As healthcare buildings are asked to do more, under more extreme weather conditions and with less margin for error, Colin Rees argues the solution lies in using digital tools to narrow the gap between design intent and operational reality

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Colin Rees associate director at IES

Recent years have seen the conditions in which healthcare buildings operate evolve rapidly. The Met Office says 2025 was provisionally the UK’s warmest and sunniest year on record, while the UK Health Security Agency estimated over 1,300 heat-associated deaths occurred across four heat episodes in England during the summer of 2024. At the same time, adaptation reporting for the NHS is explicit that climate change is creating growing risks for both service delivery and healthcare infrastructure.

For the people who plan, fund, design, build and run healthcare facilities, this isn’t just peripheral detail, it fundamentally changes the brief. Hospitals and clinics have always been complex operations, but now they face higher peak temperatures and more volatile weather on top of evolving clinical requirements, constrained budgets and inefficient energy systems. In that context, “good building performance” now needs to mean more than a set of well-intentioned design-stage outputs. The focus must be on safe, stable operation in use – even on those days when conditions are at their worst.

While every healthcare building is different, the sector will recognise the wider pattern. A facility can meet requirements on paper, but struggles once it is in use – especially when it comes to overheating, indoor air quality and basic day-to-day resilience. When that happens, the impacts are immediate: staff working in uncomfortable spaces; estates teams firefighting; and extra cost, energy waste and disruption landing after the building is already occupied. For new builds, if risks are not spotted early in the process and managed all the way through to handover, projects are more likely to face late redesign, hurried fixes and value-engineering decisions made under pressure.

Overheating

Overheating is perhaps the most visible example because it is driven by peaks rather than averages. A building may look acceptable against annual metrics yet still tip into failure during a small number of hot days that happen to coincide with heavy operational pressure. That matters because the UK parliament Climate Change Committee has been clear that overheating in buildings is a serious and growing risk, and one of the highest priorities for effective adaptation in the UK.

Healthcare feels that risk more acutely because the tolerance for drift is lower: when a ward, treatment room or staff area becomes hard to keep within safe limits, the response is rarely neat. Set-points get overridden, temporary cooling appears, plant runs harder than intended, and energy use rises. The result is operational complexity at precisely the moment the building is under strain, as well as higher carbon and cost from reactive running.

The truth is that overheating is often the result of many small, understandable decisions that accumulate across the project lifecycle, from a glazing ratio that inches up to shading or solar control that is quietly downgraded. None of those choices looks catastrophic in isolation, but, together, they can push a healthcare building from “generally fine” to “hard to manage” during weather extremes.

Dynamic thermal simulation

This is where a shift in approach – treating stress as a normal operating condition from the early stages – pays off. When used as a decision aid rather than a compliance artefact, dynamic thermal simulation is one of the most effective tools available.

In simple terms, it models how a building behaves hour by hour (rather than steady state), so teams can see how form, fabric, glazing, shading, ventilation, internal heat gains, operating schedules and control strategies interact when temperatures rise. That helps answer questions that matter to delivery teams not just modellers – for example, which zones will fail first, and what combination of measures will actually keep critical spaces within safe limits. It also supports testing against future weather files rather than relying solely on historic baselines, something that is critical for assets that will be in service for decades to come.

The value comes from spotting problems early: if you can see where a building will struggle while it is still on the drawing board, you can fix this with informed design choices, such as tweaking glazing or changing the ventilation approach. If the same problems show up late, options are limited. Then, fixes tend to be rushed and expensive, and often come with downsides – whether that is higher energy use, more kit to maintain, or more day-to-day complexity for estates teams.

That being said, good design intent does not guarantee good performance in use. Delivery and handover are crucial points in enabling reality to match the plans. Healthcare buildings only amplify this because they are dense, highly serviced, and full of interfaces – meaning those in charge of projects should treat performance assurance as construction risk management.

Clear, measurable outcomes

None of this is about blame, it is about the incentives and pressures that sit on projects, and the need to protect performance when time and costs tighten. The most effective lever is clarity on outcomes and finding a practical way to verify them. If performance is loosely defined, it is easy to trade away under pressure. If outcomes are clear and measurable, they stay visible.

This means being more deliberate about measurement and verification of whether a building is performing as intended. It works best when considered right from the start, not tacked on after practical completion. Define what will be measured and why; plan the metering and data access properly so the information is usable by estates teams; and agree how performance will be normalised, so comparisons remain fair as occupancy and clinical activity evolve. And, critically, resource seasonal commissioning and tuning, with time in programme and clear responsibilities, so the building is supported as it settles into real use.

Turning digital assets into digital twins

This is also where the sector can make more productive use of digital assets it has already created. Many healthcare building projects generate models and datasets during design and delivery, then park them at handover. Carried forward and calibrated against measured data, those assets can become an operational digital twin – a living tool that helps estates teams spot drift, diagnose issues, test operational changes before making them live, and prioritise retrofit measures based on quantified impact. Used in that way, a digital twin is a practical way to preserve operational intent and reduce firefighting.

The bottom line is that healthcare buildings are being asked to do more, under tougher conditions, with less margin for error. A credible response is to tighten the link between design intent and operational reality – stress-testing early, protecting performance through construction, commissioning and tuning properly, and verifying outcomes in use. Do that, and the benefits are tangible – from fewer overheated spaces to lower running costs and carbon emissions – because systems operate as intended rather than in permanent correction mode.

In a constrained capital environment, it can be tempting to treat performance assurance as optional, but in healthcare, it is better understood as insurance against avoidable instability when the building is under stress. With climate and public-health data exposing the human cost of evolving environments, it is difficult to argue that extremes are someone else’s problem or something to plan for later. The operational environment is already changing – the job now is to deliver healthcare buildings that can cope with it.