Fairness gaps in Machine learning models for hospitalization and emergency department visit risk prediction in home healthcare patients with heart failure.

The findings highlight substantial differences in fairness metrics across diverse patient subpopulations in ML risk prediction models for heart failure patients receiving home healthcare services. Ongoing monitoring and improvement of fairness metrics are essential to mitigate biases.