JMIR Publications

ABSTRACT

Background:

Online reviews of physicians have become exceedingly popular among healthcare consumers since the early 2010s. A factor that can potentially influence these reviews is the gender of the physician since the physician's gender has been found to influence patient-physician communication. When studying the direct relationship between the gender of physicians and their online reviews, it is important to account for clinical characteristics, such as the patient risk, associated with a physician to isolate the direct effect of a physician’s gender on their online reviews. It is also important to account for temporal factors that can influence physicians and their online reviews. Our study is among the first to conduct rigorous longitudinal analysis to study the effects of the gender of physicians on their reviews after accounting for several important clinical factors, including patient risk, physician specialty, as well as temporal factors using time fixed-effects. This study is also among the first ones to study the possible gender bias in online reviews using statewide data from Alabama.

Objective:

This study conducts a longitudinal empirical investigation of the relationship between the gender of physicians and their online reviews using data across the state of Alabama after accounting for patient risk and temporal effects.

Methods:

We created a unique dataset by combining data from online physician reviews from a popular physician review website RateMDs and clinical data from the Center for Medicare and Medicaid Services (CMS) for the state of Alabama. We utilized longitudinal econometric specifications to conduct the econometric analysis and controlled for several important clinical and review characteristics, including patient risk, physician specialty and latent topics embedded in the textual comments of the online reviews. We utilized the four rating dimensions (helpfulness, knowledge, staff, and punctuality) and overall rating from RateMDs as the dependent variables and gender of the physicians as the key explanatory variable in our panel regression models.

Results:

The panel used to conduct most of the analysis had approximately 1093 physicians. After controlling for clinical factors such as Medicare patient risk, number of Medicare beneficiaries, number of services provided, and physician specialty, review factors such as latent topics embedded in the review comments, and number of words in the comments and year fixed effects, the physician random-effects specifications showed that male physicians receive better online ratings than female physicians. The coefficients and the corresponding standard errors, P values of the binary variable GenderFemale (1 for female physicians and 0 otherwise) with different rating variables as outcomes are as follows: OverallRating (Coefficient: -0.194, Std. Error: 0.060, P=.001), HelpfulnessRating (Coefficient: -0.221, Std. Error: 0.069, P=.001), KnowledgeRating (Coefficient: -0.230, Std. Error: 0.065, P<.001), StaffRating (Coefficient: -0.123, Std. Error: 0.062, P=.049) and PunctualityRating (Coefficient: -0.200, Std.Error: 0.067, P=.003).

Conclusions:

This study finds that female physicians do indeed receive lower online ratings than male physicians, and this finding is consistent even after accounting for several clinical characteristics associated with the physicians and temporal effects. Even though the magnitude of the coefficients of GenderFemale is relatively small, they are statistically significant. The findings of this study provide support to the findings on gender bias in the existing healthcare literature. We contribute to the existing literature by conducting a study using data across the state of Alabama and utilizing a longitudinal econometric analysis along with incorporating important clinical and review controls associated with the physicians.