From Static States to Dynamic Disease: Why Clinical Medicine Must Reframe Illness as a Temporal Process

Abstract

This paper examines why clinical medicine continues to treat disease as a static state despite extensive theoretical and empirical evidence that illness unfolds as a dynamic process over time. Drawing on physiological research, complexity theory, large-scale clinical registry implementation, and human-centered systems design, the paper traces an unbroken intellectual lineage from early work on dynamic stability to contemporary challenges in AI-driven healthcare. Rather than proposing a new model, the paper analyses structural and organisational reasons why dynamic disease concepts have remained marginal in clinical practice. It argues that the persistence of static representations reflects limitations of healthcare infrastructures—governance, accountability, and digital systems—rather than scientific uncertainty. The paper positions dynamic disease frameworks as a prerequisite for patient safety, responsible AI implementation, and sustainable clinical decision-making.

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