ArticleJournal of the American College of Emergency Physicians open2023
A cross-sectional analysis of Yelp and Google reviews of hospitals in the United States.
Article in Journal of the American College of Emergency Physicians open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Public Perception of Health Care Before, During, and After COVID-19: Longitudinal Analysis of Online Reviews.Journal of medical Internet research · 2026Observational
- Google star ratings of Canadian hospitals: a nationwide cross-sectional analysis.BMJ open quality · 2024Article
- A cross-sectional analysis of Yelp and Google reviews of hospitals in the United States.Journal of the American College of Emergency Physicians open · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Patient satisfaction is now an important metric in emergency medicine, but the means by which satisfaction is assessed is evolving. We sought to examine hospital ratings on Google and Yelp as compared to those on Medicare's Care Compare (CC) and to determine if certain hospital characteristics are associated with crowdsourced ratings. Methods: We performed a cross-sectional analysis of hospital ratings on Google and Yelp as compared to those on CC using data collected between July 8 and August 2, 2021. For each hospital, we recorded the CC ratings, Yelp ratings, Google ratings, and each hospital's characteristics. Using multivariable linear regression, we assessed for associations between hospital characteristics and crowdsourced ratings. We calculated Spearman's correlation coefficients for CC ratings versus crowdsourced ratings. Results: Among 3000 analyzed hospitals, the median hospital ratings on Yelp and Google were 2.5 stars (interquartile ratio [IQR], 2-3) and 3 stars (IQR, 2.7-3.5), respectively. The median number of Yelp and Google reviews per hospital was 13 and 150, respectively. The correlation coefficients for Yelp and Google ratings with CC's overall star ratings were 0.19 and 0.20, respectively. For Yelp and Google ratings with CC's patient survey ratings, correlation coefficients were 0.26 and 0.22, respectively. On multivariable analysis, critical access hospitals had 0.22 (95% confidence interval [CI], 0.14-0.30) more Google stars and hospitals in the West had 0.12 (95% CI, 0.05-0.18) more Google stars than references standard hospitals. Conclusion: Patients use Google more frequently than Yelp to review hospitals. Median UnS hospital ratings on Yelp and Google are 2.5 and 3 stars, respectively. Crowdsourced reviews weakly correlate with CC ratings. Critical access hospitals and hospitals in the West have higher crowdsourced ratings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.