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Abstract
Healthcare systems worldwide are increasingly confronted with the dual challenge of population aging and the rising prevalence of chronic disease and multimorbidity. As healthcare and long-term care expenditures continue to grow, greater attention has been directed toward preventive approaches that can support health earlier in the disease trajectory while maintaining fiscal sustainability. Yet, despite this growing emphasis on prevention, many contemporary healthcare systems remain primarily oriented toward the detection and management of measurable disease risk. Preventive interventions are typically initiated only after biomedical indicators exceed established thresholds, leaving subtle subjective changes that precede diagnosable disease insufficiently addressed.
East Asian medicine (EAM), including Kampo, offers a different preventive perspective through the concept of mibyo (“not yet a disease”), which emphasizes the recognition and management of pre-disease states before overt pathology develops. Rather than focusing exclusively on discrete disease categories, EAM approaches health as a dynamic balance shaped by constitution, lifestyle, environment, and emotional state. Through individualized diagnostic frameworks such as sho (pattern differentiation), practitioners seek to identify subtle patterns of imbalance and intervene before disease fully manifests.
Japan provides a particularly important context for examining this approach because Kampo has been institutionally integrated into the modern healthcare system while remaining only partially operationalized within mainstream preventive care. At the same time, emerging digital health initiatives in Japan are increasingly exploring how technologies such as machine learning, imaging systems, and clinical data platforms may support the standardization, accessibility, and scalability of Kampo-based diagnostic approaches. This paper explores how the concept of mibyo, together with emerging digital technologies, may contribute to more anticipatory and personalized models of prevention within contemporary healthcare systems.
Author
KPMG AZSA LLC
Michikazu Koshiba
Director - Healthcare & Well-being (HC&WB)
Ritsuko Yamagata
Senior Manager
Nodoka Kobayashi
Senior Associate