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insurance industry is unacceptable to the HSCIC? Its own information governance assessment from August says that access to individual patients’ records can ‘enable insurance companies to accurately calculate actuarial risk so as to offer fair premiums to its [sic] customers. Such outcomes are an important aim of Open Data, an important government policy initiative.’ Is that document binding? What are the rules? Are there previous dodgy data-sharing arrangements, agreed by the NHSIC, that the HSCIC is still honouring, with data still flowing out of the building?
    This is chaos. Then, on Thursday, to make things worse, Public Health Minister Jane Ellison appears to have misled Parliament, telling it that the data released by the HSCIC was ‘publicly available, non-identifiable and in aggregate form’. This is utterly untrue. It was line-by-line data – every individual hospital episode, for every individual patient, with unique pseudonymous identifiers – which was then aggregated into summary tables by the actuaries.
    To summarise, a government body handed over parts of my medical records to people I’ve never met, outside the NHS and the medical research community, but it is refusing to tell me what it handed over, or who it gave it to, and the Minister is now incorrectly claiming that it never happened anyway.
    There are people in my profession who think they can ignore this problem. Some are murmuring that this mess is like MMR, a public misunderstanding to be corrected with better PR. They are wrong: it’s like nuclear power. Medical data, rarefied and condensed, presents huge power to do good, but it also presents huge risks. When leaked, it cannot be unleaked; when lost, public trust will take decades to regain.
    This breaks my heart. I love big medical datasets, I work on them in my day job, and I can think of a hundred life-saving uses for better ones. But patients’ medical records contain secrets, and we owe them our highest protection. Where we use them – and we have used them, as researchers, for decades without a leak – this must be done safely, accountably and transparently. New primary legislation, governing who has access to what, must be written: but that’s not enough. We also need vicious penalties for anyone leaking medical records; and the HSCIC needs to regain trust, by releasing all documentation on all past releases, urgently. Care.data needs to work: in medicine, data saves lives.
    The care.data programme was suspended shortly after this piece was published, with the promise that they’d have a think and relaunch in six months. Six months have already passed, and there has been no relaunch. I’m on their Advisory Group and continue to shout about the issues raised above, indoors and out. Medical data can save lives, but if the single biggest project ever conceived on patient records is not handled properly, we risk destroying public trust for all such projects, not just care.data.

The Huff
    Guardian , 19 January 2008
    In 1954 a man called Darrell Huff published a book called How to Lie with Statistics . Chapter 1 is called ‘The Sample With Built-In Bias’, and it reads exactly like this column, which I’m about to write, on a Daily Telegraph story in 2008.

    Huff sets up his headline: ‘The Average Yaleman, Class of 1924, Makes $25,111 a Year!’ said Time magazine, half a century ago. That figure sounded pretty high: Huff chases it, and points out the flaws. How did they find all these people they asked? Who did they miss? Losers tend to drop off the alma mater radar, whereas successful people are in Who’s Who and the College Record . Did this introduce ‘selection bias’ into the sample? And how did they pose the question? Can that really be salary rather than investment income? Can you trust people when they self-declare their income? Is the figure spuriously precise? And so on.
    In the intervening fifty years this book has sold one and a half million copies. It’s the