Monthly Archives: September 2020

When Waiting is Not Enough

Healthcare is emerging from the immediate crisis response of COVID-19 into a hugely uncertain environment. One of the very few things of which we can be sure is significantly longer waiting times for elective procedures.

The Health Foundation recently published a report drawn from pre-COVID data,[1] which starkly portrayed the challenges around the 18 weeks Referral to Treatment target. The report estimated that the NHS needed to treat an additional 500,000 patients per year for the next four years to restore delivery of the target. Using data from NHS England following the first month of COVID-19 induced elective shutdown, Dr Rob Findlay noted a jump, both in the number of patients waiting over 52 weeks, and the average wait time for patients, which rose to 6 months.[2] These figures are likely to increase further in coming months. The article also noted that very few long-wait patients were treated. Longer wait patients should be de facto low clinical urgency, as it is this that has made them appropriate to wait.

There are two significant decision-making points for the treatment of patients on waiting lists. Clinical urgency, which of course affects those near the start of their waiting time, and being in imminent danger of breaching a waiting time target, which necessarily affects those towards the end. Between these decision-making points at the start and end of the waiting list lie a huge volume of patients with little categorisation or prioritisation.

Herein lies a significant future challenge: as waiting times increase and a growing number of patients breach waiting time targets, how do you ensure that limited elective capacity is targeted towards those with greatest clinical need?

If NHS England and NHS Improvement do not relax waiting time restrictions, maximum wait times will continue to be an important decision-making point. This incentivises providers to make a trade-off and treat longer waiting, but clinically less urgent, patients over short waiting, but clinically more urgent, ones. This would be a difficult position to justify ordinarily but in a time of likely constrained resource, the policy is likely to do far more harm than good.

It is crucially important to use need as the basis for prioritising which patients to treat. A recent literature review described some of the efforts made around the start of the millennium to develop a more systematic and transparent approach to prioritisation based on need. This approach developed from the Western Canada Waiting List Project [3] and the New Zealand Priority Criteria Project.[4] These approaches were rigorously reviewed through a range of academic articles and evaluated well, showing both transparency and consistency of decision making and prioritisation. Importantly, they also carried strong public support when reviewed with focus groups.

These ‘point-count’ systems work by creating a scoring chart for each clinical condition, such as cataract surgery, major joint replacement, coronary bypass graft. However, they have also been successfully used and evaluated for topics such as the use of Magnetic Resonance Imaging (MRI) and children’s mental health. The scoring grid is unique to each clinical condition and developed through consensus discussion with clinicians to balance a range of clinical and social factors. The objective is to prioritise patients for treatment who will gain the most substantial benefit from intervention.

‘Point-count’ systems have translated successfully into several healthcare settings but not to the NHS. Often these types of changes are put in to the ‘too difficult’ category as the resource required to implement them is seen to be greater than the benefit gained. However, we are moving to a different paradigm post COVID-19 where integrated care systems are more accountable to their population and a more objective and transparent decision-making process is desirable.

Think too of the benefits of a shared language of waiting lists. We should not forget that many non-clinical staff are involved in the booking and scheduling of elective patients. A common currency in which objective comparisons can be made on the likely benefit of surgery or intervention across clinical indications and specialties is highly appealing.

One of the most keenly-debated elements of the development of these ‘point-count’ systems was what factors should be considered as part of the scoring criteria. Repeatedly the idea of including some reflection of how long a patient had waited was considered, and strongly rejected. Instead a measure of ‘potential for disease progression’ was included to ensure those, for instance, waiting for a joint replacement procedure, were not constantly usurped by patients with a more acute presentation. However, it guards against the current system of those waiting longest receiving priority at the potential expense of another who would derive greater clinical benefit.

So, as a policy directive there is a clear indication – the maintenance of the current maximum wait times will prioritise many clinically less urgent patients over more urgent cases. It remains to be seen whether the evidence base is substantial enough, and whether there is sufficient appetite within the NHS to revisit some of these clinical prioritisation approaches, but their use should be considered and their implementation would make a fascinating piece of research in the coming years.

Paul Bird, Head of Programme Delivery (Engagement), Richard Lilford, ARC WM Director

With thanks to Prof. Tim Hofer (University of Michigan) for discussion and input.


  1. Charlesworth A, Watt T, Gardner T. Returning NHS waiting times to 18 weeks for routine treatment. The Health Foundation. 2020.
  2. Findlay R. Average waiting time for NHS operations hits six months thanks to covid. Health Serv J. 2020.
  3. Noseworthy TW, McGurran JJ, Hadorn DC, et al. Waiting for scheduled services in Canada: development of priority-setting scoring system. J Eval Clin Pract. 2003; 9(1): 23-31.
  4. Hadorn DC, Holmes AC. The New Zealand priority criteria project. Part 1: Overview. BMJ. 1997; 314: 131.

Recognising the rising tide in service delivery and health systems research

With rising demands and finite resources, health systems worldwide are under constant financial pressure. The US has been at the extreme end of high spending, with health expenditure consisting of 17% of its GDP in 2017 – compared with 9.8% for the UK and 8.7% for the average of the OECD countries (OECD).[1] Therefore, the imperative of containing healthcare cost is mounting in the US. Under the Affordable Care Act (ACA), alternative payment models (often known as value-based payments) have been widely introduced to replace the fee-for-service model.

A recent article in JAMA highlighted a paradox,[2] in which an apparent plateau in overall healthcare expenditure (at around 18% of US GDP) is contrasted with lack of significant success reported in individual evaluations of these alternative payment models. Why has health spending as a proportion of GDP plateaued when the interventions to reduce spending have been ineffective in doing so? The authors ruled out the explanation that the growth in GDP has outpaced the growth of health expenditures as the latter seems to be genuinely flattening. So how can this discrepancy be reconciled?

The authors offered three explanations:

  1. Anticipation of ACA-driven expansion of alternative payment models may have induced changes in the psychology and practice of clinicians and health care organisations, leading to curbs on spending irrespective of the introduction of alternative payment models.
  2. Primed by the above change in mindset, clinicians and health care organisations may have been influenced by their peers and emulate their practice. This would cause a wider spread of the change beyond the institutions where the alternative payment modelled were first introduced and evaluated (e.g. from within the Medicaid system to those covered by commercial insurers).
  3. Simultaneous introduction of a large number of alternative models in different places may have led to contamination of control groups in individual evaluations, where the control group chosen in one evaluation may be subject to the introduction of another alternative payment model.

Taken in the round, these explanations suggest a secular trend of system-wide changes (in this case cost containment), which may take various forms and be achieved through different means, but which are triggered by heightened awareness of the same issue and shared social pressure to tackle it across the board – what we have described as the ‘rising tide phenomenon’.[3] The phenomenon is by no mean a rare occurrence in health services and systems research and so is well worth considering when a null finding is observed in a controlled study. The corollary is that when there is a rising tide, null findings do not disprove the potential effectiveness of the intervention being evaluated. A more nuanced interpretation taking into account the secular trend is required, as the authors of the aforementioned paper did.

Yen-Fu Chen, Associate Professor; Richard Lilford, ARC WM Director


  1. Organisation for Economic Co-operation and Development. Health. 2020. Available at:
  2. Navathe AS, Boyle CW, Emanuel EJ. Alternative Payment Models—Victims of Their Own Success? JAMA. 2020; 324(3):237-8.
  3. Chen Y-F, Hemming K, Stevens AJ, Lilford RJ. Secular trends and evaluation of complex interventions: the rising tide phenomenon. BMJ Qual Saf. 2016; 25(5): 303-10.