The Medical Insurance Image Cloud (MIIC) is a cloud-based medical imaging management system led by the National Healthcare Security Administration, aiming to achieve the business objectives of "accessible to patients, retrievable by healthcare providers, and verifiable by medical insurance" and address the persistent problem of repeated imaging examinations across healthcare institutions. Drawing on systems theory, this paper analyzes the construction logic of the MIIC business system along three dimensions: system architecture, operation mechanisms, and optimization mechanisms. The study deconstructs the business system into four core business domains—data collection, quality control, caching, and retrieval—and elucidates the operational logic of the full-pipeline closed loop of "collection-quality control-caching-retrieval". It further reveals a synergistic architecture comprising the "1+32" hierarchical structure as the organizational backbone, "centralized indexing with distributed data" as the technical foundation, the MIIC index as the data circulation hub, the "5-yuan service fee" as the operational fulcrum, diversified settlement mechanisms as the operational safeguard, and data-driven medical insurance governance as the value engine. The study identifies four structural challenges confronting the system: dilemmas in data quality governance, inadequate incentives for healthcare institutions, the trade-off between privacy protection and data utilization, and structural risks to operational sustainability. Accordingly, it proposes optimization pathways across four dimensions—full-pipeline data quality governance, incentive-compatible participation mechanisms, a legal framework for privacy protection, and sustainable operational ecosystems with technology evolution paths—so as to provide theoretical support and policy references for the high-quality development of the MIIC.