Patient experience
Search, schedule, prepare and follow up in one accessible, mobile-first place.
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Platform & data
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Practical intelligence embedded where work happens — with evaluation, governance and human control built in.
Regulated sectors
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Transformation stories
Case studies structured around challenge, intervention and evidence — not slogans.
Case study · Healthcare
Patient access was spread across phone lines and disconnected systems. We redesigned it as one self-service journey supported by a connected operational core.
Build → Adopt → Measure
DeliveredThe challenge
Patients relied heavily on phone-based appointment requests while clinical and administrative teams worked across disconnected systems that never shared a view of the same person.
The approach
Experience work and integration work ran as one stream, so the journey we designed was the journey the systems could actually support.
Map patient and staff needs across the whole access path.
Connect the visible experience to the backstage work.
Define experience and technical architecture together.
Connect identity, scheduling and records.
Measure real usage and keep improving.
The solution
A single journey for patients, standard interoperability underneath, and visibility for the teams running the service.
Search, schedule, prepare and follow up in one accessible, mobile-first place.
Identity, scheduling and record exchange using established HL7 and FHIR patterns.
Adoption, service volume and exception handling made visible to the teams accountable for them.
Outcomes
We agree the measures during discovery and instrument them before go-live, so the change can be assessed rather than asserted.
Appointment booking, preparation and follow-up moved from phone queues into a journey patients complete themselves, at the time that suits them.
Identity, scheduling and clinical records exchange through standard HL7 and FHIR interfaces, so teams see the same person regardless of channel.
Adoption, service volume and exceptions surface on a live view the operational teams own, replacing manual reporting after the fact.
How we measure
Every engagement defines its measures before the first release, instruments them at launch, and reviews them with the client after real usage — not before it.