Date published: 6th February 2018

95% of patients attending an A&E department should be treated, discharged or admitted within 4 hours.

It has been widely pulicised that this winter has been amongst the worst on record for the sheer volume of patients attending A&E with most Trusts failing to meet that target, prompting the unprecedented steps of blanket postponement of non-urgent surgery, on out-patient appointments and an apology from the Prime Minister, Theresa May and the Health Secretary, Jeremy Hunt.

However, it has come to light that data reporting between hospital Trusts on A&E waiting times is misleading.

NHS Improvement wrote to hospital Trusts in October telling the Trusts that their A&E statistics include nearby Walk-In Centres even if unconnected to the hospital Trust.

This came to light when The UK Statistics Authority complained to health officials about how their data was being recorded.

Certain Trusts who have included such data look to be performing better in their A&E departments such as:

Patients seen etc. within 4 hour target

A&E performance without including additional activity

  • United Lincolnshire Hospitals NHS Trust - 69.50%
  • Kettering General Hospital NHS Foundation Trust - 73.40%
  • Norfolk and Norwich University Hospitals NHS Foundation Trust - 69.00%
  • Portsmouth Hospitals NHS Trust - 69.70%

A&E performance when extra activity from local walk-in-centres added:

  • United Lincolnshire Hospitals NHS Trust - 82.00%
  • Kettering General Hospital NHS Foundation Trust - 85.50%
  • Norfolk and Norwich University Hospitals NHS Foundation Trust - 80.60%
  • Portsmouth Hospitals NHS Trust - 78.70%

NHS Improvement says that the letter was actually designed to address variations between data recording between Trusts and ensure consistency.

To confuse matters further, an NHS mapping exercise showed that the data was unaltered whether or not walk-in-centres were included or not. But as can be seen from above, that finding is questionable. Such misleading data looks good politically but could backfire on the ground where patients think its okay to go to their local A&E as the wait won’t be too bad.

Ed Humpherson, Director General for Regulation at the UK Statistics Authority pointed out to health officials that the impact of adding such additional data needs to be clearer: “This will support better decision making and avoid users reaching misleading conclusions”.

Of course it makes sense for patients to be re-directed away from A&E where this is appropriate so that A&E departments can concentrate on those in need of emergency care, but this needs to be reflected in the data.

When data is misleading, how does this affect staff morale when this clearly belies the reality? False impressions could also prevent the necessary changes to front-line services with less political pressure from the public.