Amid an array of new complications, historic models for elective care will need to be reimagined and patient safety remain a guiding principle, argues Karina Malhotra
The NHS has had to adapt very rapidly while navigating the challenges of covid-19 and, as the service now considers how best to resume elective care, much more will have to be adapted or indeed fundamentally reimagined.
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Waiting lists for elective care, already growing before covid hit, have lengthened as routine activity has inevitably taken a back seat to dealing with the pandemic. While referrals have fallen across all aspects of elective care – including, notably, cancer – they are likely to ultimately return at an even higher rate than before. Patient safety must remain paramount, despite these new complications.
So how best to resume elective care in the aftermath of the first peak? Certainly, demand and capacity planning will be crucial to manage the pace of recovery – indeed, NHS England and Improvement are rightly promoting the need for this work right now. Visibility of how many new patients are being referred, how many patients are waiting and their acuity will be key to enabling such planning.
Reimagining concepts
A complexity here, however, is that traditional models used for capacity and demand planning are no longer appropriate. Demand as a concept is going to need reimagining to ensure that patient safety is the guiding principle when managing elective care with the limited resources available. It is no longer about the patients waiting on known lists or indeed how long they have waited. Rather, demand considerations will need to be finessed to include individual patient clinical prioritisations, the backlog of deferred patients and a potential buildup of delayed referrals from primary care.
Digital tools will be essential if this expertise is to be harnessed effectively and at pace to provide reliable models
The definition of capacity is likely to need rethinking too. Historically, modelling has been about determining the number of additional slots that would be needed to meet demand. The “slots” described in such models have traditionally been associated with physical estate and clinically staffed hours jointly. In a post-covid world, it will be necessary to understand much more explicitly if capacity shortfalls are estate related, staff related or both.
In some areas capacity may be increasingly shared between sites, with local and system-wide waiting lists and activity plans being devised. There is also a need to develop ways of modelling virtual capacity – telephone and video consultations, for instance – and of indirect capacity such as clinical reviews of waiting lists which might lead to patients being discharged or prioritisation decisions being revised.
A further challenge is that, until now, all demand and capacity planning models have been based on historical data. Such models are demonstrably no longer fit for purpose. The current situation is completely unprecedented and so, as the move towards something resembling normal begins, demand and capacity scenario planning will be absolutely key in managing elective care. It will be necessary to model a range of possible scenarios, including a second wave necessitating another suspension of elective activity. To do that effectively will require expertise in harnessing both data and operational intelligence.
Digital tools will be essential if this expertise is to be harnessed effectively and at pace to provide reliable models. Platforms which allow a collaborative operational approach and data sharing among teams across pathways, organisations or care systems are important here.
Data accuracy
The quality of data itself then is also crucial to success, but currently this is not a given. Getting accurate data on referral to treatment times involves multiple individuals and multiple pieces of software and so provides multiple opportunities for errors to be made. This complexity means it is understandable that inaccuracies creep in, but this presents a significant challenge if decisions are taken based on this inaccurate information.
It is important, therefore, to check in with local operational and information teams to assess and review the data quality on waiting lists, as well as commence demand and capacity scenario modelling. These teams will require effective recovery tools, skills and capacity to conduct a more holistic recovery of elective care.
Since this is an unprecedented scenario, there is currently no established best practice to rely upon. Individual trusts will need to find the approaches that work best internally and within their own integrated care systems. Each system should look to develop a plan which is embedded in an accurate and evolving understanding of the capacity and demand locally – while keeping patient safety at the forefront. At Acumentice, we use our operational expertise to support the creation of these recovery plans by ensuring data accuracy, scenario planning, digital tools and dashboards for NHS partners.
What is beyond doubt is that, as elective care recommences, all trusts need to be prepared for multiple scenarios, including future peaks and the potential impact on patient safety. It is only through expert use of data and digital tools that this will be achieved.
Karina Malhotra is founder and director of Acumentice, a consultancy working with NHS organisations to deliver improvement on elective waits. She previously held a number of senior leadership roles within the NHS.
