Institutional Frictions and Optimization Pathways of Class III AI-Powered Medical Devices in China: An Analysis Based on the Multiple Streams Framework

Currently, the article discusses the reasons why the clinical implementation of Class III artificial intelligence (AI) medical devices in China is limited, regardless of the accelerating technology and robust policy endorsement via programs such as the Healthy China 2030. Beyond technology and risk-based studies, the paper utilizes Kingdon’s Multiple Streams Framework (MSF) to determine how the lack of alignment across these three streams of the problem, policy, and political core has resulted in institutional wrangles that have remained. Using regulatory documents, secondary data, and policy evidence, the analysis can pinpoint three linked causes of friction: lengthy and mismatched regulatory approval processes, hospital system mismatch of capacity and responsibility, and the unresolved reimbursement/trust gap at the patient level. Such obstacles are reflections of institutional stalemateness, and not outdated technology, where current regulatory and payment strategies are ill-equipped to respond flexibly and data-driven AI applications. To resolve this misalignment, the paper compares two policy courses, including a market-led adaptive model and a model of rule-based governance, and suggests a step-by-step reform agenda involving the use of regulatory sandboxes, nationally standardized reimbursement, centralized data and reporting, etc. This strategy aims at compensating the innovation incentive, equity, and system persistence by balancing short-term experimentation with long-term institutional coordination. The research paper can add to the literature as it generalizes on the use of MSF and its use in technology governance and provides practical policy recommendations to enhance regulatory consistency and promote the seamless introduction of AI-driven medical devices in China.