Punished for Success? A Natural Experiment of Displaying Clinical Hospital Quality on Review Platforms

The healthcare market struggles with information asymmetry, limiting patients’ ability to make informed hospital choices. Aiming to bridge this gap, review platforms like Yelp have begun displaying hospitals’ clinical quality data alongside consumer reviews. However, our research uncovers that Yelp’s introduction of maternity care clinical quality measures unexpectedly resulted in lower subsequent Yelp ratings for high-quality hospitals with insufficient staffing. Employing precise foot traffic data and transfer deep learning, we discovered that high-quality, yet understaffed, hospitals experienced a surge in patient volume, which strained their resources and diminished patient satisfaction, leading to negative reviews. This finding has significant implications, signaling the unintended consequences of revealing clinical quality measures, including potential financial losses for hospitals because of reduced federal funding. This research not only contributes to our understanding the dynamics of patient satisfaction but also, offers actionable insights for high-quality hospitals to mitigate the negative impacts of unexpected visibility on review platforms. Our research underscores the importance for patients to discern between objective clinical quality measures and self-reported subjective ratings in their decision-making process. This research applies machine learning and transfer deep learning techniques to healthcare analytics, offering a deeper understanding of the interplay between information disclosure, online reviews, patient satisfaction, and hospital management. The healthcare market faces severe information asymmetry; patients struggle to evaluate the quality of hospitals and make informed decisions about their healthcare. Review platforms (e.g., Yelp) have begun to display the clinical quality of hospitals (alongside consumer reviews) to inform patients about hospital selection. In 2017 and 2019, Yelp introduced a feature with clinical measures of maternity care for hospitals that deliver babies in select markets. We study how clinical quality measures displayed on Yelp—especially for those (clinically) high-quality hospitals—influence subsequent patients’ ratings of hospitals. Our difference-in-differences estimation shows that when clinical quality measures are displayed, high-quality hospitals are surprisingly punished with lower subsequent ratings on Yelp, especially hospitals with low staffing capacity. This novel finding is consequential