The accuracy of Internet search engines to predict diagnoses from symptoms can be assessed with a validated scoring system

Purpose: To validate a scoring system that evaluates the ability of Internet search engines to correctly predict diagnoses when symptoms are used as search terms. Methods: We developed a five point scoring system to evaluate the diagnostic accuracy of Internet search engines. We identified twenty diagnoses common to a primary care setting to validate the scoring system. One investigator entered the symptoms for each diagnosis into three Internet search engines (Google, Bing, and Ask) and saved the first five webpages from each search. Other investigators reviewed the webpages and assigned a diagnostic accuracy score. They rescored a random sample of webpages two weeks later. To validate the five point scoring system, we calculated convergent validity and test-retest reliability using Kendall's W and Spearman's rho, respectively. We used the Kruskal-Wallis test to look for differences in accuracy scores for the three Internet search engines. Results: A total of 600 webpages were reviewed. Kendall's W for the raters was 0.71 (p < 0.0001). Spearman's rho for test-retest reliability was 0.72 (p < 0.0001). There was no difference in scores based on Internet search engine. We found a significant difference in scores based on the webpage's order on the Internet search engine webpage (p = 0.007). Pairwise comparisons revealed higher scores in the first webpages vs. the fourth (corr p = 0.009) and fifth (corr p = 0.017). However, this significance was lost when creating composite scores. Conclusions: The five point scoring system to assess diagnostic accuracy of Internet search engines is a valid and reliable instrument. The scoring system may be used in future Internet research. (C) 2013 Elsevier Ireland Ltd. All rights reserved.