The extent of gender/sex variables included in clinical algorithms across medical specialties

Publication information:

Davis, Seetha H., Ann Caroline Danielsen, Ivan Yi-Fan Hsiao, Kendra K. Albert, Maggie K. Delano, Carmel Shachar, Sarah S. Richardson, David S. Jones, and Nancy Krieger. “The Extent of Gender Sex Variables Included in Clinical Algorithms across Medical Specialties”. Health Affairs 45, no. 7 (2026).

Abstract

Gender/sex variables are often included in clinical algorithms, typically without articulating which aspects of gender or sex-linked biologies are hypothesized to contribute to the tools’ output. To date, there exists little systematic evaluation of how gender/sex inputs are used in clinical algorithms. We analyzed all clinical algorithms available in the online database MDCalc, assessing whether and how they include gender/sex inputs. For tools with gender/sex inputs, we evaluated the consequences of, justification for, and timeline of including such inputs. Of 602 tools reviewed, 112 (18.6 percent) included gender/sex. These inputs were used to adjust the algorithmic outcome by directly allocating points according to a change in the gender/sex variable or to normalize the outcome by using gender/sex to interpret other tool inputs. Fewer than half of tools included text justifying the inclusion of gender/sex in initial tool development, and only five tools had been updated since their initial development. Systematic reconsideration and regular reevaluation of gender/sex inputs in clinical algorithms may be needed to determine which inputs, if any, are warranted to support clinicians in providing better care for patients.