Biases in Race and Ethnicity Introduced by Filtering Electronic Health Records for “Complete Data”: Observational Clinical Data Analysis
Our findings underscore the importance of using only necessary filters, as they might disproportionally affect data availability of minoritized racial and ethnic populations. Researchers must consider these unintentional biases when performing data-driven research and explore techniques to minimize the impact of these filters, such as probabilistic methods or adjusted cohort selection methods. Additionally, we recommend disclosing sample sizes for racial and ethnic groups both before and after data filters are applied to aid the reader in understanding the generalizability of the results. Future work should focus on exploring the effects of filters on downstream analyses.
Authors
- Oliver J. Bear Don’t Walk (ORCID: https://orcid.org/0000-0003-4310-9279)
- Kevin K. Tsang (ORCID: https://orcid.org/0000-0002-1531-3312)
- Kathleen LaRow Brown (ORCID: https://orcid.org/0000-0002-6625-4156)
- Yasaman Fatapour (ORCID: https://orcid.org/0000-0001-8660-1621)
- Michael Zietz
- Undina Gisladottir
- Hongyu Liu (ORCID: https://orcid.org/0000-0002-0686-1122)
- Nadine A. Friedrich (ORCID: https://orcid.org/0000-0002-6713-0614)
- Apoorva Srinivasan
- Nicholas P. Tatonetti (ORCID: https://orcid.org/0000-0002-2700-2597)
- Jose Miguel Acitores Cortina (ORCID: https://orcid.org/0009-0007-0361-9334)
- Aditi Kuchi (ORCID: https://orcid.org/0009-0005-4662-5051)
- Jacob Berkowitz
- Danner Peter (ORCID: https://orcid.org/0009-0006-5513-9845)
- Sophia Kivelson (ORCID: https://orcid.org/0000-0003-0937-6517)
Institutions
- Cedars-Sinai Medical Center (US)
- University of Washington Medical Center (US)
- Columbia University (US)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2025-03-27
- DOI
- https://doi.org/10.2196/67591
- Primary Topic
- Ethics in Clinical Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00