Literature DB >> 29025145

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

Timothy J Daskivich1,2, Justin Houman1, Garth Fuller2,3, Jeanne T Black4, Hyung L Kim1, Brennan Spiegel2,3,5.   

Abstract

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 surgical 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 consumer ratings and specialty-specific performance scores (β-coefficient range, -0.04, 0.04), primary care physician scores (β-coefficient range, -0.01, 0.3), and administrator scores (β-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.

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Mesh:

Year:  2018        PMID: 29025145     DOI: 10.1093/jamia/ocx083

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  12 in total

1.  AN OUTCOMES-BASED APPROACH ACROSS THE MEDICAL EDUCATION CONTINUUM.

Authors:  Mark E Rosenberg
Journal:  Trans Am Clin Climatol Assoc       Date:  2018

2.  Patient satisfaction survey scores are not an appropriate metric to differentiate performance among anesthesiologists.

Authors:  Robert E Freundlich; Gen Li; Brendan Grant; Paul St Jacques; Warren S Sandberg; Jesse M Ehrenfeld; Matthew S Shotwell; Jonathan P Wanderer
Journal:  J Clin Anesth       Date:  2020-05-07       Impact factor: 9.452

3.  A Comparison of Online Physician Ratings and Internal Patient-Submitted Ratings from a Large Healthcare System.

Authors:  Kanu Okike; Natalie R Uhr; Sherry Y M Shin; Kristal C Xie; Chong Y Kim; Tadashi T Funahashi; Michael H Kanter
Journal:  J Gen Intern Med       Date:  2019-09-17       Impact factor: 5.128

4.  How Referring Providers Choose Specialists for Their Patients: a Systematic Review.

Authors:  Caitlin B Finn; Jason K Tong; Hannah E Alexander; Chris Wirtalla; Heather Wachtel; Carmen E Guerra; Shivan J Mehta; Richard Wender; Rachel R Kelz
Journal:  J Gen Intern Med       Date:  2022-04-19       Impact factor: 6.473

5.  What Do Patients Care About? Mining Fine-grained Patient Concerns from Online Physician Reviews Through Computer-Assisted Multi-level Qualitative Analysis.

Authors:  Lu He; Changyang He; Yue Wang; Zhaoxian Hu; Kai Zheng; Yunan Chen
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

6.  Scope, Breadth, and Differences in Online Physician Ratings Related to Geography, Specialty, and Year: Observational Retrospective Study.

Authors:  Jessica Janine Liu; John Justin Matelski; Chaim M Bell
Journal:  J Med Internet Res       Date:  2018-03-07       Impact factor: 5.428

Review 7.  Developing Embedded Taxonomy and Mining Patients' Interests From Web-Based Physician Reviews: Mixed-Methods Approach.

Authors:  Jia Li; Minghui Liu; Xiaojun Li; Xuan Liu; Jingfang Liu
Journal:  J Med Internet Res       Date:  2018-08-16       Impact factor: 5.428

8.  What Do Patients Say About Doctors Online? A Systematic Review of Studies on Patient Online Reviews.

Authors:  Y Alicia Hong; Chen Liang; Tiffany A Radcliff; Lisa T Wigfall; Richard L Street
Journal:  J Med Internet Res       Date:  2019-04-08       Impact factor: 5.428

9.  Association of Social Media Presence with Online Physician Ratings and Surgical Volume Among California Urologists: Observational Study.

Authors:  Justin Houman; James Weinberger; Ashley Caron; Alex Hannemann; Michael Zaliznyak; Devin Patel; Ariel Moradzadeh; Timothy J Daskivich
Journal:  J Med Internet Res       Date:  2019-08-13       Impact factor: 5.428

10.  Differences in Online Consumer Ratings of Health Care Providers Across Medical, Surgical, and Allied Health Specialties: Observational Study of 212,933 Providers.

Authors:  Timothy Daskivich; Michael Luu; Benjamin Noah; Garth Fuller; Jennifer Anger; Brennan Spiegel
Journal:  J Med Internet Res       Date:  2018-05-09       Impact factor: 5.428

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