[ Case study ]
Therapists prescribed exercises as printed sheets; patients lost them, adherence was invisible, and progress reviews were argued from memory rather than evidence.
CLIENT a six-clinic physiotherapy group — FOCUS Prescribe from a governed library
Representative examplesEvery case study in this library is an illustrative composite of the kind of engagement we deliver — written to show our method and standards, not to name clients.
Six physiotherapy clinics across a metro area, owned by two senior clinicians and staffed by therapists who see a patient every half hour. Programs were printed: an exercise sheet with hand-drawn sets, reps, and a photocopied diagram, going home in a folder. The group's clinical lead reviews everything patients receive, reception does double duty as print shop, and the clinics run fully booked most days, which means nobody has time to design a new process — it has to fit the gaps between appointments.
Therapists prescribed exercises as printed sheets; patients lost them, adherence was invisible, and progress reviews were argued from memory rather than evidence.
We proposed an iOS app built around a governed exercise library: the clinical lead approves every video and parameter set before it exists in the app, and prescribing becomes selection plus dosage rather than authoring. Patients install from a clinic QR code with their program already attached — no account creation in the waiting room. Sessions are logged in two taps and surface on a dashboard the therapist reviews before each appointment, so the progress conversation runs on evidence instead of memory.
Just as important is what we ruled out, and why:
The app draws from a curated exercise library with clinician-approved videos and parameters, so prescribing is selection plus dosage — never authoring.
Sessions are logged with two taps and synced to a dashboard the therapist reviews before each appointment, making the progress conversation evidence-based.
Large targets, offline caching of the current program, and no account creation in-clinic — patients install from a clinic QR code and their program is already attached.
Delivered by the experience pod — mobile engineer + designer over 10 weeks, with working increments reviewed with the client every week.
Obstacle
Filming the library stalled: therapists shot exercise videos on their phones between patients, the clinical lead rejected most batches for inconsistent framing, and the library ran three weeks behind the build.
Handled: We wrote a one-page shot list — camera angle, patient position, plain background — and ran two filming afternoons where the clinical lead approved takes on the spot; the library filled in a fortnight.
Obstacle
The first onboarding flow assumed patients knew how to find, install, and open an app; usability sessions with older patients showed several stalling at the home-screen step.
Handled: We rebuilt onboarding around the clinic QR code — scan, and the program is already attached — then rehearsed the flow with the least confident patients until none needed help.
The headline: every new patient onboarded to the app over the pilot quarter, with adherence visible to the treating therapist — Printed sheets → prescribed app programs, read from Clinic's own adherence dashboard. A second check: logged home-session frequency vs paper-program estimates at 2.4×.
The eight minutes between appointments stopped being a print run. Prescribing happens inside the gap between patients — the therapist builds the program while the patient dresses down — and the review opens with the adherence dashboard instead of a question about memory. Reviews became shorter and less adversarial because the evidence was on the screen. The clinical lead finally sees prescribing patterns across all six clinics, so weaker exercise choices get corrected once, centrally. Patients' home programs survive losing the folder, and reception's mornings no longer begin at the printer.
The result was read from Clinic's own adherence dashboard against the pre-engagement baseline over the stated window, with a guardrail check on logged home-session frequency vs paper-program estimates. Where platform-reported numbers and business outcomes differ, this record says which layer it is quoting.
What we would do differently
We would involve the least tech-confident patients in usability sessions from the first build, not the pilot — the first onboarding flow assumed more iOS fluency than many patients had.
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