Clinically informed machine learning elucidates the shape of hospice racial disparities within hospitals.

ABSTRACT: Racial disparities in hospice care are well documented for patients with cancer, but the existence, direction, and extent of disparity findings are contradictory across the literature. Current methods to identify racial disparities aggregate data to produce single-value quality measures that exclude important patient quality elements and, consequently, lack information to identify actionable equity improvement insights. Our goal was to develop an explainable machine learning approach that elucidates healthcare disparities and provides more actionable quality improvement information. We infused clinical information with engineering systems modeling and data science to develop a time-by-utilization profile per patient group at each hospital using US Medicare hospice utilization data for a co

SUBMITTER: Khayal IS 

PROVIDER: S-EPMC10570342 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature