Simulation technology takes the risk out of decision-making to reveal the ideas, technologies, changes in pathways and processes that will improve healthcare, writes Tom Stephenson
There’s widespread agreement that the development of new technologies will be a critical part of solving the huge healthcare challenges that we face today. We are already seeing how artificial intelligence, machine learning, IoT, robotics and nanotechnology are improving healthcare provision. The connection between technology and improved healthcare feels closer than ever – raising hopes that we might be on the verge of discovering some ‘silver bullet’ to solve challenges like the much-reported waiting list backlog.
Unfortunately, there is no silver bullet solution to such a complex situation. The biggest and most immediate impact will come from altering our approach to decision-making and identifying every single incremental gain to be made. And to do this, we can look to support from a specific type of technology – simulation.
As someone who has been working with healthcare organisations around the world for the last decade, delivering simulation projects that examine everything from staffing rotas to operational management challenges and capital investments, I’ve seen the transformative benefits of this technology in healthcare process improvement.
It’s a method of digitally recreating a system and then running simulations of various scenarios – asking ‘what if? questions to understand what’s happening and how it will be impacted by changing or reconfiguring the system.
Safe digital testing ground
Think of simulation as a safe, digital testing ground that demonstrates exactly what optimal looks like and how to achieve it, making it the best way to de-risk decision-making. Rather than a silver bullet, simulation offers a guiding light to reveal the ideas, technologies, changes in pathways and processes that can lead us towards improved healthcare, one decision at a time.
There is no doubt that we are in crisis and in need of ideas. Research from The Health Foundation now suggests a worst-case scenario where the elective care waiting list could peak at 8.4 million by the end of 2024.
Its ‘better-case’ scenario not only requires an end to strikes by healthcare staff, but also a growth in the rate of hospital activity by a third to reach 10.4%. Under this scenario the waiting list could fall to below 7.2 million by the end of 2024 – the same level it reached in January 2023 when the Prime Minister made his pledge to bring waiting lists down.
Plan more effectively
I recently caught up with a long-term collaborator, Dr John Boulton, a national director for NHS Quality Improvement and Patient Safety, to discuss what could be done to help the backlog. Dr Boulton has worked on quality improvement methodologies for many years, spanning work in Public Health Wales, NHS Sheffield, in the Middle East and at the Institute for Healthcare Improvement in Massachusetts. We have worked together on a number of different simulation projects.
His first experience of simulation was when he was a rheumatologist with huge, unexplained backlogs in his clinic. “By building a simulation I could understand the referral waves coming in, how many non-attendances there would be, or cancellations, how it all fit together and what outputs it would produce,” he said.
“I think there’s a huge opportunity to use simulation in this way to understand how healthcare systems actually behave and the dynamics that cause that behaviour. We know that simulation has the power to help us plan more effectively, building in all the variations that are experienced in the real world. This way we can understand the impact of things such as the patients not attending, or the clinic being cancelled. It gives us a much better opportunity to plan forward, and that’s something we need to get better at.”
Simulation has been increasingly adopted by healthcare strategists and planners. A lot of my work has been in helping teams within hospital departments use simulations to gather evidence around ideas for improving or introducing new processes. By providing a clear view of all potential impacts within a dynamic system, it’s possible to start making decisions to cut off the problem before it starts. This can apply to identifying bottlenecks and ways to clear them, as well as testing new configurations for the flow of patients or how resources can be optimised. With everything getting simulated, as opposed to real- world testing, recommendations are arrived at quickly, accurately and at relatively low cost.
Wider adoption of simulation in healthcare offers a way to unlock more effective problem-solving, which will in turn help improve productivity. And it gets even more interesting with the development of ‘digital twins’, which are taking simulations to the next level and linking them with real-time data. This creates tools for even more dynamic operational decision making that can be used in a continuous loop to maximise process performance.
Simulation-powered digital twins
Digital twins are fast becoming the planning method of choice for organisations across industrial sectors. Increasingly, they are also being developed to map healthcare pathways and optimise in-hospital processes.
They live alongside the real-world system and provide a testing ground in which to run simulations so that every single decision can be tried and tested to find the optimal course in a cost-effective and timely way. Digital twins are able to capture the thinking of the most experienced hospital planner and then make recommendations accessible to anyone that needs to make a quick decision on where to allocate resources based on up to the minute data. They not only account for the variations that occur, but also take a wider view of the knock-on impact to the whole system.
Dr Boulton pointed out that we can predict a lot of flow challenges and harm events from people as soon as they appear at the front door of an emergency department. “Let’s say that we have a validated simulation built of the department and we are putting in data about new patient arrivals on a real time basis,” he explained. “We could be giving a heads up to the rest of the hospital and potentially the wider system to say that we’ve had a bad day in the emergency department. You know that in 24 hours there is going to be a difficult challenge in the rest of the hospital and potentially wider.
“Likewise, if we can feed data in from primary care, then we will know that in the next few days that is going to have an impact as it feeds its way into the hospital. There is huge potential to develop digital twins in this way,” he said.
He added that some experienced NHS planners are already adopting a similar approach, but on a manual basis. “If we look at the organisations that are really high performing and have high reliability, while they might not be using digital twins yet, they are using manual applications to do something very similar to build that situational awareness and know what’s happening now, where do we think it’s going to impact next, and what are the things that we need to do to alleviate it.
“Imagine putting all of that into a simulation instead, where it will do all of the thinking rapidly, automatically, and with even more accuracy. We will be able to give a heads up of what will happen in the next hour, four hours, eight hours, 48 hours and then plan accordingly.”
Lean into the technology
Simulation can paint the full picture for us, present unlimited different scenarios and outcomes, and generate the evidence for moving ahead with the best-case scenario.
Of course, more funding and staffing support are needed too, but even if they become available it will be necessary to make sure that resources are allocated in the most optimal way. The technology is already available to make operational and process decisions; now is the time to lean into it. First, to turn the tide on the NHS backlog, but more fundamentally as the most proactive way we have to plan for whatever might be coming down the track.
Tom Stephenson is director of Strategic Partnerships – Healthcare, Simul8.