Promoting Anti-Racism in Clinical Practice: Lessons Learned in the Process of Removing the Race Coefficient from the Estimated Glomerular Filtration Rate Algorithm
Background: Promoting anti-racism in medicine entails naming racism as a contributor to health inequities and being intentional about changing race-based practices in health care. Unscientific assumptions about race have led to the proliferation of race-based coefficients in clinical algorithms. Ide...
| Format: | Article |
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| Language: | English |
| Published: |
Mary Ann Liebert
2023-11-01
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| Series: | Health Equity |
| Online Access: | https://www.liebertpub.com/doi/full/10.1089/HEQ.2023.0095 |
| _version_ | 1797402343836221440 |
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| collection | DOAJ |
| description | Background: Promoting anti-racism in medicine entails naming racism as a contributor to health inequities and being intentional about changing race-based practices in health care. Unscientific assumptions about race have led to the proliferation of race-based coefficients in clinical algorithms. Identifying and eliminating this practice is a critical step to promoting anti-racism in health care. The New York City Department of Health and Mental Hygiene (NYC-DOHMH) formed the Coalition to End Racism in Clinical Algorithms (CERCA), a health system consortium charged with eliminating clinical practices and policies that perpetuate racism.
Objective: This article describes the process by which an academic medical center guided by the NYC-DOHMH tackled race-based clinical algorithms.
Methods: Multiple key interested parties representing department chairs, hospital leaders, researchers, legal experts, and clinical pathologists were convened. A series of steps ensued, including selecting a specific clinical algorithm to address, conducting key informant interviews, reviewing relevant literature, reviewing clinical data, and identifying alternative and valid algorithms.
Key Outcomes: Given the disproportionately higher rates of chronic kidney disease risk factors, estimated glomerular filtration rate (eGFR) was prioritized for change. Key informant interviews revealed concerns about the clinical impact that removing race from the equation would have on patients, potential legal implications, challenges of integrating revised algorithms in practice, and aligning this change in clinical practice with medical education. This collaborative process enabled us to tackle these concerns and successfully eliminate race as a coefficient in the eGFR algorithm.
Conclusions: CERCA serves as a model for developing academic and public health department partnerships that advance health equity and promote anti-racism in practice. Lessons learned can be adapted to identify, review, and remove the use of race as a coefficient from other clinical guidelines. |
| first_indexed | 2024-03-09T02:22:57Z |
| format | Article |
| id | doaj.art-9cdd0fbdb98c4efe888444a9cfc68c1b |
| institution | Directory Open Access Journal |
| issn | 2473-1242 |
| language | English |
| last_indexed | 2024-03-09T02:22:57Z |
| publishDate | 2023-11-01 |
| publisher | Mary Ann Liebert |
| record_format | Article |
| series | Health Equity |
| spelling | doaj.art-9cdd0fbdb98c4efe888444a9cfc68c1b2023-12-06T16:26:30ZengMary Ann LiebertHealth Equity2473-12422023-11-0110.1089/HEQ.2023.0095Promoting Anti-Racism in Clinical Practice: Lessons Learned in the Process of Removing the Race Coefficient from the Estimated Glomerular Filtration Rate AlgorithmBackground: Promoting anti-racism in medicine entails naming racism as a contributor to health inequities and being intentional about changing race-based practices in health care. Unscientific assumptions about race have led to the proliferation of race-based coefficients in clinical algorithms. Identifying and eliminating this practice is a critical step to promoting anti-racism in health care. The New York City Department of Health and Mental Hygiene (NYC-DOHMH) formed the Coalition to End Racism in Clinical Algorithms (CERCA), a health system consortium charged with eliminating clinical practices and policies that perpetuate racism. Objective: This article describes the process by which an academic medical center guided by the NYC-DOHMH tackled race-based clinical algorithms. Methods: Multiple key interested parties representing department chairs, hospital leaders, researchers, legal experts, and clinical pathologists were convened. A series of steps ensued, including selecting a specific clinical algorithm to address, conducting key informant interviews, reviewing relevant literature, reviewing clinical data, and identifying alternative and valid algorithms. Key Outcomes: Given the disproportionately higher rates of chronic kidney disease risk factors, estimated glomerular filtration rate (eGFR) was prioritized for change. Key informant interviews revealed concerns about the clinical impact that removing race from the equation would have on patients, potential legal implications, challenges of integrating revised algorithms in practice, and aligning this change in clinical practice with medical education. This collaborative process enabled us to tackle these concerns and successfully eliminate race as a coefficient in the eGFR algorithm. Conclusions: CERCA serves as a model for developing academic and public health department partnerships that advance health equity and promote anti-racism in practice. Lessons learned can be adapted to identify, review, and remove the use of race as a coefficient from other clinical guidelines.https://www.liebertpub.com/doi/full/10.1089/HEQ.2023.0095 |
| spellingShingle | Promoting Anti-Racism in Clinical Practice: Lessons Learned in the Process of Removing the Race Coefficient from the Estimated Glomerular Filtration Rate Algorithm Health Equity |
| title | Promoting Anti-Racism in Clinical Practice: Lessons Learned in the Process of Removing the Race Coefficient from the Estimated Glomerular Filtration Rate Algorithm |
| title_full | Promoting Anti-Racism in Clinical Practice: Lessons Learned in the Process of Removing the Race Coefficient from the Estimated Glomerular Filtration Rate Algorithm |
| title_fullStr | Promoting Anti-Racism in Clinical Practice: Lessons Learned in the Process of Removing the Race Coefficient from the Estimated Glomerular Filtration Rate Algorithm |
| title_full_unstemmed | Promoting Anti-Racism in Clinical Practice: Lessons Learned in the Process of Removing the Race Coefficient from the Estimated Glomerular Filtration Rate Algorithm |
| title_short | Promoting Anti-Racism in Clinical Practice: Lessons Learned in the Process of Removing the Race Coefficient from the Estimated Glomerular Filtration Rate Algorithm |
| title_sort | promoting anti racism in clinical practice lessons learned in the process of removing the race coefficient from the estimated glomerular filtration rate algorithm |
| url | https://www.liebertpub.com/doi/full/10.1089/HEQ.2023.0095 |