Management Consulting

Aon collaborated with a multinational employer facing the challenge of managing a significant number of recurring high-cost polychronic members within their health plan. The client aimed to enhance engagement among these plan members and improve clinical outcomes, particularly focusing on those most likely to drive costs higher. To address this issue, Aon implemented its Health Risk Analyzer, a machine learning-powered tool designed to predict future claims costs for each member of the health plan. The analysis revealed that half of the predicted high-risk cohort had not been identified by the existing care management program, which contributed to low engagement levels. Aon worked closely with the employer to utilize these predictions to optimize their health program, proactively engaging the high-risk members in care management. As a result of this tailored intervention, 20 percent of the identified high-risk members were actively managed by the employer’s clinical programs. This proactive management is expected to lead to improved health outcomes and cost savings, translating to an anticipated claim savings of over $2,000 for each additional managed individual. This case exemplifies how leveraging machine learning can significantly enhance employee health management and reduce healthcare costs for employers.