Case Study

Proactive Winter Bed Planning at an Acute NHS Trust

Overview

Winter pressures represent one of the most predictable and yet consistently damaging challenges in acute NHS operations. Every year, Trusts face surging demand, constrained bed capacity, and escalating ambulance handover delays — and every year, the response is largely reactive. Not because operational teams lack the will to plan ahead, but because the modelling capability required to produce genuinely useful forecasts has historically been out of reach. Running the kind of high-fidelity, scenario-based simulation that makes proactive winter planning possible requires serious computational resource — the kind that standard FDP tenancy environments are not designed to deliver. For one large acute NHS Trust, this had meant winter planning was still largely driven by last year's experience and operational instinct rather than data-driven scenario modelling. VE3 deployed FDP+ to change that — introducing a Compute Arbitration Architecture that brought high-performance simulation capability directly into the Trust's FDP environment, without displacing any of the operational data and applications that clinical teams depended on every day.

Challenges

Broad Understanding of Winter Pressures, Insufficient Precision

Operational planning teams understood the shape of their winter pressures but could not model them with enough precision or speed to inform proactive resource decisions before conditions deteriorated.

Multiple Interacting Variables Driving Bed Occupancy

Winter capacity is not driven by a single factor. Admission rates, length of stay, discharge rates, community capacity, staffing levels, and emergency department flow all interact simultaneously — making accurate modelling inherently complex.

High-Performance Compute Required for Meaningful Simulation

Modelling the interactions across thousands of plausible scenarios requires complex simulation algorithms running on high-performance infrastructure — capability that was not available within the existing analytical environment.

Previous Modelling Was Slow and Disconnected from Live Data

Earlier attempts at winter planning produced outputs that arrived too late to act on. Models were not connected to live operational data, and the gap between insight and action made them difficult to trust or operationalise.

Scenario Parameters Were Fixed, Not Adjustable on Demand

Teams had no ability to stress-test different conditions in real time. Scenario parameters were static, preventing planners from exploring alternative assumptions or rapidly modelling the impact of changing circumstances.

Results Were Siloed, Creating Delay at the Point It Mattered Most

Outputs lived in separate analytical tools and required manual steps to translate insight into action. This friction was most damaging precisely when speed was critical — during fast-moving winter pressure events.

The Approach

Compute Arbitration — The Right Workload on the Right Infrastructure

  • A deliberate Foundry + Azure Compute Arbitration Architecture implemented — routing workloads to the infrastructure best suited to them
  • Foundry retained as the intelligence and application layer — Ontology, decision logic, and all operational dashboards running within Foundry with Compute Credits fully preserved
  • Azure configured as dedicated high-performance compute for simulation workloads — Azure Batch resources running digital twin models of hospital flow
  • Live clinical dashboards and operational applications unaffected throughout the entire modelling process

Building the Digital Twin

  • Digital twin model of the Trust's operational environment built on the Canonical Data Model within Foundry
  • Core Objects — Patient, Location (Ward/Bed), Clinical Event — used as the foundation, ensuring simulation is anchored in the same data structures powering operational applications
  • Scenario parameters designed to cover the realistic range of winter conditions — flu admission rate increases of 10%, 20%, and 30%; community discharge capacity reductions of 15% and 25%; varying staffing levels across nursing and medical rotas
  • Each scenario combination run as a separate simulation in Azure, producing occupancy forecasts, escalation trigger points, and recommended resource positions

Secure Bridge — Connecting Simulation to Decision

  • Secure bridge mechanism connecting Azure simulation environment to Foundry
  • Raw data passed securely from Foundry to Azure for processing
  • Only high-value outputs — occupancy forecasts, risk scores, recommended escalation thresholds — returned to Foundry upon completion
  • Scenario outputs surfaced in Workshop alongside live operational data — no tool-switching, no manual data transfer, no disconnection between forecast and live operational picture
  • Operational and executive teams able to compare forecasts, stress-test assumptions, and commit to resource allocation decisions entirely within Foundry

Proactive Monitoring & Alerting

  • Real-time monitoring of key winter pressure indicators configured within Foundry
  • Pipeline latency thresholds, bed state staleness checks, and admission rate anomaly detection all configured as automated alerts
  • Operational teams notified of emerging pressure before it became a crisis — not after

The Outcome

The deployment shifted the Trust's approach to winter planning from reactive crisis management to genuinely proactive, data-driven operational leadership.

  • Winter surge scenarios modelled and ready weeks ahead of peak demand — giving operational and executive teams time to act on forecasts rather than react to conditions
  • Hundreds of scenario combinations available on demand — varying admission rates, discharge capacity, and staffing simultaneously to cover the realistic range of winter conditions
  • Reduced corridor care through earlier escalation and resource pre-positioning based on modelled forecasts rather than lagging operational indicators
  • Improved ambulance handover performance through better-predicted peak admission windows and pre-planned surge responses
  • Foundry Compute Credits fully preserved throughout the modelling cycle — live clinical dashboards and operational applications unaffected
  • Executive and operational teams working from one environment — scenario outputs and live operational data in a single, governed Foundry workspace
  • Faster decision-making — the time from scenario request to actionable output reduced significantly compared to previous planning processes
  • Sustained capability — the digital twin model and compute arbitration architecture remain in place year-round, available for ongoing scenario analysis and future planning cycles

The Compute Arbitration Architecture VE3 deployed is not a generic cloud integration — it is a deliberate engineering pattern developed specifically for the constraints and requirements of NHS Foundry tenants. VE3's position as the national FDP Solution Assurance provider means this architecture has been designed with full knowledge of the platform's operational boundaries and governance requirements, ensuring the Azure bridge meets NHS data security and sovereignty standards from the ground up. Ready to move your winter planning from reactive to proactive?

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