Evaluating the Use of Sex in Gastroenterology Algorithms: A Fairness Assessment in Representing Sex Framework Analysis

INTRODUCTION: Clinical algorithms are integral to decision-making in gastroenterology, yet the inclusion of sex as a variable remains underexamined. We applied the Fairness Assessment in Representing Sex (FAIRS) framework to evaluate the medical, ethical, and equity implications of sex-based variables in adult gastroenterology algorithms. METHODS: Of 184 algorithms reviewed, 11 met inclusion criteria by explicitly incorporating sex or gender. The FAIRS framework was applied to these algorithms. RESULTS: Using FAIRS, 10 algorithms demonstrated appropriate and clinically justified inclusion of sex, typically reflecting biologically meaningful differences that improved prognostic accuracy without exacerbating disparities. Notably, Model for End-Stage Liver Disease 3.0 exemplified how sex inclusion can mitigate inequity in liver transplant allocation. By contrast, the Obesity Surgery Mortality Risk Score failed FAIRS criteria because evidence suggests sex-based risk differences are confounded by comorbidities and access to care. DISCUSSION: Our findings highlight that sex inclusion in algorithms must be explicitly justified, continuously reevaluated, and contextualized to avoid perpetuating bias.