Guiding principles to address the impact of algorithm bias on racial and ethnic disparities in health and health care (15 December 2023)

Summary

Health care algorithms are used for diagnosis, treatment, prognosis, risk stratification and allocation of resources. However, bias in the development and use of algorithms can lead to worse outcomes for racial and ethnic minoritised groups and other historically marginalised populations such as individuals with lower incomes.

This study aimed to provide a conceptual framework and guiding principles for mitigating and preventing bias in health care algorithms, in order to promote health and health care equity. The authors suggested five guiding principles:

1. Promote health and health care equity during all phases of the health care algorithm life cycle
2. Ensure health care algorithms and their use are transparent and explainable
3. Authentically engage patients and communities during all phases of the health care algorithm life cycle and earn trustworthiness
4. Explicitly identify health care algorithmic fairness issues and trade-offs
5. Establish accountability for equity and fairness in outcomes from health care algorithms.