Ascertaining provider-level implicit bias in electronic health records with rules-based natural language processing: A pilot study in the case of prostate cancer
In this pilot study, providers' practice patterns were associated with both patient race and implicit racial preferences in prostate cancer. Alerting providers of existing implicit bias may restore parity, however future assessments are needed to validate this concept.
Authors
- Charlotta Lindvall (ORCID: https://orcid.org/0000-0003-2090-2039)
- Christopher E. Barbieri (ORCID: https://orcid.org/0000-0002-0381-1947)
- Joe Pelt (ORCID: https://orcid.org/0000-0002-9980-5794)
- Douglas S. Scherr (ORCID: https://orcid.org/0000-0001-5868-5493)
- Neal Patel
- Lina Posada Calderon
- Ashwin Ramaswamy (ORCID: https://orcid.org/0000-0002-8816-7838)
- I Scherr
- Gerald Wang (ORCID: https://orcid.org/0000-0002-0631-011X)
- Parsa Iranmahboub
- Jim C. Hu (ORCID: https://orcid.org/0000-0003-3406-5542)
- Michael Hung (ORCID: https://orcid.org/0000-0002-4456-9536)
- David Green (ORCID: https://orcid.org/0009-0004-9572-9853)
- Timothy McClure
Institutions
- NewYork–Presbyterian Hospital (US)
- Harvard University (US)
- Cornell University (US)
- New York Hospital Queens (US)
- Presbyterian Hospital (US)
- Dana-Farber Cancer Institute (US)
Publication Details
- Journal
- PLoS ONE
- Published
- 2024-12-30
- DOI
- https://doi.org/10.1371/journal.pone.0314989
- Citations
- 1
- Primary Topic
- Migration, Health and Trauma
- Type
- article
- Field-Weighted Citation Impact
- 0.64