scholarly journals Conflicting measures of hospital quality: Ratings from “Hospital Compare” versus “Best Hospitals”

2007 ◽  
Vol 2 (3) ◽  
pp. 128-134 ◽  
Author(s):  
Lakshmi K. Halasyamani ◽  
Matthew M. Davis
Keyword(s):  
Hospital Quality ◽  
Quality Ratings ◽  
Hospital Compare

scholarly journals Neighborhood Disadvantage and Hospital Quality Ratings in the Medicare Hospital Compare Program

Medical Care ◽  
2020 ◽  
Vol 58 (4) ◽  
pp. 376-383 ◽  
Author(s):  
John Fahrenbach ◽  
Marshall H. Chin ◽  
Elbert S. Huang ◽  
Mary K. Springman ◽  
Stephen G. Weber ◽  
...  
Keyword(s):  
Neighborhood Disadvantage ◽  
Hospital Quality ◽  
Quality Ratings ◽  
Hospital Compare

Wisdom of the Experts versus Wisdom of the Crowd in Hospital Quality Ratings: Cross-Sectional Analyses of Google Ratings (Preprint)

2021 ◽  
Author(s):  
Hari Ramasubramanian ◽  
Satish Joshi ◽  
Ranjani Krishnan
Keyword(s):  
Application Programming Interface ◽  
Hospital Quality ◽  
Rating System ◽  
Cross Sectional ◽  
Quality Performance ◽  
Quality Ratings ◽  
Before And After ◽  
Fractional Response ◽  
The Individual ◽  
Hospital Compare

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.

scholarly journals Relationship of Hospital Star Ratings to Race, Education, and Community Income

2020 ◽  
Vol 15 (10) ◽  
pp. 588-593
Author(s):  
Bo Shi ◽  
Christopher King ◽  
Sean Shenghsiu Huang
Keyword(s):  
Educational Attainment ◽  
Multinomial Logistic Regression ◽  
Hospital Quality ◽  
Minority Population ◽  
Lower Income ◽  
Community Characteristics ◽  
Cross Sectional ◽  
Quality Ratings ◽  
Relationship Of ◽  
Racial Ethnic

INTRODUCTION: The Centers for Medicare & Medicaid Services (CMS) publishes hospital quality ratings to provide more transparent and useable quality information to patients and stakeholders. However, there is a gap in the literature regarding the geographic distribution of the hospitals with higher star ratings. In this paper, we focus on the associations between star ratings and community characteristics, including racial/ethnic mix, household income, educational attainment, and regional difference. METHODS: A retrospective study and cross-sectional logistic and multinomial logistic regression analyses. RESULTS: According to the multivariate regression results, hospitals in areas with lower income, lower educational attainment, and higher minority population shares have lower quality ratings (lower income: odds ratio [OR] 0.67; 95% CI, 0.49-0.91; lower education: OR 0.66; 95% CI, 0.51-0.85; higher minority: OR 0.52; 95% CI, 0.40-0.69). Compared with hospitals in the Midwest, hospitals in Northeast, South, and West regions have lower quality ratings (Northeast: OR 0.37; 95% CI, 0.25-0.56; South: OR 0.68; 95% CI, 0.51-0.91; West: OR 0.69; 95% CI, 0.49-0.97). DISCUSSION AND CONCLUSION: Overall, our results show that hospitals with higher star ratings are less likely to be located in communities with higher minority populations, lower income, and lower levels of educational attainment. Findings contribute to the discussion of integrating social factors in hospital quality star rating calculation methodologies.

scholarly journals Performance of Multihospital Health Systems’ Flagship Hospitals in the CMS Star Rating Program

2020 ◽  
Vol 15 (7) ◽  
pp. 407-410
Author(s):  
Jianhui Hu ◽  
David R Nerenz
Keyword(s):  
United States ◽  
Acute Care ◽  
Health Systems ◽  
The United States ◽  
Hospital Quality ◽  
Uncompensated Care ◽  
Star Rating ◽  
The Difference ◽  
Hospital Compare ◽  
Teaching Intensity

Using the Hospital Compare overall hospital quality star ratings and other publicly available data on acute care hospitals, we examined star ratings for the flagship hospitals of a set of multihospital health systems in the United States. We compared star ratings and hospital characteristics of flagship and nonflagship hospitals across and within 113 health systems. The system flagship hospitals had significantly lower star ratings than did nonflagship hospitals, and they did not generally have the highest star ratings in their own systems. Higher teaching intensity, larger bed size, higher uncompensated care, and higher disproportionate share hospital (DSH) patient percentage were all significantly associated with lower star ratings of flagship hospitals when compared with nonflagship hospitals across all health systems; the flagship hospital of a system was more likely to have the lowest star rating in its system if the difference in DSH percentage was relatively large between the flagship and nonflagship hospitals in that system.

scholarly journals The association of hospital quality ratings with adverse events

2014 ◽  
Vol 26 (2) ◽  
pp. 129-135 ◽  
Author(s):  
J. S. Weissman ◽  
L. Lopez ◽  
E. C. Schneider ◽  
A. M. Epstein ◽  
S. Lipsitz ◽  
...  
Keyword(s):  
Adverse Events ◽  
Hospital Quality ◽  
Quality Ratings

Estimating a Composite Measure of Hospital Quality From the Hospital Compare Database

Medical Care ◽  
2008 ◽  
Vol 46 (8) ◽  
pp. 778-785 ◽  
Author(s):  
Michael Shwartz ◽  
Justin Ren ◽  
Erol A. Peköz ◽  
Xin Wang ◽  
Alan B. Cohen ◽  
...  
Keyword(s):  
Hospital Quality ◽  
Composite Measure ◽  
Hospital Compare
Sign in / Sign up

Export Citation Format

Share Document