Open framework · Version 1.0.1
Make readiness for health data research visible¶
Health Data Readiness Level (HDRL) is a practical, evidence-informed maturity framework for assessing organisational and system readiness for trusted, federated health data research.
Its 64 indicators turn broad principles into a structured view of capability, evidence gaps and investment priorities across the whole operating environment.
Commissioned by and intellectual property rights owned by Research Data Scotland; originated and developed by OPL Advisory Ltd.
Version and validation: The paper reports the original applied HDRL v1.0. The website presents v1.0.1, a clarification release that changes programme-status language only; it makes no changes to the method, indicators, evidence or assessment results. Further independent validation is required. Review the evidence and limitations.
Framework distinct from programme requirements
HDRL supports assessment, comparison and improvement planning for health data research services, networks and systems in the UK and internationally. Its first application informed discussion about the emerging UK Health Data Research Service (HDRS), but it is not an official HDRS standard, accreditation scheme or participation decision. The five Foundational Indicators are proposals within HDRL's own assessment logic, not established programme requirements.
The missing middle¶
From principles and specifications to a usable readiness roadmap
Federated health data research is a sociotechnical undertaking, not simply a technology deployment. Data coverage, semantics, governance, research delivery, public trust, long-term sustainability and skilled people all have to work together. HDRL provides a common assessment structure across those interdependent conditions, regardless of governance model, organisational structure or scale.
Five Safes, public benefit and trustworthy data use
Evidence, capability gaps and an improvement roadmap
Trusted research environment architecture, secure data environment specifications and information-security standards
See the whole system
Assess technical, organisational, governance and trust conditions in one coherent view.
Separate assertion from evidence
Make visible where capability exists but documentation, metrics or external assurance lag behind.
Target improvement
Translate maturity patterns into practical priorities for policy, investment and service development.
Eight domains, one readiness picture¶
Each domain answers a distinct question about trusted research delivery
Data Coverage & Federation
Are the required data available, linkable and usable across settings?
Domain BData Semantics & Quality
Can data be understood, assessed and reused consistently?
Domain CGovernance & Access
Can safe, lawful research be approved and delivered efficiently?
Domain DResearch Integration & Market Use
Does the service support real research use, collaboration and impact?
Domain EPublic Trust & Transparency
Are transparency, public benefit and meaningful engagement built in?
Domain FSustainability
Can capability, funding and service continuity be sustained over time?
Domain GWorkforce & Culture
Are the people, skills and service culture in place to deliver?
Domain HInfrastructure & Compute Capacity
Is the technical environment secure, resilient and scalable?
Value across the research ecosystem¶
A common language for people making different decisions
Policy makers & funders
Distinguish policy, infrastructure, workforce and evidence priorities so investment can address the real constraint.
Data services & operators
Build a practical improvement roadmap and identify the evidence needed to demonstrate dependable delivery.
Researchers
Understand the conditions that shape discovery, access, analysis and multi-site delivery.
Industry partners
Assess evidence of operational capability and predictability without treating a maturity level as a guarantee.
Patients & the public
See how transparency, public benefit, safeguards and meaningful engagement form part of readiness.
System partners
Compare heterogeneous services using a shared structure while retaining local governance and context.
Developed for a real cross-nation challenge¶
HDRL originated in the 3 Nations Readiness Assessment, commissioned by Research Data Scotland on behalf of Scotland, Wales and Northern Ireland and delivered by OPL Advisory. Its formative application combined documentary evidence, stakeholder engagement, national workshops, structured Right of Reply and two research use-case stress tests.
That field application tested whether one framework could create a consistent, decision-useful view across different health data research systems without assuming a single institutional model. Research Data Scotland published the Final Report on 14 July 2026, and the framework-development and formative-application paper was posted on medRxiv on 27 July 2026.
Understand the model
Start with its purpose, scope, units of assessment and relationship to other standards.
Framework overview →Apply it responsibly
Define scope, collect evidence, score descriptors and turn findings into a roadmap.
How to apply HDRL →Go to the reference
Review all domains, maturity levels, classifications and proposed Foundational Indicators.
Indicator quick reference →