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Online physician ratings fail to predict actual performance on measures of quality, value, and peer review

6-10-2021, 13:46

Objective: Patients use online consumer ratings to identify high-performing physicians, but it is unclear if ratings are valid measures of clinical performance. We sought to determine whether online ratings of specialist physicians from 5 platforms predict quality of care, value of care, and peer-assessed physician performance.
Materials and Methods: We conducted an observational study of 78 physicians representing 8 medical and sur-
gical specialties. We assessed the association of consumer ratings with specialty-specific performance scores (metrics including adherence to Choosing Wisely measures, 30-day readmissions, length of stay, and adjusted cost of care), primary care physician peer-review scores, and administrator peer-review scores.
Results: Across ratings platforms, multivariable models showed no significant association between mean con-
sumer ratings and specialty-specific performance scores (b-coefficient range, 0.04, 0.04), primary care physician scores (b-coefficient range, 0.01, 0.3), and administrator scores (b-coefficient range, 0.2, 0.1). There was no association between ratings and score subdomains addressing quality or value-based care. Among physicians in the lowest quartile of specialty-specific performance scores, only 5%–32% had consumer ratings in the lowest quartile across platforms. Ratings were consistent across platforms; a physician’s score on one platform significantly predicted his/her score on another in 5 of 10 comparisons.
Discussion: Online ratings of specialist physicians do not predict objective measures of quality of care or peer assessment of clinical performance. Scores are consistent across platforms, suggesting that they jointly measure a latent construct that is unrelated to performance.
Conclusion: Online consumer ratings should not be used in isolation to select physicians, given their poor association with clinical performance.

Journal of the American Medical Informatics Association, 25(4), 2018, 401–407

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