In April 2024, over 20 scientists, clinicians, and experts in health equity convened in Denver, Colorado, for an interdisciplinary Summit on Advancing Precision in Health Assessment. The Summit was hosted by the National Academy of Neuropsychology (NAN) with an aim to develop a pathway to identify, assess, and implement alternatives to broad proxies, such as race and sex/gender, in health assessments. Presentations and breakout group discussions focused on re-examining existing clinical algorithms for bias; how big data, artificial intelligence, and machine learning will lead to new algorithms and how to design and use these in ethical ways and how to assess and successfully implement changes in health care assessment aimed at achieving equity. Race received the most discussion. Participants supported calls to replace race-based decision-making tools that erroneously consider race as a biological variable. When possible, underlying social determinants of health should be included in clinical algorithms. Moving forward, research should include clear definitions and justification for all variables used. Future research paths should assess the utility and fairness of algorithms across groups before and after implementation. Changing the narrative to focus on better health for all people, and to achieving health equity, will require collaboration, partnerships, and openness to innovation.
Arredondo et al. (Thu,) studied this question.