For healthcare professionals only

Views & Reviews Acute Perspective

David Oliver: Stop blaming patients for emergency visits

BMJ 2015; 351 doi: (Published 13 November 2015) Cite this as: BMJ 2015;351:h6119

Yes, stop blaming patients, but start by identifying the root causes of problems

David Oliver is quite right that it is wrong to blame patients for going to A&E. But he misses an opportunity to correctly identify the major causes of A&E crowding. It is also critical that we correctly identify the root causes of poor A&E performance so effective acting can be taken to improve the current 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 confusing 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.

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 ( ) and concluded that the most significant problem was poor flow through the hospital's beds. This has been well know 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. While true in extremis, 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 get 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.

Competing interests: No competing interests

15 November 2015
stephen black
data scientist
biggleswade, bedfordshire