Secondary Health‑Data Use — Governance Altitude

Secondary use of health data is a system‑layer governance problem, not an analytics problem.

• Friction comes from fragmented review bodies, inconsistent public‑interest criteria, and dual approvals without aligned definitions. - OECD’s criteria (population health, research quality, ethical proportionality, equity, transparency) are consequence‑architecture tools, not policy slogans.

Public interest is not a moral label; it is a structured governance test.

• Review bodies must evaluate proportionality, data necessity, scientific independence, and safeguards (PETs, TREs, TEEs).
• Cross‑border fragmentation is the primary blocker to legitimate secondary use.

• Divergent interpretations of public interest create regulatory drag.
• Excessive approval durations reduce societal benefits and slow innovation.
• Dual‑body approvals (HDABs, ethics committees, DPAs) require aligned criteria to avoid contradictory decisions.

• Trusted technical environments (PETs, TREs, TEEs) convert sensitive data into legitimate public value.
• Scientific independence must be structurally protected, especially in industry‑funded studies.
• Transparency and publication freedom are governance safeguards, not optional extras.

• OECD alignment is the only path to seamless secondary use across jurisdictions.
• Without harmonised criteria, federated data spaces and AI‑enabled analytics cannot scale.

• PETs (Privacy‑Enhancing Technologies) enable secure data analysis without exposing raw information.
• TREs (Trusted Research Environments) provide controlled access for accredited researchers under strict governance.
• TEEs (Trusted Execution Environments) ensure computation integrity by isolating sensitive processes from external interference. Together, these technical guardrails convert sensitive health data into legitimate public value while maintaining privacy and trust.

Secondary health‑data use is consequence architecture. Clear criteria, aligned review bodies and trusted technical guardrails are what convert sensitive data into legitimate public interest — and prevent the fragmentation loop that currently slows cross‑border health innovation.