commvita
Connected care platform
Clinical Research

How privacy-safe clinical research works — from cohort to publication, without data leaving safe hands

A demo reference for the research roles and the exact commvita controls that carry a study from lawful basis through the Design → Publication → Archival lifecycle — anonymised, federated, and provable, so the answers travel while the records stay put.

Live vs demonstrated: Live — real, API-backed platform logic (wired end-to-end today) Demonstrated — representative control surface with seeded data / illustrative UI mock-up

The roles

Research on the live clinical record is built as a secondary use: separate purpose, separate lawful basis, separate people. The participant keeps their rights and their opt-out; the sponsor is accountable; the team only ever touches minimised, governed data.

Research participant

The data subject — the patient whose record contributes to a cohort

Never re-keyed into research; their record is anonymised or pseudonymised first. They keep every right (Art.15 access, rectify, object) and can opt out — the National Data Opt-Out removes their confidential data from this secondary use.

Where in commvita National Data Opt-Out enforced in /ig-spine · Art.15 SAR & "query this access" · Patient Portal research-participation view.

Sponsor / data controller

The provider or research sponsor — NHS trust · university · ICB

Decides why and how the study runs. Holds the lawful basis (Art.6(1)(e) + Art.9(2)(j) with Art.89 safeguards), the HRA/IRAS approval, the DPIA and the DSA / contract register. Signs off each project before an extract can be taken.

Where in commvita /clinical-studies Study Library & Data Governance · DPIA + DSA register · project approval packs.

Research team & analyst

The people building cohorts and running the analysis

Work only on minimised data at the approved tier — never the raw record, never the token vault. Build cohorts with a no-code filter builder; every extract they take is logged with an Extract ID + file hash to the ledger.

Where in commvita /clinical-studies Cohort Builder · Anonymisation & Token Vault · Extract Ledger.

commvita governance roles

Separation of duties across the research lifecycle

Six scoped roles keep the controls apart: data_custodian · ig_reviewer · project_approver · analyst · auditor · break_glass. Re-identification is possible for break_glass only, and every touch is auditable.

Where in commvita Role gates across /clinical-studies (/studies/) — custodian holds the vault, approver signs off, auditor reads the ledger.

A Lawful basis & approvals — before a single record is read

Research is not care. It needs its own basis and its own paperwork, and in commvita every link must be satisfied before an extract can be taken.

1

Fix the lawful basis for research

Public-body research runs on UK GDPR Art.6(1)(e) public task plus the special-category condition Art.9(2)(j) scientific research, together with the mandatory Art.89 safeguards (technical & organisational measures, data minimisation) — the basis that makes lawful research on health data possible.

UK GDPR Art.6(1)(e) · 9(2)(j) · 89DPA 2018
2

Secure HRA / IRAS research IG approval

The study is registered and approved through HRA / IRAS research information-governance review before recruitment opens. The approval reference is held against the study record — no approval, no extract.

/clinical-studies · Study LibraryHRA / IRAS
3

Complete a DPIA and register the DSA / contract

A Data Protection Impact Assessment is required for this high-risk processing, and any onward sharing is bound by a Data Sharing Agreement in the contract register. The Data Governance tab holds the project approval pack, DPIA refs and re-identification risk register together.

/clinical-studies · Data GovernanceDPIA · DSA / contract register
4

Enforce the National Data Opt-Out

This is a secondary use, so the National Data Opt-Out is applied — an opted-out patient's confidential data is removed from the cohort. The same enforcement point governs Caldicott-reviewed secondary access in the IG Spine.

/ig-spine · National Data Opt-OutCaldicott 8
5

Apply ICO anonymisation guidance

The controls follow the ICO anonymisation / pseudonymisation guidance and NHS re-identification risk controls: minimise, generalise, and separate identifiers from the analysis dataset before anyone runs a query.

ICO anonymisation guidancere-identification risk register

B The study lifecycle

A commvita study moves through six governed stages — each is a status in the Study Library, and a study cannot skip a gate.

1

Design

Define the research question, endpoints, cohort criteria and the anonymisation tier the study will run at. Lawful basis and DPIA are attached here.

/clinical-studies
2

Registration

The study is registered with its HRA / IRAS approval and lawful basis recorded — the project-approval workflow gates progress.

/clinical-studies
3

Recruitment

The cohort is assembled from the live record with a no-code filter builder, opt-outs removed, at the approved minimisation tier.

/clinical-studies
4

Analysis

Analysts work only on the minimised extract; each extract is stamped with an Extract ID + file hash to the immutable ledger.

/clinical-studies
5

Publication

Outputs are aggregate and disclosure-controlled; the Evidence Pack assembles the IG artefacts that support the results.

