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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Oct 4, 2021
Date Accepted: Jun 13, 2022

The final, peer-reviewed published version of this preprint can be found here:

Wisdom of the Experts Versus Opinions of the Crowd in Hospital Quality Ratings: Analysis of Hospital Compare Star Ratings and Google Star Ratings

Ramasubramanian H, Joshi S, Krishnan R

Wisdom of the Experts Versus Opinions of the Crowd in Hospital Quality Ratings: Analysis of Hospital Compare Star Ratings and Google Star Ratings

J Med Internet Res 2022;24(7):e34030

DOI: 10.2196/34030

PMID: 35881418

PMCID: 9364164

Wisdom of the Experts versus Opinions of the Crowd in Hospital Quality Ratings: An Analysis of Hospital Compare Star Ratings and Google Star Ratings

  • Hari Ramasubramanian; 
  • Satish Joshi; 
  • Ranjani Krishnan

ABSTRACT

Background:

Popular online portals provide free and convenient access to user-generated quality reviews. Centers for Medicare and Medicaid Services (CMS) also provide patients with Hospital Compare Star Ratings (HCSR), a single public measure of hospital quality aggregating multiple quality dimensions. Consumers often use crowdsourced hospital ratings on platforms such as Google to select hospitals, but it is unknown if these ratings reflect a comprehensive measure of clinical quality.

Objective:

We analyze if Google online quality ratings, which reflect the wisdom of the crowd, are associated with HCSR, which reflect the wisdom of the experts. CMS revised the methodology of assigning star ratings to hospitals. Therefore, we analyze these associations before and after the 2021 revisions of the CMS rating system.

Methods:

We extracted Google ratings using Application Programming Interface (API) in June 2020. The HCSR data of April 2020 (before the revision of HCSR methodology) and April 2021 (after the revision of HCSR methodology) were obtained from CMS’ Hospital Compare (HC) website. We also extracted scores for the individual components of hospital quality for each of the hospitals in our sample using the code provided by HC. Fractional Response Model (FRM) was used to estimate the association between Google Ratings and HCSR and individual components of quality.

Results:

Results indicate that Google ratings are statistically associated with HCSR (P<.001) after controlling for hospital level effects. A one star improvement in CMS ratings before the change in methodology (after the change in methodology) is expected to increase the Google ratings by 0.145 (0.135) on average (95% CI 0.127- 0.163; P<.001, 95% CI 0.116-0.153; P<.001). The analyses with individual components of hospital quality reveal that Google ratings are not associated with components of HCSR that require medical expertise such as ‘Safety of care’ or ‘Readmissions’. The revised CMS rating system ameliorates previous partial inconsistencies in association between Google ratings and component scores of HCSR.

Conclusions:

Overall, crowd sourced Google hospital ratings are informative about expert CMS hospital quality ratings and several individual quality components that are easier for patients to evaluate. Therefore, hospitals should not expect improvements in quality metrics that require expertise to assess such as safety of care and readmission to result in improved Google star ratings. Hospitals can benefit from using crowd-sourced ratings as timely, easily available, and dynamic indicators of their quality performance.


 Citation

Please cite as:

Ramasubramanian H, Joshi S, Krishnan R

Wisdom of the Experts Versus Opinions of the Crowd in Hospital Quality Ratings: Analysis of Hospital Compare Star Ratings and Google Star Ratings

J Med Internet Res 2022;24(7):e34030

DOI: 10.2196/34030

PMID: 35881418

PMCID: 9364164

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