Using the Framework¶
The Health Data Readiness Level (HDRL) Framework is designed to turn a complex sociotechnical operating environment into a structured evidence review and improvement roadmap. It can be applied at system, service or dual level, but the scope and evidence standard should be explicit before scoring begins.
What an HDRL assessment is — and is not
An HDRL assessment is a structured maturity assessment. It is not accreditation, certification, a compliance audit or an official decision on participation in the UK Health Data Research Service (HDRS) or any other programme. Scores describe the evidence available at the time of assessment and should be interpreted alongside context, capacity and the needs of the intended research use case.
A four-stage assessment¶
Define the assessment boundary
Choose system, service or dual-level assessment. Record the organisations, services, capabilities and time period in scope.
Assemble the evidence
Collect public, auditable and internally verifiable material before interviews. Use stakeholder testimony to explain evidence and identify gaps, not as an automatic substitute for it.
Score against the descriptors
Assess every applicable indicator against its five maturity descriptors. Record the evidence, rationale, uncertainty and evidence gap for each judgement.
Calibrate and build the roadmap
Review scoring consistency, invite factual correction through Right of Reply, and translate domain patterns into sequenced improvement actions.
Evidence is part of maturity¶
The framework deliberately distinguishes operational assertion from demonstrable performance. A service may have strong capability but receive a lower score when the supporting documentation, metrics or external assurance are not available.
| Level | Evidence expectation |
|---|---|
| L1 · Initial | Minimal or no documented capability. |
| L2 · Developing | Capability is demonstrated but remains informal or is supported mainly by uncorroborated testimony. |
| L3 · Defined | Formal, documented processes and responsibilities are in place. |
| L4 · Managed | Performance is measured, standardised and at least partly published or externally verifiable. |
| L5 · Optimising | Systematic improvement and credible benchmarking can be demonstrated over time. |
This evidence hierarchy helps surface an important distinction:
- Capability gap: the function, resource or pathway does not yet exist at the required maturity.
- Evidence gap: capability may exist, but documentation, metrics, audit evidence or published performance do not yet demonstrate it.
- Capacity gap: capability exists, but staffing, funding or operating headroom limit the volume or pace that can be delivered.
Capability and evidence visibility
HDRL v1.0 scores the capability demonstrated by the available evidence, so a result can reflect both operational maturity and the strength or visibility of its evidence. This protects against unsupported self-assessment, but the two concepts should be interpreted separately. A future validation phase should test whether capability maturity and evidence confidence are better recorded as distinct dimensions.
Choose the right unit of assessment¶
| Approach | Use when | Key consideration |
|---|---|---|
| System-level | Assessing a nation or health system as a potential node. | Service-level indicators need a defined primary service or a transparent aggregation method. |
| Service-level | Assessing an individual secure data environment (SDE), trusted research environment (TRE) or data service. | System indicators should be inherited from the relevant national context or marked not applicable. |
| Dual-level | Distinguishing systemic constraints from operational service gaps. | Keep the two evidence records explicit; a shared context does not mean identical scores. |
Interpret the result responsibly¶
An assessment can support¶
- a shared view of strengths, constraints and missing evidence;
- comparison of maturity patterns across domains;
- prioritisation of policy, service, workforce and infrastructure improvements;
- capability-specific planning for different research offers; and
- repeat assessment to track documented progress over time.
An assessment should not be used to¶
- treat a single overall score as a complete verdict;
- rank organisations without considering scope, evidence availability and institutional context;
- imply that one level guarantees delivery time, quality or participation;
- replace legal, ethical, security or data-controller decisions; or
- publish sensitive evidence or detailed assessment records without the relevant permissions.
Proposed Foundational Indicators¶
HDRL designates five indicators as Foundational Indicators and assumes a minimum of Level 3 for baseline participation within the framework's own assessment logic. The 3 Nations Final Report explicitly presents these as proposed conditions and a contribution to the initial HDRS design conversation, not as established or current HDRS requirements. Other programmes and international users should determine their own governance requirements rather than treating the five indicators as an externally mandated threshold.
Review the five proposed Foundational Indicators
Current validation status¶
HDRL has been applied formatively through one multi-jurisdiction assessment across three distinct UK health data systems. That application demonstrates practical feasibility, but it does not establish reliability, validity or accreditation fitness. Priorities for further work include independent expert and public content-validity review, scoring by multiple assessors, formal inter-rater reliability testing, sensitivity analysis, prospective application and refinement of Level 4 and Level 5 thresholds using UK and international benchmark data.
Good assessment discipline
Preserve an auditable record of the evidence, rationale, assessor judgement, uncertainty, Right of Reply and any score change. Readiness is dynamic, so always state the assessment date.