Online Reviews as Health Data: Examining the Association Between Availability of Health Care Services and Patient Star Ratings Exemplified by the Yelp Academic Dataset

BACKGROUND: There have been public health interventions that aim to reduce barriers to health care access by extending opening hours of health care facilities. However, the impact of opening hours from the patient’s perspective is not well understood. OBJECTIVE: This study aims to investigate the relationship between temporal accessibility of health care services and how patients rate the providers on Yelp, an online review website that is popular in the United States. Using crowdsourced open Internet data, such as Yelp, can help circumvent the traditional survey method. METHODS: From Yelp’s limited academic dataset, this study examined the pattern of visits to health care providers and performed a secondary analysis to examine the association between patient rating (measured by Yelp’s rating) and temporal accessibility of health care services (measured by opening hours) using ordinal logistic regression models. Other covariates included were whether an appointment was required, the type of health care service, the region of the health care service provider, the number of reviews the health care service provider received in the past, the number of nearby competitors, the mean rating of competitors, and the standard deviation of competitors’ ratings. RESULTS: From the 2085 health care service providers identified, opening hours during certain periods, the type of health care service, and the variability of competitors’ ratings showed an association with patient rating. Most of the visits to health care service providers took place between normal working hours (9 AM-5 PM) from Sunday to Thursday, and the least on Saturday. A model fitted to the entire sample showed that increasing hours during normal working hours on Monday (OR 0.926, 95% CI 0.880-0.973, P=0.03), Saturday (OR 0.897, 95% CI 0.860-0.935, P<0.001), Sunday (OR 0.904, 95% CI 0.841-0.970, P=0.005), and outside normal working hours on Friday (OR 0.872, 95% CI 0.760-0.998, P=0.048) was associated with receiving lower ratings. But increasing hours during outside normal working hours on Sunday was associated with receiving higher ratings (OR 1.400, 95% CI 1.036-1.924, P=0.03). There were also observed differences in patient ratings among the health care services types, but not geographically or by appointment requirement. CONCLUSIONS: This study shows that public health interventions, especially those involving opening hours, could use crowdsourced open Internet data to enhance the evidence base for decision making and evaluation in the future. This study illustrates one example of how Yelp data could be used to understand patient experiences with health care services, making a case for future research for exploring online reviews as a health dataset.