Evidence map›Paper›PMID 35394435›Full record

ArticleJournal of medical Internet research2022

Physician Gender, Patient Risk, and Web-Based Reviews: Longitudinal Study of the Relationship Between Physicians' Gender and Their Web-Based Reviews.

Danish Hasnain Saifee, Matthew Hudnall, Uzma Raja

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Danish Hasnain SaifeeDepartment of Information Systems, Statistics, and Management Science, The University of Alabama, Tuscaloosa, AL, United States.ORCID 0000-0002-2058-4117
Matthew Hudnall *Department of Information Systems, Statistics, and Management Science, The University of Alabama, Tuscaloosa, AL, United States.ORCID 0000-0003-3063-2458
Uzma RajaDepartment of Systems and Technology, Auburn University, Auburn, AL, United States.ORCID 0000-0001-5791-8566

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWeb-based reviews of physicians have become exceedingly popular among health care consumers since the early 2010s. A factor that can potentially influence these reviews is the gender of the physician, because the physician's gender has been found to influence patient-physician communication. Our study is among the first to conduct a 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, and temporal factors, using time fixed effects. In addition, this study is among the first to study the possible gender bias in web-based reviews using statewide data from Alabama, a predominantly rural state with high Medicaid and Medicare use.

objectiveThis study conducts a longitudinal empirical investigation of the relationship between physician gender and their web-based reviews using data across the state of Alabama, after accounting for patient risk and temporal effects.

methodsWe created a unique data set by combining data from web-based physician reviews from the popular physician review website, RateMDs, and clinical data from the Center for Medicare and Medicaid Services for the state of Alabama. We used longitudinal econometric specifications to conduct an econometric analysis, while controlling for several important clinical and review characteristics across four rating dimensions (helpfulness, knowledge, staff, and punctuality). The overall rating and these four rating dimensions from RateMDs were used as the dependent variables, and physician gender was the key explanatory variable in our panel regression models.

resultsThe panel used to conduct the main econometric analysis included 1093 physicians. After controlling for several clinical and review factors, the physician random effects specifications showed that male physicians receive better web-based ratings than female physicians. Coefficients and corresponding SEs and P values of the binary variable GenderFemale (1 for female physicians and 0 otherwise) with different rating variables as outcomes were as follows: OverallRating (coefficient -0.194, SE 0.060; P=.001), HelpfulnessRating (coefficient -0.221, SE 0.069; P=.001), KnowledgeRating (coefficient -0.230, SE 0.065; P<.001), StaffRating (coefficient -0.123, SE 0.062; P=.049), and PunctualityRating (coefficient -0.200, SE 0.067; P=.003). The negative coefficients indicate a bias toward male physicians versus female physicians for aforementioned rating variables.

conclusionsThis study found that female physicians receive lower web-based ratings than male physicians even after accounting for several clinical characteristics associated with the physicians and temporal effects. Although the magnitude of the coefficients of GenderFemale was relatively small, they were statistically significant. This study provides support to the findings on gender bias in the existing health care literature. We contribute to the existing literature by conducting a study using data across the state of Alabama and using a longitudinal econometric analysis, along with incorporating important clinical and review controls associated with the physicians.

Indexed as

PhysiciansSexismAgedFemaleHumansInternetLongitudinal StudiesMaleMedicareUnited StatesAlabamagendergender biaspatient perceptionpatient riskweb-based physician reviews

Identifiers

PMID35394435
PMCPMC9034420

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.