The NHS faces a defining challenge: delivering on ambitious elective recovery targets while confronting historic workforce shortages and demand pressures. Meeting the 18-week Referral to Treatment (RTT) standard — 65% of patients treated within 18 weeks by March 2026, rising to 92% by 2029 — will require more than incremental change. It demands a system-wide understanding of what needs to happen, when, and where.

At Whole Systems Partnership (WSP), we help health and care leaders move beyond dashboards and performance reports. Our modelling and simulation tools reveal the dynamics that sit beneath the numbers, enabling strategic choices about how to recover performance sustainably across trusts, specialties and regions.

The challenge: a growing performance gap

Over the past year, RTT performance has improved slightly — around 2% year-on-year, with 250,000 fewer people waiting over 18 weeks. Yet referral rates have remained stable and total elective activity has not risen. Temporary list clearances and operational drives can only take performance so far. Without structural change — increased capacity or reduced referral demand — further improvement will stall.

Behind the headline figures lies a strategic dilemma. Health systems have no shortage of data, but much of it is backward-looking. Dashboards and reports describe what has happened, not what needs to happen next. Board papers across integrated care systems (ICSs) show the same pattern: detailed analytics but limited forecasting of future performance or demand.

Why business-as-usual planning is no longer enough

Traditional approaches to planning often rely on operational estimates — “how much more can we do with existing resources?” This can produce targets, but not strategies. It assumes a linear world, where performance improves simply by doing more.

The reality is more complex. Waiting-list recovery is a dynamic process influenced by feedback loops between demand, capacity, and patient behaviour. Without understanding these relationships, leaders risk over-promising and under-delivering. That is where modelling and simulation come in.

From hindsight to foresight

Forward-looking modelling transforms static data into a living system view. It allows boards to explore critical “what-if” questions:

What will performance look like if nothing changes?
How much additional activity is needed to meet national targets?
What would happen if referral demand fell by 2–5% through upstream interventions?
Which trusts or specialties would require the greatest uplift to hit 18-week or 52-week recovery milestones?

Using provider data submitted to NHS England, our Elective Recovery Model forecasts referral volumes, waiting lists, and activity trajectories for each trust. It then dynamically calculates the additional capacity required to reach target performance — whether at system, trust, or specialty level.

This makes the abstract tangible. For example, achieving national RTT targets could require a 24% uplift in elective activity system-wide over the recovery period. At the trust level, that varies: some will need modest growth, while others face increases of 40% or more. Understanding this distribution is essential for realistic workforce and capacity planning.

Here we can see 18 week performance, with the ‘do-nothing’ baseline in blue and the recovery trajectory in red.

Modelling interventions, not just effort

Recovery is not only about increasing throughput. Strategic interventions — such as referral management, pathway redesign, or better primary–secondary coordination — can also shift the curve. Our models simulate how such measures alter future waiting-list trajectories.

For example, a 3% reduction in referral rates through targeted demand management can have the same effect on performance as a significant uplift in surgical activity. By quantifying these relationships, the model helps systems balance investment between activity growth and demand reduction.

This evidence allows boards to discuss not only how much to do, but what kind of change will yield sustainable results.

Informing strategy across levels

The Elective Recovery Model supports decision-making at multiple levels:

National and regional: forecasting performance trajectories to assess whether the system is on track to meet the 65% and 92% targets.
System (ICS): identifying which trusts require the largest proportional increases in activity, and which specialities are most constrained.
Trust and specialty: calculating the precise percentage uplift required by service line to meet local goals.

By linking these layers, the model creates a shared view of the problem and a common language for strategic planning.

Again, with do-nothing in blue and recovery in red, the require additional activity can be modelled that is required to take the trust to 92% 18 week performance.

The path forward

The NHS is under no illusion about the scale of the challenge. Current elective recovery targets demand both operational rigour and strategic insight. Forward-looking modelling and integrated workforce planning can transform the conversation from reactive management to proactive system design.

Health leaders who embrace these tools gain the foresight to allocate resources intelligently, balance short-term pressures with long-term sustainability, and build resilient systems capable of delivering care closer to patients’ needs.

At Whole Systems Partnership, our mission is to help organisations move from what happened to what happens next — and from isolated action to whole-system collaboration.

From Data to Decisions: How Whole-System Modelling Can Power NHS Elective Recovery