Leveraging Clinical Informatics to Address the Quintuple Aim for End-of-Life Care

Abstract

As the population of older adults grows at an unprecedented rate, there is a large gap to provide culturally tailored end-of-life care. This study describes a payor-led, informatics-based approach to identify Medicare members who may benefit from a Compassionate Care^SM Program (CCP), which was designed to provide specialized care management services and support to members who have end-stage and/or life-limiting illnesses by addressing the quintuple aim. Potential participants are identified through machine learning models whereby nurse care managers then provide tailored outreach via telephone. A retrospective, observational cohort analysis of propensity-weighted Medicare members was performed to compare decedents who did or did not participate in the CCP. This program enhanced the end-of-life care experience while providing equitable outcomes regardless of age, gender, and geography and decreased inpatient (-37%) admissions with concomitant reduced (-59%) medical spend when compared to decedents that did not utilize the end-of-life care management program.