Health platforms carry a burden most software does not: the data is sensitive, the people it concerns often did not choose to become software users, and the rules about consent and retention are specific and enforced.
The Performance Centre handles exactly that shape of problem outside the clinical setting. It holds records about children, gathered by volunteers and coaches, with consent capture, retention rules, role-based visibility and audit trails built into the platform rather than bolted on once someone asked.
Insights
The safest record is the one you did not collect
Most data protection effort goes on securing information that never needed to exist. Minimisation is the cheapest control available and the least used.
Read the articleConsent is not a checkbox at sign-up
A single agreement at registration is easy to build and rarely means what it claims. Real consent is granular, revocable and has to survive a live system.
Read the articleA retention rule that needs remembering is not a rule
Most retention policies are documents. The data they describe is still there, because deletion was left to a person with more urgent work.
Read the article
How we support changemakers in health and life sciences
Set up and run teams
We work inside your teams rather than at arm's length from them, with people who understand that in this sector the data model is a governance decision as much as a technical one.
Launch new products
We build to production standards from the first sprint, with data protection considered at design time rather than assessed after the fact.
Discover new propositions and customer experiences
We research with clinicians, carers and patients rather than about them, and we prototype cheaply enough that being wrong early costs very little.
How we strengthen your team
Consent, retention and access, designed in
We have built platforms handling data about children, with consent capture, retention rules, role-based access and audit trails from the outset. Retrofitting any of that is far harder than building it in.
Data minimisation as a design principle
The safest record is the one you did not collect. We start by questioning what genuinely needs storing, which usually shortens the compliance conversation considerably.
AI with human oversight
Where models contribute to a decision, the contributing factors are logged and explainable, and a person stays in the loop. We have built exactly this for safety-critical scoring.
Subject access and erasure that actually work
Requests answered from the system rather than by a manual hunt: everything held about a person exportable in a documented format, with erasure that cascades properly through related records, files and free text, and a log of what was removed and when.
Visibility that follows the role
Least privilege by default, with each role seeing only the fields its job needs — the person handling billing never sees medical notes. Read access is logged as well as changes, because unauthorised viewing leaves no trace in a change log.
Analytics without spreading identity
Reporting and model training run on pseudonymised or aggregated data, with re-identification keys held separately and access to them controlled and logged. Most analytics needs the pattern rather than the person, and asking which is required usually shortens the compliance conversation.
White paper
Handling sensitive personal data in consumer-facing platforms
Consent capture, retention rules, subject access, role-based visibility and audit trails, with particular attention to platforms used by children and their parents.
Our work
Let’s talk
Have a problem you need to solve or an idea you want to explore? Let’s talk about how we can make it happen.