Ethics of Data Sharing in Medical Research

1. Research problem

How should researchers weigh public benefit against re-identification and consent risks? The project would examine this question within responsible innovation, where institutional arrangements, measurable outcomes and the costs of implementation may point in different directions. It is designed as a falsifiable research programme rather than a claim that the proposed mechanism has already been demonstrated.

2. Working proposition

Tiered access and clear purpose limitation can improve legitimate secondary research. This is a testable proposition, not an established result. Competing explanations and contexts in which the mechanism fails should be specified before data collection begins.

3. Research theses for examination

1. Mechanism: Tiered access and clear purpose limitation can improve legitimate secondary research.
2. Boundary conditions: Assess whether the proposition remains plausible when jurisdiction, organisational maturity, resource constraints or stakeholder interests change.
3. Disconfirmation: Record which observations would favour an alternative explanation or show that the proposed approach adds no meaningful value.

4. Research design and methods

Map data sharing models, governance boards and statistical privacy thresholds. The initial protocol should establish sampling criteria, the unit of analysis, definitions of variables or legal concepts, a transparent source register, and access and ethics approvals where necessary.

5. Evidence horizon and relevant developments

WHO World Health Statistics 2026 consolidates health-related SDG indicators and reviews inequalities and progress in health outcomes. It supplies population-level context, not proof that a proposed clinical intervention works.

WHO extended its Global Strategy on Digital Health through 2027, emphasising the combined financial, organisational, human and technological requirements of health-system transformation.

The cited publications provide current institutional context and candidate sources for the literature review. They do not certify the proposed hypothesis; original empirical work, careful comparison and jurisdiction-specific validation would still be required.

6. Planned work packages

1. Conceptual groundwork: Define the research object, terminology, competing frameworks and decision context.
2. Evidence mapping: Create an auditable inventory of relevant primary evidence, with dates, definitions, strengths and limitations.
3. Evaluation: Map data sharing models, governance boards and statistical privacy thresholds; contrast results with alternative specifications, control cases or rival interpretations.
4. Critical review: Report missing observations, conflicting evidence, implementation costs and circumstances that limit transferability.
5. Translation into practice: Prepare the intended practical output and an independent review checklist.

7. Anticipated research product

Research data stewardship protocol. The deliverable will be evaluated against the research question and the evidence collected.

8. Limitations, ethics and scholarly integrity

At this stage no original sample, statistical test, clinical cohort or experimental result is claimed. Any future research involving human participants, proprietary data, medical outcomes or regulated activities must obtain the applicable permissions. Publicly accessible official publications are cited for context only; their findings are not represented as findings of BBARTI.

9. Selected institutional reading

• WHO · World Health Statistics 2026 ↗13 May 2026
• WHO · Global Strategy on Digital Health 2020–2027 ↗1 December 2025