Registry, Outcomes & RWE
Turn routine data into real-world evidence
Registry data models, outcomes dictionaries and an evidence pathway that supports publication and market access.
What we deliver
Evidence by design
- Registry data model
- Outcomes dictionary
- Governance approach
- Publication / evidence pathway
Why it matters
Routine data is an evidence asset, not exhaust
Every clinical encounter, device interaction and patient-reported response generates data. Left in silos, it answers nothing; structured deliberately, it becomes the foundation of a credible evidence base. A registry is the structure that turns that flow into something you can analyse, defend and publish — a defined cohort, a consistent set of measures, and a record of how each value was captured. The difference between a spreadsheet and a registry is intent: a registry is designed before the first record is entered, so the question it will answer is decided in advance rather than reverse-engineered from whatever happens to be collected.
Real-world evidence (RWE) is the analysis that sits on top of that foundation. Where a randomised trial answers whether an intervention can work under controlled conditions, RWE asks whether it does work in routine practice — across the messy variation of real caseloads, comorbidities and care pathways. Done rigorously, it complements trial data; done carelessly, it invites the bias and confounding that make assessors discount the result. Our work begins from the discipline that separates the two. For a fuller primer, see our explainer on what real-world evidence is, and the wider healthcare data and analytics service it sits within.
How we work
From question to evidence pathway
- Frame the question. We start with the decision the evidence must support — a publication, a value dossier, a post-market commitment — and work backwards to the data needed to answer it credibly.
- Design the data model. We specify the minimum dataset, the entities and relationships, and mapping to recognised terminologies such as SNOMED CT so the registry interoperates rather than becoming a private dialect.
- Build the outcomes dictionary. Each endpoint is defined unambiguously — what it measures, how and when it is captured, and how it is derived — so two analysts reach the same figure from the same data.
- Settle governance and lawful basis. We agree the information-governance route, the lawful basis under UK GDPR, and the safeguards for special-category data before collection begins, working within your existing arrangements.
- Pre-specify the analysis. Cohort, comparators, handling of missing data and confounders are documented up front, so the method withstands scrutiny from peer reviewers and market-access assessors alike.
- Generate and report. We deliver the analysis as a publishable output or an evidence package, with a plan for ongoing reporting as the dataset matures.
Who this is for
Teams that need evidence to count
This service suits medical-device and digital-health companies preparing market-access or post-market evidence, clinical teams establishing a disease or procedure registry, and service leads who need outcomes data that will survive external review. If your product makes a clinical claim, the registry is where that claim is tested against reality.
Device & digital-health teams
Build the real-world evidence dossiers that underpin market access and post-market surveillance commitments.
Clinical registries
Stand up a disease or procedure registry with a defensible data model and outcomes dictionary from day one.
Service & commissioning leads
Evidence outcomes over time with data that holds up to scrutiny from funders and assessors.
Governance is not an afterthought here. Every registry we design names its lawful basis and its safeguards explicitly — see how we approach data protection and security.
Answers
Frequently asked questions
Can you design a clinical registry?
Yes — we design the data model, outcomes dictionary and governance, and a pathway to generate real-world evidence that can support publication and market access.
How is data governance handled?
We work to UK GDPR and your information-governance arrangements, with clear lawful bases and safeguards for any special-category data.
How do you avoid bias in real-world data?
We pre-specify the analysis, define the cohort and comparators up front, and document confounding, missingness and selection effects. The aim is a transparent method a reviewer or assessor can scrutinise, not a result chosen after the fact.
Can a registry use routine NHS data?
Often, yes — with the right lawful basis and information-governance approvals. We help define the minimum dataset, mapping to recognised coding such as SNOMED CT, and the safeguards needed for special-category data.
What outputs can the evidence support?
A well-designed registry can feed peer-reviewed publications, value dossiers for market access, post-market surveillance, and ongoing outcomes reporting to the teams using your product or service.
Build your evidence base
Tell us your product or service and we'll design the registry.