Abstract
Data on minority group physicians from diverse racial/ethnic backgrounds is sparse and not reported by PG metrics at the national level. While PG metrics typically concentrate on the individual, patterns and trends are clearly discernible at the group level and comparison of groups to capture patterns may yield results hitherto unknown. One could even envisage using AI to capture any trends, differences, and comparative figures to build databases for the future. It is time to retool PG surveys to fit the modern U.S. healthcare workforce and be inclusive, and not selective at the individual level.
| Original language | English |
|---|---|
| Pages (from-to) | 85-86 |
| Number of pages | 2 |
| Journal | CNS Spectrums |
| Volume | 29 |
| Issue number | 2 |
| DOIs | |
| State | Published - Apr 22 2024 |
Bibliographical note
Publisher Copyright:© The Author(s), 2023. Published by Cambridge University Press.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- HCAHPS
- Press Ganey surveys
- diversity
- equity
- inclusion
- minority healthcare workers
- patient satisfaction scores
ASJC Scopus subject areas
- Clinical Neurology
- Psychiatry and Mental health
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