COVID-19 has caused major changes and disruption to the usual working of healthcare organisations. Some planned changes have been accelerated, including remote consultations and some of the planned changes have been at the expense of other services, such as cancelling surgery to allow anaesthetists to work in new critical care areas. Although globally the number of COVID cases are rising again, in the UK cases are declining as are COVID admissions to hospital and we are able to start cautiously returning our focus to the care of other conditions. But the presence of the virus means that the system will still need some of the exceptional design features to protect patients and staff. It is likely that healthcare facilities will continue to need to have three physically separate care streams (COVID-19; non-COVID emergencies and clean elective care) with separate staffing for some significant length of time.
The required diversion of resources for COVID-19 patients and the need to protect vulnerable patients has led to a backlog of work. To develop plans to reduce this backlog, the NHS will need to quantify and characterise it.
This blog series will look at how that planning and implementation can be supported by digital approaches, most of which are commonly used in other sectors. We will explore various aspects and how digital approaches can help resolve the challenges: Understanding how we match capacity and demand in an agile manner can facilitate more rapid recovery and make our systems more resilient to future insults. We believe there are five elements to this which will be studied in more detail in subsequent blogs: understanding the data; understanding the true demand, understand the human capacity, understanding the physical capacity and then manging the waiting lists.
Understanding the data
A lot of NHS data is produced for performance management and then used for service management. The former is usually a single figure (or target) designed to reflect the efficiency of the system. The latter needs a more detailed understanding of the multiple steps in a process with quantitative and qualitive elements. Our blog on bed occupancy will illustrate how understanding and interpreting data is vital to restoring healthcare. The infamous figure of 85% occupancy is often misinterpreted. If you never exceed 85% then you are wasting capacity. If you have higher occupancy but never exceed 100% then you will have good flow. We highlight the use of predictive analytics and modelling that can help organisations achieve good flow and higher utilisation (occupancy) rates.
Understanding true demand
Most systems are quantifying their backlog by looking at the waiting list but is this too simplistic. The waiting list is simply patients already identified as needing an intervention. it does not show the true demand for several reasons. Patients are not presenting to their GP because of more difficult access, perception of risk and perception that hospitals will not be able to undertake their treatment. Those referring patients to hospital and those adding individuals on to waiting lists have changed their thresholds as they try to control the workload. A waiting list is a static measure, and the demand is varying more than historical data would suggest because of our unique circumstances at present. As waiting lists get longer, they may also contain patients who have died or no longer want/require the procedure. Calculating the backlog is complex and the formula below is still too simplistic. in a future blog we will suggest a new approach that allows live monitoring of true demand, that avoids over-simplicity but is easy to use for operational management.
Understanding the human capacity
Individuals working in healthcare have been recognised for their response to the pandemic with personal sacrifice to help others. But many of the changes are not sustainable.
whilst we need to address the backlog of work, staff also need time to recover and adapt to new working. some staff will not be able to return, some will retire, some will seek less intense employment. The many volunteers returning to the NHS may not be able or wish to continue. Is now the opportunity for true workforce transformation? Can digital systems help with recruitment and retention? Can e-rostering systems improve the work-life balance. Can we make it simple for staff to work across organisations with shared HR systems or digital passports? In the future blog in this area we will explore how HR transformation, including digital approaches, could help the NHS to approach some of these questions.
Understanding the physical capacity
How do we optimise the use of facilities as they become available (e.g. critical care capacity returning to use as theatres and their recovery areas) and as restrictions change (e.g. distancing, isolation) to best suit the changing health needs of a local population?
How do we used digital logistics systems to ensure the supply change can keep abreast of the rapidly changing demands as we increase elective surgery but also as we flex between specialties and locations?
Physical capacity constraint is a major part of a complex interplay of service capacity that also involves how we manage the service and how we deploy staff to maximally use the capacity. Can we create increased capacity by expanding the success of remote monitoring and remote consultation achieved during the pandemic? Not only do we need to have bigger and better facilities, but we also need smarter capacity and adaptability in the system to accommodate the changing health needs of the population the system serves. What if we did something radical? What if we designed whole modular healthcare ecosystems from the ground up and used AI digital systems to increase the agility of responsiveness?
Managing the waiting list
How do we ensure that our resources are aligned and focussed correctly to maximise the reductions in waiting lists? Could digital waiting lists enable more flexibility and more patient choice? Existing digital list programming is used by supermarket delivery vans to make sure the most efficient route is picked, whilst prioritising particular deliveries; we could use similar systems to plan the most efficient use of facilities, staff and equipment whilst prioritising clinically high-risk patients. Giving more control to the user, via customer relationship management systems as has already occurred with many online services, enabling the patient to balance their priorities. The digital waiting list could safely reduce waiting lists through workload distribution and resource management whilst promoting patient choice. Later in the series we will demonstrate how a digital waiting list can help reduce healthcare waiting lists.
Healthcare has adopted many modern technologies during the pandemic. The restoration of normal healthcare is another opportunity for transformational improvement using digital technologies. we are already undertaking this in other sectors and believe that we could support a digitally enabled restoration of healthcare. More detail will follow over the next few weeks as the series develops.
I would love to hear your views on smarter digital approaches to restoring our healthcare systems after the pandemic.
Matthew is Chief Clinical Officer at Capgemini. He spent most of his career working in the NHS as an emergency physician and was the National Clinical Director for Urgent and Emergency Care.