The Impact of Patient–Physician Racial and Gender Concordance on Patient Satisfaction with Outpatient Clinic Visits

Patient and provider race and gender concordance (patient and physician identify as the same race/ethnicity or gender) may impact patient experience and satisfaction.

Objective

We sought to examine how patient and physician racial and gender concordance effect patient satisfaction with outpatient clinical encounters. Furthermore, we examined factors that changed satisfaction among concordant and discordant dyads.

Design

Consumer Assessment of Healthcare Provider and Systems (CAHPS) Patient Satisfaction Survey Scores were collected from outpatient clinical encounters between January 2017 and January 2019 at the University of California, San Francisco.

Participants

Patients who were seen in the eligible time period, who voluntarily provided physician satisfaction scores. Providers with fewer than 30 reviews and encounters with missing data were excluded.

Main Measures

Primary outcome was rate of top satisfaction score. The provider score (1–10 scale) was dichotomized as “top score (9-10)” and “low scores (<9).”

Key Results

A total of 77,543 evaluations met inclusion criteria. Most patients identified as White (73.5%) and female (55.4%) with a median age of 60 (IQR 45, 70). Compared to White patients, Asian patients were less likely to give a top score even when controlling for racial concordance (OR: 0.67; CI 0.63–0.714). Telehealth was associated with increased odds of a top score relative to in-person visits (OR 1.25; CI 1.07–1.48). The odds of a top score decreased by 11% in racially discordant dyads.

Conclusions

Racial concordance, particularly among older, White, male patients, is a nonmodifiable predictor of patient satisfaction. Physicians of color are at a disadvantage, as they receive lower patient satisfaction scores, even in race concordant pairs, with Asian physicians seeing Asian patients receiving the lowest scores. Patient satisfaction data is likely an inappropriate means of determining physician incentives as such may perpetuate racial and gender disadvantages.

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Data Availability

Data will not be made available.

Code Availability

Code can be made available without associated data.

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Acknowledgements

We gratefully acknowledge the assistance of Nizar Hakam, Behnam Nabavizadeh, Natalie Rios, and Michael Sadighian particularly for their roles in reviewing provider profiles. All represent the UCSF Department of Urology and were otherwise uncompensated for their work.

Author information

  1. Diane Sliwka and Benjamin N. Breyer contributed equally to this work.

Authors and Affiliations

  1. Department of Urology, University of California San Francisco, San Francisco, CA, USA Nathan M. Shaw, Jordan Holler & Benjamin N. Breyer
  2. Department of Urology, MedStar Georgetown University Hospital, Washington, DC, USA Nathan M. Shaw
  3. Department of Epidemiology and Biostatistics, University of California San Francisco, 1001 Potrero Suite 3A, San Francisco, CA, 94110, USA Nancy Hills & Benjamin N. Breyer
  4. Department of Neurology, University of California San Francisco, San Francisco, CA, USA Nancy Hills
  5. Harvard T.H. Chan School of Public Health, Boston, MA, USA Jordan Holler
  6. Department of Medicine, University of California San Francisco, San Francisco, CA, USA Alicia Fernandez, Denise Davis, Nynikka R. Palmer & Diane Sliwka
  7. Division on General Internal Medicine at Zuckerberg San Francisco General Hospital, University of California San Francisco, San Francisco, CA, USA Alicia Fernandez & Nynikka R. Palmer
  1. Nathan M. Shaw