Race, Ethnicity, and Ancestry in Clinical Pathways: A Framework for Evaluation

Area of Science:

• Health Equity
• Clinical Decision-Making
• Medical Informatics

Background:

• Clinical algorithms aim for consistent and equitable medical care delivery.
• The appropriateness of including race, ethnicity, and ancestry in clinical decision-making is unclear.
• Existing clinical pathways may contain these demographic terms, necessitating evaluation.

Approach:

• Developed and applied a structured framework to assess race, ethnicity, and ancestry terms in clinical pathways.
• Reviewed 132 institutional clinical pathways, identifying 8 with demographic terms.
• Multispecialty teams evaluated 3 pathways using the framework, leading to term removal or modification.

Key Points:

• Race, ethnicity, or ancestry terms were removed (n=6) or modified (n=2) in all 8 pathways reviewed.
• Recommended practices include rigorous definitions, assessing mechanisms of associations, and mitigating inequities.
• Caution is advised when applying population data to individual patient encounters.

Conclusions:

• The developed framework provides a systematic approach to evaluating demographic terms in clinical guidelines.
• This process can help ensure clinical algorithms promote equity and avoid exacerbating disparities.
• The framework is potentially valuable for institutional programs and national organizations revising clinical guidelines.