Healthcare AI visualization for NHS teams

Plan for tomorrow, today.

Harris Vision builds patient admission prediction dashboards that help NHS trusts spot pressure before it lands on the board. What if your team could see tomorrow’s demand at 6 a.m., not after the emergency department has already filled up?

Daily forecasts by 6 a.m.
GDPR and NHS Digital aligned
Bed and staffing insight in one view
NHS operations team reviewing a predictive admissions dashboard on a large screen in a bright hospital command room

Live 72-hour demand preview

Hovering over each hour reveals projected admissions, confidence bands, and the staffing impact for the next shift. Static on mobile. Clear on every device.

92% forecast accuracy by 6 a.m.
15% average reduction in bed waiting time
HL7 FHIR built for NHS data standards
24 hours to a clinician-led demo
Why NHS teams act sooner

What if you could see tomorrow’s patient volume today?

Our dashboards combine historical admissions, GP referrals, 111 calls, weather patterns, and flu surveillance into one operational forecast. That means less guesswork, fewer bottlenecks, and fewer late-night firefights.

Built for pressure points

Need clearer bed management, earlier discharge planning, or better staffing calls? The dashboard surfaces the pressure before it becomes visible on the ward.

Updated every morning

Forecasts refresh by 6 a.m. so site managers start with a current view, not yesterday’s story. Clean. Fast. Actionable.

Made for governance

Compliance, auditability, and role-based access are baked in. Because a beautiful dashboard is only useful if people can trust it.

How the model works

How we forecast patient flow

Why rely on one signal when the whole picture is available? We merge operational and public-health data, engineer useful features, train the model, then present the result in a dashboard teams can actually use.

1

Data ingestion

Admission records, GP referrals, NHS 111 calls, weather, flu surveillance, and seasonal patterns are pulled into one pipeline. That wider context matters, doesn't it?

2

Feature engineering

We translate raw signals into meaningful patterns, from weekday effects to weather-linked spikes.

3

Forecast delivery

Gradient-boosted trees produce the demand outlook, with confidence intervals shown alongside the forecast.

Accuracy snapshot

Mean absolute error Low and stable
MAPE reliability 92%
Confidence bands help teams see where to act early and where to hold steady.

UK healthcare data

Designed around NHS datasets, local demand patterns, and operational realities.

Confidence intervals

Planned capacity is shown with a range, not a single guess.

Controlled access

Role-based views keep clinicians, managers, and executives focused.

NHS-ready dashboard features

A bento view of the pressure points

Two larger panels carry the story. Three supporting cards show the details. Why bury the essentials under noise?

Hospital bed occupancy dashboard on a monitor beside a nurse station showing ward capacity and discharge timing

Bed occupancy tracker

See available beds, occupancy trends, and predicted strain across wards. The view is immediate, clean, and built for daily rounds.

Discharge prediction panel in a hospital office with coloured risk bands and timeline cards

Discharge prediction

Spot which patients are likely to move sooner, so flow is easier to plan.

Theatre utilisation

Match theatre schedules to admissions pressure and release hidden capacity.

Staffing recommendations

Shift suggestions align with the forecast, not gut feel.

Role-based access

Clinicians, bed managers, and leaders each get the right level of detail.

Screenshot-led previews

Hover to reveal what the live dashboard feels like before deployment.

Scenario simulator

Test different scenarios

What happens if staffing changes, or elective activity shifts, or one more ward opens? The simulator makes the trade-offs visible before the day starts.

The sliders are simple on purpose. Can your team read the result at a glance?

Predicted wait time impact

Current state versus the recommended position

-22%
expected wait-time reduction
18%
improvement with optimal beds
+6
hours earlier escalation warning
1 view
for staffing and flow decisions
Case study: East Midlands NHS Trust

Reducing wait times when winter pressure hits

The trust was dealing with 12-hour A&E waits and frequent escalation calls. Could a single operational view calm that chaos? The answer was a forecast-led dashboard, built around a 7-day view and clear staffing recommendations.

18%
reduction in average waiting time
22%
fewer escalations
7 days
of forecast visibility

The nicest part? Staff stopped chasing the day and started steering it.

Before and after

Busy hospital waiting room with standing patients and crowded seating during peak demand

Before: queues building, decisions lagging.

Hospital command centre with a predictive dashboard, colour coded risk bands, and a focused management team

After: demand visible, actions prioritised.

  • Integrated with NHS data standards
  • Forecasts delivered by 6 a.m.
  • Designed for real operational conversations
Clinician endorsement

One clear testimonial, no fluff

East Midlands NHS Trust

“Knowing our predicted admissions by 6 a.m. has transformed how we start the day. We’re no longer reacting, we’re planning.”

Dr Adis Imoru, Medical Director

Book a 30-minute demo

Arrange an NHS-focused demo

Tell us your trust name, your role, and the operational headache you want to solve. We’ll prepare a tailored example before the call, so the conversation stays practical.

Contact our team
Contact details

Talk to an analytics specialist

Want the fastest route to a working dashboard? Start here.

Healthcare analytics consultant presenting a demo dashboard on a laptop in a modern meeting room
Book early if you want winter-pressure planning before the next rota cycle.
Frequently asked questions

Questions NHS teams usually ask

Straight answers. No jargon. Because the fastest way to judge a dashboard is to ask the awkward questions first.

Daily forecasts are updated by 6 a.m. and have averaged 92% accuracy in pilot settings. We show the confidence band as well, so teams can judge how much to act on each hour.

Yes. The platform is designed for HL7 FHIR and MESH workflows, with access controls and data handling aligned to NHS expectations.

Clinicians, bed managers, site teams, and executives each get a tailored view. One platform. Different decisions.