Abstract

An increasing number of hospitals and health systems utilize social media to allow users to provide feedback and ratings. The correlation between ratings on social media and more conventional hospital quality metrics remains largely unclear, raising concern that healthcare consumers may make decisions on inaccurate or inappropriate information regarding quality. The purpose of this study was to examine the extent to which hospitals utilize social media and whether user-generated metrics on Facebook(®) correlate with a Hospital Compare(®) metric, specifically 30-day all cause unplanned hospital readmission rates. This was a retrospective cross-sectional study conducted among all U.S. hospitals performing outside the confidence interval for the national average on 30-day hospital readmission rates as reported on Hospital Compare. Participants were 315 hospitals performing better than U.S. national rate on 30-day readmissions and 364 hospitals performing worse than the U.S. national rate. The study analyzed ratings of hospitals on Facebook's five-star rating scale, 30-day readmission rates, and hospital characteristics including beds, teaching status, urban vs. rural location, and ownership type. Hospitals performing better than the national average on 30-day readmissions were more likely to use Facebook than lower-performing hospitals (93.3 % vs. 83.5 %; p < 0.01). The average rating for hospitals with low readmission rates (4.15 ± 0.31) was higher than that for hospitals with higher readmission rates (4.05 ± 0.41, p < 0.01). Major teaching hospitals were 14.3 times more likely to be in the high readmission rate group. A one-star increase in Facebook rating was associated with increased odds of the hospital belonging to the low readmission rate group by a factor of 5.0 (CI: 2.6-10.3, p < 0.01), when controlling for hospital characteristics and Facebook-related variables. Hospitals with lower rates of 30-day hospital-wide unplanned readmissions have higher ratings on Facebook than hospitals with higher readmission rates. These findings add strength to the concept that aggregate measures of patient satisfaction on social media correlate with more traditionally accepted measures of hospital quality.

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