Effects of surgeon sociodemographics on patient-reported satisfaction

Patient-reported satisfaction scores, including the Press Ganey surveys, are increasingly used as measures for quality healthcare among surgical subspecialties. However, the influence of surgeon sociodemographics is not clear.

This cross-sectional study analyzed Press Ganey surveys linked to outpatient surgical visits at a single academic institution from January 2015 to December 2018 as they related to surgeon age, gender, and race. The primary outcome variable was achievement of a top-box score (5/5) on likelihood to recommend surgeon queries. Secondary analysis examined the relationship of likelihood to recommend surgeon to other survey questions, such as those regarding surgeon courtesy, concern, understandability, patient inclusion in medical decision making, and patient confidence in surgeon. χ² tests and generalized estimating equation regression models were run to assess correlation.

In bivariate analysis of 36,840 surveys, non-Hispanic white surgeons were more likely to receive likelihood to recommend surgeon top-box ratings than Asian (P < .001) or underrepresented minority surgeons (P < .001). Additionally, male gender (P < .01) and older surgeon age (P < .001) were associated with higher top-box scores. However, in multivariate generalized estimating equation analysis, the effect of age was no longer significant, but female gender continued to be associated with lower odds of top-box likelihood to recommend surgeon ratings (odds ratio 0.83; 95% confidence interval, 0.70%-0.99%), as did Asian compared with white race (odds ratio 0.78; 95% confidence interval, 0.65%-0.95%). Likelihood to recommend surgeon scores correlated most closely with patients' "confidence" in the surgeon rather than measures of courtesy, concern, understandability, or inclusion in medical decision making.

Top-box scores varied by surgeon race and gender in correlation with patients' perceived confidence in the provider. Interpretation of Press Ganey scores should account for potential bias in patient satisfaction surveys based on surgeon demographics.