Table, not tiles.
- One row per room, read in one fixation
- One screen, not six
- One click to live video
Before: a page per room, a separate alerts console, video in a third tool.
Case study 01Healthcare AI
Ambient AI that watches every hospital room, so nurses and sitters see only what deserves them.
01The moment
At 2:40 AM a post-surgical patient gets out of bed alone. Confused from pain medication, he will not press the call button.
PatientNurseOut of bed, no call
Nothing about that moment is unusual.
02The problem
An AI that sees everything drowns a nurse in alerts, unless the interface decides what deserves her attention. That was the brief.
The brain learns to filter them out, and filters out the real one too.
Industry context, not results of this deployment. Figures as summarised by Nurse.org from published research.
03The approach
Tier colours and event examples from the product’s semantic palette. Icons are the production webfont.
04The flow
The nurse station and the phone in her pocket show the same three states.
AMS-M2 sensor: an event, not footage.
Console and phone, same alert.
One tap stops the escalation clock.
Live video and two-way talk.
Documentation is a by-product.
05Decisions that held
Before: a page per room, a separate alerts console, video in a third tool.
06The interface
Swipe the wall sideways
The live sitter wall plays itself. Click anything to take over.
The Ambient Monitoring console plays itself. Click anything to take over.
The Command Center plays itself. Click anything to take over.
Virtual Care plays itself. Click anything to take over.
The mobile app plays itself. Click anything to take over.
The real product, three moments
The tabs above are the product redrawn as vector with demo data. Numbered marks point to the design decisions. Drill-downs, rules, calls and Drop In are illustrative behaviour. The strip below the tabs, and the hero, are real product screenshots with demo data.
07The system
A hallway sign at four metres and a phone in a corridor each got a step on one scale, never their own rules.
Try it: hover a row.
The most valuable thing I left behind was not a screen. It was the rule that a nurse moving between four products should never have to ask what a colour means.
08Leadership
Set quality benchmarks, ran UX review, mentored designers to own modules end to end.
Each defines “done” differently. I held one definition across all four.
Also art-directed the product films and animated walkthroughs used to sell the platform.
The recurring argument was less.
Engineering wants more detections, more data, more alerts. Alarm fatigue is what happens when nobody wins that argument.
09A correction
I filed the AMS-H1 bedside unit as hardware. It is a complete patient app: thirteen screens for elderly users in assisted living and home care.
How I had been thinking
What the patient app needed
Try it: press Call a nurse.
A toast is correct by convention and wrong in practice. A frightened patient needs a whole screen: “Evelyn has been called to your room.”
I was categorising by device, not by user. Correcting that changed how I audit my own scope.
10Outcome
care.ai now sits inside Stryker’s Smart Care business.
Who runs on it, as published
Customer programmes as published by those organisations and Stryker. Context for the scale the design had to survive, not a claim of individual credit.
What I took from it
Good design is knowing what to leave out.
Sources: Nurse.org, care.ai announcement, Stryker completion, Stryker on Henry Ford. Product screens are redrawn as vector with demo data, except the hero and the real-product strip, which are screenshots with demo data; the live wall, drill-downs and Drop In are illustrative behaviour, not telemetry. WCAG 2.1 AA targeted, demos keyboard operable, motion off under reduced-motion.