Inclusive Equitable Research

Research participants often do not represent the target population for treatment. Systematic exclusion of particular groups limits the generalizability of research and perpetuates health inequalities. The REP-EQUITY toolkit guides representative and equitable inclusion in research. Its use may promote trust between communities and research institutions and improve the applicability of research findings.

Read more on Nature Medicine.

Patient-reported outcomes are increasingly collected in clinical trials and in routine clinical practice, but strategies must be taken to include underserved groups to avoid increasing health disparities. Our Nature Medicine article and ongoing work within the NIHR Birmingham BRC considers current challenges related to PRO data collection in underserved groups and identifies approaches for greater inclusion.

Relevant links:

• Patient reported outcome assessment must be inclusive and equitable | Nature Medicine
• Improving outcomes for people with inflammatory diseases - NIHR Birmingham Biomedical Research Centre

Health datasets should be curated with inclusivity and diversity in mind. We have developed recommendations to ensure AI healthcare technologies are supported by adequately representative data. The recommendations aim to encourage transparency around ‘who’ is represented in the data, ‘how’ people are represented, and how health data is used.

Relevant links:

• Data diversity website
• Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations - PubMed
• Tackling bias in AI health datasets through the STANDING Together initiative - PubMed