I’ve welcomed the response of the UK Statistics Authority to my letter complaining on the use of incorrect comparisons on NHS data by Labour Ministers.
As the SNP Spokesperson for Health and Social Care at Westminster, I had written to the Chair of the UK Statistics Authority, Penny Young, to alert her to the misuse of data on NHS Scotland waiting times as related to the NHS in England by two Labour Under-secretaries. At the time of writing this letter, I understood that other UK Government Ministers had already been informed by the UK Statistics Authority of the potential risks to public trust on the use of incorrect statistics both on their social media channels and in statements to the House of Commons.
This instances I highlighted to Ms Young were as follows: MP Sharon Hodgson, Parliamentary Under Secretary for Health and Social Care in Health Questions in the Chamber on 14th April had stated that “Patients are 30 times more likely to wait two years for care in Scotland than in England “. Then in Westminster Hall on April 16th, former MP Dr Zubir Ahmed, former Parliamentary Under Secretary for Health and Social Care had relayed the claim that, “my patients and my constituents under NHS Scotland are 30 times more likely to wait over two years for treatment”.
The UK Stats Authority had already highlighted to UK Government Ministers two key points on why it is wrong to make such claims due to the limited comparability of NHS waiting times statistics between UK nations, and the potential for misleading claims where pathway-based waiting times are interpreted as numbers of individual patients.
In their reply to my complaint, the UK Stats Authority reiterated these risks with Ms Young stating, ‘Given the high public interest in NHS performance, particularly during an election period, we continue to stress the importance of presenting statistics clearly, transparently and with sufficient context in line with the OSR’s Standards for the Public Use of Statistics’.
I welcome this response from the UK Statistics Authority to my letter. I felt that the use of erroneous and potentially misleading comparisons on waiting times between the NHS in England and Scotland made by Labour Ministers in the Chamber was more of a blatant and petty political point scoring exercise than based on any hard and fast data. Indeed, my suspicions were confirmed to be true by Ms Young’s response to my letter, where she stated that she was aware of these statements in the House of Commons and recognised the concerns I raised about these comparisons presented without appropriate context.
Labour has form on this, but they are now on notice. I’ve already had to write to another former Environment Minister, Steve Reed MP, or Sewage Steve as he was named for his outrageous and wholly incorrect statements on Scottish water quality as being poorer than water quality in England. The UK Statistics Authority corrected Mr Reed and warned him at the time about the risk to public trust due to a Minister misusing data. Then again, Mr Michael Shanks MP has also had his wrists slapped by the Authority for repeating misleading claims on waiting times and the comparison of incompatible statistics. Fast forward just a few months, and now two separate Labour Ministers are back at this game, in the run up to the Scottish elections to add further political game playing to the mix.
It isn’t good enough and we should expect better from our public servants who have a duty of candour and a duty to ensure the public are given the correct facts. It seems the UK Statistics Authority agrees. Now, there is nowhere for Labour to hide from their economy with the truth and pick n’ mix data fabrications.
I’m pleased that the UK Statistics Authority has issued public guidelines on the responsible use of statistics going forward and hope that this signals the end to Labour’s unprofessional and frankly shocking behaviour. Meanwhile, thanks to the hard work of the Scottish Government, waiting times continue to go down in Scotland and we should be pleased with this progress as we continue to reduce lists further.
