Hospital needless deaths figure 'misleading' Dr David Spiegelhalter said newspapers and politicians are wrong in their widespread use of the number. The unsubstantiated but widely quoted figure of 13,000 excess deaths at the 14 hospital trusts recently investigated by the Keogh inquiry into mortality rates threatens to become a statistic that will not go away, according to a leading healthcare statistician. Dr David Spiegelhalter, who is Winton professor for the public understanding of risk at the University of Cambridge, said newspapers and politicians are wrong in their widespread use of the number. He gave as an example the Sunday Telegraph stating that "13,000 died needlessly at 14 worst NHS trusts," but other papers ran similar claims. Sir Bruce Keogh, NHS medical director, led an investigation into the 14 hospital trusts to find out whether their apparent higher than expected death rate over the seven years from 2005 to 2012 was a reflection of poor care. But, Spiegelhalter pointed out in the British Medical Journal, he did not substantiate the number of excess deaths, let alone deaths that could have been avoided. In fact, the Keogh report categorically stated that it was not possible to work out how many potentially avoidable deaths there may have been at a hospital from either of the two mortality indexes currently in use - the HSMR (hospital standardised mortality ratio) or the SHMI (summary hospital-level mortality indicator). "It is in my view misleading and a potential misuse of the figures to extrapolate from them a conclusion that any particular number, or range of numbers of deaths were caused or contributed to by inadequate care," Keogh's report said. The 13,000 figure came from data produced by Professor Sir Brian Jarman of the Dr Foster unit at Imperial College, who devised the HSMR, but Spiegelhalter said it is not clear who told journalists about it. "It should have been fairly predictable that such a briefing to journalists would be misleadingly reported," he said. Jarman, in emails to the Guardian, said he had tried to correct journalists when they suggested the 13,000 deaths were avoidable, because that could not be established from the figures. I am very grateful to the media, of all political persuasions, for helping us to get people to take our data seriously - it has been a long struggle for over a decade ... ... we have been doing no more than ask that people use the data as a trigger to look further - to use SMRs, mortality alerts, individual patients, staff and patient surveys etc. We would like to take it out of the political arena and look at the data rationally. So, no, I don't regret the use of our data by the press and media although I would like them to be more precise - it may be my fault that I am not persistent enough in explaining a rather complicated subject," he wrote. But Spiegelhalter said: "The crucial fact is that both the SHMI and HSMR are standardised to recent national performance, and so we would expect at any time that around half of all trusts would have 'higher than expected' mortality, just by chance variability around an average. Indeed, for the SHMI between January 2012 and December 2012, 56% of trusts (80/142) had above expected mortality. It would be absurd to label all these as outliers, and yet a BBC news item claims that: 'Outliers are trusts which have a higher than expected number of deaths.' It is enough to make a statistician sob. Spiegelhalter, who led the statistical team at the inquiry into babies' deaths following heart surgery at Bristol Royal Infirmary, says he deeply regrets the term "excess deaths" for the difference between the observed and expected number, which was first used there. It too easily translates, "whether through ignorance or mendacity," into needless deaths, he says. "So what about the '1,200 needless deaths' at Mid-Staffs?" he writes. A recent BBC news story claims: 'Data shows there were between 400 and 1,200 more deaths than would have been expected between 2005 and 2008.' But there are no published data that show this, as fully discussed in the first Francis report. Like the '1,200' at Mid-Staffs, '13,000' threatens to become a 'zombie statistic' - one that will not die in spite of repeated demolition.