Abstract:

The integration of smart devices, mobile health applications, and commercial health insurance is transforming proactive health data into a crucial basis for underwriting, pricing, claims processing, and health interventions. Drawing on the analytical evaluation approach of Design Science Research (DSR), this paper proposes a secure data circulation mechanism centered on purpose limitation and accountable computing. The mechanism categorizes data sensitivity into high, medium, and low levels, and classifies usage purposes into service, transaction, and modeling categories, thereby establishing a“data sensitivity×purpose type”matrix for authorization and computation. Based on this framework, it configures verification channels using individual-level Trusted Execution Environments (TEEs) and modeling channels utilizing population-level privacy-preserving computing. The study concludes that the mechanism’s effectiveness hinges on the alignment among scenarios, data granularity, computing environments, output formats, and audit evidence, offering an actionable framework for the secure circulation of proactive health data within health insurance ecosystems.

Key words: proactive health, health insurance, secure data circulation