Accuracy of a Popular Online Symptom Checker for Ophthalmic Diagnoses Journal Articles uri icon

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  • IMPORTANCE: Because more patients are presenting with self-guided research of symptoms, it is important to assess the capabilities and limitations of these available health information tools. OBJECTIVE: To determine the accuracy of the most popular online symptom checker for ophthalmic diagnoses. DESIGN, SETTING, AND PARTICIPANTS: In a cross-sectional study, 42 validated clinical vignettes of ophthalmic symptoms were generated and distilled to their core presenting symptoms. Cases were entered into WebMD symptom checker by both medically trained and nonmedically trained personnel blinded to the diagnosis. Output from the symptom checker, including the number of symptoms, ranking and list of diagnoses, and triage urgency were recorded. The study was conducted on October 13, 2017. Analysis was performed between October 15, 2017, and April 30, 2018. MAIN OUTCOMES AND MEASURES: Accuracy of the top 3 diagnoses generated by the online symptom checker. RESULTS: The mean (SD) number of symptoms entered was 3.6 (1.6) (range, 1-8). The median (SD) number of diagnoses generated by the symptom checker was 26.8 (21.8) (range, 1-99). The primary diagnosis by the symptom checker was correct in 11 of 42 (26%; 95% CI, 12%-40%) cases. The correct diagnosis was included in the online symptom checker's top 3 diagnoses in 16 of 42 (38%; 95% CI, 25%-56%) cases. The correct diagnosis was not included in the symptom checker's list in 18 of 42 (43%; 95% CI, 32%-63%) cases. Triage urgency based on the top diagnosis was appropriate in 7 of 18 (39%; 95% CI, 14%-64%) emergent cases and 21 of 24 (88%; 95% CI, 73%-100%) nonemergent cases. Interuser variability for the correct diagnosis being in the top 3 listed was at least moderate (Cohen Îș = 0.74; 95% CI, 0.54-0.95). CONCLUSIONS AND RELEVANCE: The most popular online symptom checker may arrive at the correct clinical diagnosis for ophthalmic conditions, but a substantial proportion of diagnoses may not be captured. These findings suggest that further research to reflect the real-life application of internet diagnostic resources is required.


  • Shen, Carl
  • Nguyen, Michael
  • Gregor, Alexander
  • Isaza, Gloria
  • Beattie, Anne

publication date

  • June 1, 2019