健康医疗数据协同治理的现实困境与破解路径

Practical Challenges and Solutions for the Collaborative Governance of Health and Medical Data

摘要: 随着医疗行业的数字化转型，健康医疗数据加速资源化，但实践中却深陷信息交互壁垒、合规风险不可控及协同低效的现实困境。面对兼具多重利益属性的海量诊疗信息，传统的单一事后监管模式早已捉襟见肘。本文突破常规的制度修补思路，探索“规则代码化”的创新实践：首先通过构建分级治理体系纾解技术割裂下的数据碎片化分布难题，进而将复杂的合规红线转化为底层智能合约代码，实现自动化合规审查与权责明晰；在此基础上，引入Shapley值搭建价值量化反哺机制，从利益根源上激发基层机构的协作意愿。这种多维协同方案，为兼顾隐私保护与要素流通的健康医疗数据生态提供了现实可行的治理范式。

Abstract: With the digital transformation of the healthcare industry, the resource utilization of health and medical data is accelerating. However, in practice, it is deeply trapped in the realistic dilemmas of fragmented information exchange barriers, uncontrollable compliance risks, and inefficient coordination. Faced with massive diagnosis and treatment information possessing multiple interest attributes, the traditional single ex-post regulatory model has long been stretched to its limits. Breaking through the conventional approach of institutional patching, this paper explores the innovative practice of “Codification of rules”: first, by constructing a tiered governance system to alleviate fragmented data distribution caused by technological fragmentation; subsequently, by transforming complex compliance red lines into underlying smart contract code to achieve millisecond-level automated compliance review and clarify rights and responsibilities; on this basis, introducing the Shapley value to establish a value-quantified feedback mechanism, thereby stimulating the data-sharing motivation of grassroots institutions from the root of interests. This multi-dimensional collaborative scheme provides a practical governance paradigm for a medical data ecosystem that balances privacy protection and data element circulation.