/clinical-studies
6

Archival

The study is closed and retained per its retention schedule — provenance, extracts and governance pack preserved for audit.

/clinical-studies

C How the data is protected — three tiers of anonymisation

The study picks the least-identifiable tier that answers its question. Identifiers are separated from analysis data before anyone runs a query.

① Pseudonymisedinternal, DPIA + HRA ② k-Anonymousk≥5, broader / cross-org ③ Synthetic + DPε=1.0, external, no DSA

Pseudonymised — internal, break-glass reversible

Direct identifiers are replaced with stable tokens. Re-identification is possible by authorised break-glass only. Suitable for approved internal research that carries a DPIA and HRA approval.

/clinical-studies · Anonymisationbreak_glass

k-Anonymous (k≥5)

Quasi-identifiers are generalised so each record is indistinguishable from at least k−1 others (k≥5). Suitable for broader internal analysis and approved cross-organisational datasets.

k-Anonymous (k≥5)

Synthetic + Differential Privacy (ε=1.0)

A statistically representative synthetic dataset with ε-differential privacy (ε=1.0) — a mathematical privacy guarantee. Safe for external sharing without a DSA requirement.

/synthetic-dataε=1.0

Token-vault separation

The reverse mapping lives in a separate key-management system with its own audit trail — analysts cannot access reverse mappings. Only the data_custodian / break_glass path can touch the vault, and every use is logged.

/clinical-studies · Token Vaultseparate KMS

Re-identification risk register & minimisation

A live re-identification risk register tracks residual disclosure risk per dataset; data minimisation (Art.89) keeps each extract to the fields the study actually needs — nothing more.

/clinical-studies · Data GovernanceUK GDPR Art.89

D Federated by design — count without moving rows

Feasibility and cross-site questions are answered where the data lives. The counts come back; the records never leave the source.

Aggregate-only feasibility counts (k≥5)

Cohort Discovery runs a no-code criteria query across the federated network and returns an aggregate network count only, with small-number suppression (k≥5) — counts below five show as <5 per ICO anonymisation guidance. 0 rows leave the source.

/cohort-discoveryk≥5 suppression

Cross-site queries without data leaving source

Federated Query executes SQL/FHIR across independent sites and aggregates results without any data leaving its source; disclosure risk is surfaced on the result. Federated-by-design — the safe default for multi-site research.

/federated-querydisclosure risk
Immutable, intelligent audit — nothing leaves untraceably. Every extract is written to an append-only Extract Ledger carrying an Extract ID + SHA-256 file hash: a leaked file can be traced straight back to the row that produced it, and the ledger cannot be modified after creation. Every touch of the source record rides the WORM hash-chained audit that the server re-verifies on read — a broken chain shows a tamper banner. Nothing is extracted, shared or re-identified without a hashed, tamper-evident record of who, when and why.

Where it lives in commvita

Participantcontributes anonymised → Sponsor / controllerapproves & governs → Research team
Research conceptModuleRouteModel / APIStandard
Study lifecycle & approvals (Design→Archival)Clinical Studies/clinical-studies/studies/ · project approval · DPIA / DSA refsHRA/IRAS · UK GDPR Art.6(1)(e)/9(2)(j)/89
Cohort buildingCohort Builder · Population Health/clinical-studies · /population-healthno-code filter builder · opt-out removalICO anonymisation guidance
Anonymisation & token vaultClinical Studies — Anonymisation/clinical-studies3 tiers · vault in separate KMS · break_glassICO · re-identification risk controls
Extract ledger (immutable provenance)Clinical Studies — Extract Ledger/clinical-studiesExtract ID · file_hash (SHA-256) · append-onlyUK GDPR Art.5(2) accountability
Federated discovery (0 rows leave)Cohort Discovery · Federated Query/cohort-discovery · /federated-queryaggregate-only · k≥5 suppressionGDPR Art.89 · TriNetX-style federation
Synthetic data (ε-DP, external-safe)Synthetic Data Generation/synthetic-datasynthetic + differential privacy (ε=1.0)ICO anonymisation guidance
External requestsResearch Data Portal/research-portal/studies/data-requests · data catalogueHRA/IRAS · DSA / contract register
IG basis (opt-out · Caldicott · WORM)Confidential-IG Spine/ig-spineNational Data Opt-Out · WORM hash-chainCaldicott 8 · DSPT 2024/25
The principle: research runs on a separate lawful basis, on minimised data at the least-identifiable tier, federated so rows never move, and provable end-to-end — every cohort, extract and share carries a hashed, tamper-evident record. The evidence travels; the patient's record stays in safe hands.
UK GDPR Art.6(1)(e) / 9(2)(j) / 89Data Protection Act 2018HRA / IRAS research IG ICO anonymisation guidanceNational Data Opt-OutNon-SaMD research control surface
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