Gender and ethnicity bias in medicine: a text analysis of 1.8 million critical care records
| dc.contributor.author | Markowitz, David M. | |
| dc.date.accessioned | 2023-10-17T20:00:22Z | |
| dc.date.available | 2023-10-17T20:00:22Z | |
| dc.date.issued | 2022-08-18 | |
| dc.description | 11 pages | en_US |
| dc.description.abstract | Gender and ethnicity biases are pervasive across many societal domains including politics, employment, and medicine. Such biases will facilitate inequalities until they are revealed and mitigated at scale. To this end, over 1.8 million caregiver notes (502 millionwords) from a large US hospitalwere evaluated with natural language processing techniques in search of gender and ethnicity bias indicators. Consistent with nonlinguistic evidence of bias in medicine, physicians focusedmore on the emotions ofwomen compared tomen and focused more on the scientific and bodily diagnoses of men compared to women. Content patterns were relatively consistent across genders. Physicians also attended to fewer emotions for Black/African and Asian patients compared toWhite patients, and physicians demonstrated the greatest need to work through diagnoses for Black/African women compared to other patients. Content disparities were clearer across ethnicities, as physicians focused less on the pain of Black/African and Asian patients compared toWhite patients in their critical care notes. This research provides evidence of gender and ethnicity biases in medicine as communicated by physicians in the field and requires the critical examination of institutions that perpetuate bias in social systems. | en_US |
| dc.identifier.citation | David M Markowitz, Gender and ethnicity bias in medicine: a text analysis of 1.8 million critical care records, PNAS Nexus, Volume 1, Issue 4, September 2022, pgac157, https://doi.org/10.1093/pnasnexus/pgac157 | en_US |
| dc.identifier.uri | https://doi.org/10.1093/pnasnexus/pgac157 | |
| dc.identifier.uri | https://hdl.handle.net/1794/28991 | |
| dc.language.iso | en | en_US |
| dc.publisher | Oxford Academic | en_US |
| dc.rights | Creative Commons BY-NC-ND 4.0-US | en_US |
| dc.subject | Bias | en_US |
| dc.subject | Gender | en_US |
| dc.subject | Ethnicity | en_US |
| dc.subject | Language | en_US |
| dc.subject | Medicine | en_US |
| dc.title | Gender and ethnicity bias in medicine: a text analysis of 1.8 million critical care records | en_US |
| dc.type | Article | en_US |