, with only 29-71% accuracy in diagnosis.

Objective: The current study investigates the diagnostic accuracy of new symptom checkers from an ENT perspective.

Materials and methods: The authors update the abovenamed diagnostic accuracy comparison by (1) including the five new symptom checkers Symptoma, Ada, FindZebra, Mediktor, and Babylon; and (2) normalizing results of the previously tested symptom checkers as to reflect each diagnostic accuracy based on the same set of patient vignettes. The winner is then compared to the two symptom checkers with the most scientific evidence, namely Isabel and FindZebra, on the basis of an ENT-specific test with patient vignettes sourced from the British Medical Journal.

Results: Most of the new symptom checkers demonstrated diagnostic accuracy rates within the previously established range, with the exception of Symptoma, which scored the right diagnosis in 82.2% of cases at the top of the list (+38% points), and in 100% of cases in the top 3 (+29% points) and the top 10 (+16% points), thus raising the bar in this field. The cross-validation with ENT cases resulted in a diagnostic accuracy of 64.3 vs. 21.4 vs. 26.2% (top 1), 92.9 vs. 40.5 vs. 42.9% (top 3), and 100 vs. 61.9 vs. 54.8% (top 10) for Symptoma vs. Isabel vs. FindZebra, respectively.

Conclusions: Symptoma is the first and only viable solution in this market. Large-scale studies should be conducted to further validate these results as well as to assess the actual practical performance of the symptom checkers and their ability to diagnose rare diseases.

Keywords: Diagnosis, computer-assisted; Diagnostic errors; Information seeking behavior; Quality of health care; Self care.

Publication types

  • Review

MeSH terms

  • Checklist / standards*
  • Diagnostic Errors*
  • Humans
  • Rare Diseases* / diagnosis