Sex and Gender Bias in Technology and Artificial Intelligence–Chapter 2: Sex and gender inequality in precision medicine: Socioeconomic determinants of health

Elsevier, Sex and Gender Bias in Technology and Artificial Intelligence: Biomedicine and Healthcare Applications, Volume, 1 January 2022
Buslon N., Cortes A., Racionero-Plaza S.

Both Human Rights and United Nations’ Sustainable Development Goals make clear that addressing the challenge of achieving an inclusive precision medicine, which does not leave women behind, is not a question of choice but a must. In this regard, the biomedical, artificial intelligence, and clinical research fields have a unique opportunity to make a difference. Yet, attaining those rights and goals implies acknowledging that not everyone has the same opportunities and outcomes in health. This has been well explored by the literature on social determinants of health, which points to differences in health status and outcomes as affected by socioeconomic factors, such as socioeconomic status, geographical location, and education. Sex and gender are the key factors, and current scientific literature has already reported specific ways in which they affect health status and experiences with the health system, in terms of negatively influencing access, diagnosis, and treatment. When various socioeconomic factors coincide, as it happens in women from ethnic minorities living in poverty, then outcomes are even worse. Likewise, gender myths, stereotypes, and false assumptions have a negative impact on girls’ and adult women's health. Algorithms employed and applied to precision medicine must take all this knowledge about various socioeconomic circumstances, inequalities in health, age, sex, and gender differences specific to some diseases, to overcome the so-called sex and gender blindness of medical research and practice, allowing precision medicine to be inclusive of all patient groups, including women.