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Gender and ethnicity bias in medicine: a text analysis of 1.8 million critical care records
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 million words) from a large US hospital wer...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Oxford University Press
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9802334/ https://www.ncbi.nlm.nih.gov/pubmed/36714859 http://dx.doi.org/10.1093/pnasnexus/pgac157 |
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author | Markowitz, David M |
author_facet | Markowitz, David M |
author_sort | Markowitz, David M |
collection | PubMed |
description | 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 million words) from a large US hospital were evaluated with natural language processing techniques in search of gender and ethnicity bias indicators. Consistent with nonlinguistic evidence of bias in medicine, physicians focused more on the emotions of women compared to men 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 to White 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 to White 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. |
format | Online Article Text |
id | pubmed-9802334 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98023342023-01-26 Gender and ethnicity bias in medicine: a text analysis of 1.8 million critical care records Markowitz, David M PNAS Nexus Social and Political Sciences 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 million words) from a large US hospital were evaluated with natural language processing techniques in search of gender and ethnicity bias indicators. Consistent with nonlinguistic evidence of bias in medicine, physicians focused more on the emotions of women compared to men 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 to White 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 to White 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. Oxford University Press 2022-08-18 /pmc/articles/PMC9802334/ /pubmed/36714859 http://dx.doi.org/10.1093/pnasnexus/pgac157 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of National Academy of Sciences. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Social and Political Sciences Markowitz, David M Gender and ethnicity bias in medicine: a text analysis of 1.8 million critical care records |
title | Gender and ethnicity bias in medicine: a text analysis of 1.8 million critical care records |
title_full | Gender and ethnicity bias in medicine: a text analysis of 1.8 million critical care records |
title_fullStr | Gender and ethnicity bias in medicine: a text analysis of 1.8 million critical care records |
title_full_unstemmed | Gender and ethnicity bias in medicine: a text analysis of 1.8 million critical care records |
title_short | Gender and ethnicity bias in medicine: a text analysis of 1.8 million critical care records |
title_sort | gender and ethnicity bias in medicine: a text analysis of 1.8 million critical care records |
topic | Social and Political Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9802334/ https://www.ncbi.nlm.nih.gov/pubmed/36714859 http://dx.doi.org/10.1093/pnasnexus/pgac157 |
work_keys_str_mv | AT markowitzdavidm genderandethnicitybiasinmedicineatextanalysisof18millioncriticalcarerecords |