책임은 귀사의 아키텍처에 내재 : ´데이터 공유 동의´에 대한 심층 분석

This IDC Perspective shares an outlook on the evolving consent landscape, the architectural and operational challenges payers face, and recommendations for technology buyers and partners.Consent-to-share is foundational to a data sharing strategy within the healthcare interoperability ecosystem.The trajectory from meaningful use to modern interoperability mandates reveals a recurring pattern: rapid enablement of data exchange followed by delayed industry standardization of controls.For payers, the absence of foundational consent standards shifts complexity downstream to them, requiring customized governance overlays, manual audits, and vendor-specific controls. The healthcare system has "opened the barn door" with large-scale data exchange but failed to implement commensurate control structures. Time is running out: foundational controls cannot be retrofitted once data is already flowing at scale.Payers must proactively invest in agile, defensible consent infrastructure to preserve trust, ensure compliance, and prevent erosion of legitimate access to clinical data by investing in robust architecture, operational processes, and governance, aiming to meet regulatory requirements, building member trust, and enabling secure, efficient data exchange."Regulators and courts no longer care what you intended. They care what your systems allow.... Liability lives in architecture," says Jeff Rivkin, research director of Payer IT Strategies, IDC.

Executive Snapshot

• Key takeaways
• Recommended actions

Situation Overview

• Executive summary
• Background
  • The new landscape of consent
  • Regulatory drivers and mandates
  • Consumer expectations and trust
• Historical perspective: From inefficient meaningful use to dangerously governed interoperability mandates
  • FHIR and the shift to API-driven exchange
  • Regulatory acceleration and the consent gap
  • Consent in a governance crisis
    • The Epic versus Health Gorilla lawsuit
    • Multiple regulatory and legal exposures
    • Five questions investigators now ask
• Defining health data sharing consent
  • Consent models and options
  • Qualities of a meaningful consent decision
  • Delegation of consent
  • Provenance and auditability
• Consent-to-share architecture for payers
  • Core architectural components
  • Consent-to-share capture models - inputs
  • Centralized consent repositories - storage
    • Consent as a service
    • Blockchain approaches
  • Request verification and data sectioning - outputs
• Regulatory and policy considerations
  • Standards
  • Federal regulations: HIPAA, Cures Act, and TEFCA
  • State-level regulations and preemption
  • Sensitive data categories and segmentation
  • Public health exceptions
• Risks and governance gaps
  • Under-governed interoperability: The core risk
  • Some payers have AI model governance, but lack AI data governance
  • Fragmented consent capture and enforcement
  • Lack of standards-based consent enforcement
• Operationalizing consent: Processes and challenges
  • Processes
  • Challenges
    • Ensuring data integrity and provenance
    • Verifying and matching data requests
    • Purpose limitation and dynamic matching
    • Secure, transparent data presentation and auditability
    • Complexity of delegation
    • Regulatory patchwork
    • Consumer comprehension

Advice for the Technology Buyer

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• Synopsis