Long waiting lists, chaotic clinics and stretched staff are usually explained the same way: there is too much demand and not enough capacity. It is a familiar conclusion, and for many services it feels like the only one available.

But as NHS consultant surgeon and independent healthcare systems engineer Simon Dodds explains on a recent episode of HLTH Chat, many of these problems are not caused by a lack of resource at all. They are caused by the way the system has been designed, or more accurately, by the fact that it was never really designed in the first place.

Why Healthcare Is Reactive by Default

One of the central messages from the discussion is the difference between how clinicians are trained to think and how designers are trained to think.

Medicine is inherently reactive. Clinicians are taught to wait for someone to become unwell and then intervene. Design is inherently proactive. It starts with a blank page, a clear purpose, and a process built to meet that purpose.

Simon trained in both, taking a second degree in computer science alongside his medical studies, and he argues that healthcare tends to apply its reactive way of thinking to everything, including the way services themselves are run. Processes are rarely designed from scratch. They evolve, they react to the latest crisis, and the underlying flaws remain.

What Healthcare Systems Engineering Actually Means

Engineering, in this context, is simply another word for design.

Most people associate engineering with bridges, aircraft and production lines. Healthcare is what is known as a sociotechnical system, which means people are an integral part of the design rather than an obstacle to it. A production line does not need to be consulted. A clinic team does.

That distinction matters in practice. Handing a finished solution to a team rarely works, because without involvement there is no ownership. The people doing the work understand the process better than any outsider ever will, and they need to be part of the design conversation from the very start.

Systems engineering also places the emphasis on the relationships between the parts of a system rather than the parts themselves. In healthcare, those relationships are often the weakest point. Clinicians, operational managers, finance teams and digital teams may each perform their own role well, but without a shared language and a shared design, patients end up falling through the gaps and doing the navigating themselves.

Fragmentation, Queues and Patient Safety

Safety is what engineers call an emergent property. It is a product of how the whole system works together, which means it has to be designed in rather than bolted on after something goes wrong.

Other industries, aviation in particular, understand this well. Healthcare has tended to approach safety reactively, responding to failures rather than preventing them by design.

Waiting is part of that picture. A queue is not simply an inconvenience. A patient waiting six or seven hours in an emergency department has a condition that is progressing while they wait, so the delay itself carries clinical risk. Remove the cause of the queue and the service becomes safer as well as faster.

Simon is clear that this is not a trade-off. Safety, flow, quality and affordability tend to improve together when the underlying design improves. In his own surgical practice, he questioned why a surgical site infection rate of around six per cent was treated as acceptable simply because it matched published averages. Asking why the figure was not zero led to a structured investigation and a reduction of more than 85 per cent, at no additional cost, and the improvement has been sustained because the design changed.

Data, Information and the Questions Worth Asking

Healthcare is not short of data. If anything, most services are drowning in it.

The more useful distinction is between data and information. Data on its own means very little. Data placed in context becomes information, and information is what builds the understanding needed to diagnose a problem and focus a redesign. That means a small amount of carefully selected data will often tell you far more than a large volume of it.

There are gaps, however, and outcomes are the clearest one. The NHS measures activity well: operations performed, patients seen, appointments delivered. Outcomes are measured far less consistently, and as Simon points out, the absence of complaints is not the same thing as quality.

How that information is presented matters just as much. Rather than red, amber and green performance tables, he uses what he calls a vitals chart, borrowed directly from the vital signs monitor at a patient’s bedside. It is the pattern across several measures over time, not any single line, that reveals what is actually causing a problem. Presented that way, the diagnosis tends to become obvious.

Digital Twins and Testing Change Before You Make It

One of the disciplines that healthcare rarely borrows from engineering is simulation. In most design work, a change is tested before it is implemented, so you know it will work before it goes live.

A digital twin takes this further by running a simulation alongside the real system, drawing on live data, and predicting what will happen next if nothing changes.

Simon describes using this approach in a chemotherapy service where the chaos was severe enough to be dangerous, and where the root cause was not visible from simply observing the process. Building a digital twin allowed different hypotheses to be tested, and the cause turned out to be a single scheduling policy. A one day test of change removed the chaos, reverting to the old policy brought it straight back, and the team implemented the new approach within a week. The service went on to see around 15 per cent more patients in the same time, with the same staff, in the same space, and some of the staff who had left because of the stress came back.

The change cost nothing.

The Barrier of Disbelief

Perhaps the most striking theme of the conversation is how simple many of these fixes turn out to be.

Simon shares a recent example from his own service, where post-pandemic backlogs meant patients were waiting up to a year for an appointment even though his clinics were under booked. The diagnosis was an internal policy that delayed routine referrals by up to 36 weeks. Reclassifying those patients allowed them to be booked at six weeks instead, and the spare capacity already in the system drained the backlog exactly as predicted. His referral to treatment time is now around nine weeks against a national target of 18.

What holds services back, in his experience, is rarely money, technology or intent. It is what he calls the barrier of disbelief: the assumption that if a fix were really that simple, someone would have done it already. Once a team tries it and sees it work in their own hands, that barrier disappears and the momentum builds quickly.

His closing message is one of optimism. The skills involved are a genuine discipline and they do require training, but they can be learned, and they can be learned far more quickly than most people assume.

Listen to the Full Conversation

This article only scratches the surface of the insights shared by Simon Dodds on HLTH Chat.

The full episode explores:

• How proactive design differs from traditional quality improvement
• Why fragmentation and silos create risk for patients
• The 6M Design framework and the discipline behind it
• The emotional journey teams go through during change
• Using digital twins and simulation as diagnostic tools
• What a self healing healthcare system would look like
• The skills healthcare leaders will need over the next decade

For healthcare professionals, providers and anyone interested in how services can be improved without additional cost, it is a fascinating discussion that offers both clinical experience and practical insight.