Data-driven identification of hub chains in disease accruals to reduce healthcare utilization and costs

BACKGROUND: Understanding how diseases accumulate over time is crucial for managing their combined impact. We aim to identify these common pathways of multimorbidity and determine how they increase healthcare use and costs beyond the sum of single diseases. METHODS: We analyzed hospital records from over 600,000 patients in China between 2013 and 2021. We identified significant sequences of three diseases diagnosed over time and measured their synergistic effect by comparing the total healthcare use along a sequence to the added use of each disease occurring in isolation. Outcomes included hospital visits, length of stay, total costs, and out-of-pocket spending. We then grouped these sequences to identify common, high-impact connections between diseases, referred to as hub chains. RESULTS: Here we show that distinct disease sequences are common, with 83 pathways identified in women and 174 in men. The combined cost of a disease sequence often exceeds the sum of its parts, in 69.9% (58/83) of female and 81.0% (141/174) of male trajectories, demonstrating a synergistic effect. Pathways involving cancer-related care show the highest resource use for both sexes. We find that a small number of critical hub chains connect many sequences; analyses indicate that interrupting these hubs could reduce associated healthcare use and costs by approximately half. CONCLUSIONS: This study demonstrates that specific sequences of diseases, particularly those linked by hub chains, drive disproportionate healthcare burdens. Focusing clinical interventions and policy on these high-impact pathways offers a promising strategy to alleviate system strain and improve care for patients with multimorbidity.