I was going to write another rant on the evidence-free stupidity of much of the current political and media commentary on the current NHS A&E crisis. Then I realised I'd written most of it before during a previous A&E crisis where the same evidence-free solutions were floated by commentators. It seems that our media and political leaders have learned little and still don't bother to check whether their solutions are compatible with the evidence.
So here is a bullet point summary of the things that we know to be true (from analysis of detailed public performance data and patient-level HES data) followed by an edited version of what I wrote in a BMJ response in 2015:
- It isn't an A&E crisis: that is just the symptom. It is a whole hospital crisis caused by a failure to manage effective, timely flow through beds.
- The volume of patients turning up at A&E is irrelevant: it isn't about "pressure" on the input side; it is about blockages on the flow from A&E to beds.
- More resources to A&E won't fix the problem: only solutions that improve flow across the whole hospital will help.
So, if you are still blaming GPs, patients with trivial problems, immigrants etc. you don't understand the problem and your solutions will just waste NHS resources and will deliver no actual benefit.
Yes, stop blaming patients, but start by identifying the root causes of problems
It is really worrying that so many system leaders think that the problem is caused because too many people are coming to A&E and that the solution is to encourage them to go somewhere else. The idea is superficially attractive as an explanation for problems but is clearly wrong for several reasons. Moreover there are no proven ways to drive patients elsewhere.
The data about A&E attendances in major A&E departments (type 1, 24hr, full service A&Es) shows a steady low rate of attendance growth over the last 20 years with no sudden surges (many people confusingly include the numbers from non-24hr minor injury units and walk-in centres which have expanded greatly over this time period without any notable effect on the numbers turning up at major A&Es). Staff numbers have grown faster than attendance.
More significantly, if we analyse the variation in attendance numbers and performance, there is no relationship at all. Higher attendance does not drive poorer performance. This is one of the clearest messages from the data.
Monitor recently published a very comprehensive review of the possible reasons for poor A&E performance ( https://www.gov.uk/government/uploads/system/uploads/attachment_data/fil... ) and concluded that the most significant problem was poor flow through the hospital's beds. This has been well known to experts for some time. In hospitals with poor internal coordination (which is many of them) this problem isn't within the span of control of the A&E department, so blaming the department for poor performance seems particularly unfair.
Why do leaders fail to identify this root cause or tackle it effectively? This seems to be a consequence of a failure to train medics or many managers in the science of how operational processes work. An effective understanding of how processes involving queues work is a significant part of the science Operational Research. And the results are often surprisingly at variance with a naive intuition.
To a naive observer untrained in operational research, it feels like the only reason why a queue is long is because the flow into the queue is high. "Too many people have turned up." The science recognises something more subtle. The speed that a queue is processed is usually far more important than the number of people joining it. And, importantly, the length of the queue will grow very quickly if the processing speed gets slightly slower even if the numbers joining the queue don't change at all. In A&E departments this means the crowding and the overall delay for patients is highly sensitive to the speed of the whole process (of which treatment and assessment are not the bottlenecks). So, if it takes a long time to find a bed when a patient needs it (which we know is a very common and significant problem) the number of patients waiting can grow very quickly indeed even if no more patients than normal arrive in the department. If the department becomes crowded, even the patients who don't need a bed get treated more slowly, compounding the problem and making the queue grow even more.
So a naive manager identifies that the department is crowded and assumes that is because too many people have turned up when the real problem is that there is a bottleneck in the process that means patients can't be moved quickly from the A&E department. The manager might argue more staff are required to cope with the extra demand, but, if the problem is finding a bed, more staff will do nothing to make the discharges faster and actually won't help the crowding problem at all.
The consequence of a naive understanding of how queues work and a failure to analyse the data about the key causes of A&E crowding is a large amount of effort and money spent on the wrong problems. Adding staff in A&E won't magic up more free beds; diverting patients (even if we knew any way to do it) won't actually reduce the crowding in A&E.
So let's stop blaming patients. But, more importantly, let's analyse the data to identify the real causes of A&E delays and let's train NHS medics and managers in how operational processes work so they know where to focus their improvement efforts instead of naively wasting time, effort, and money on the wrong problems.
