Category Archives: Politics

Correlation does not equal causation, Healthcare, Politics

Hospital special measures and regression to the mean

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Forgive me for writing 2 posts in a row about regression to the mean. But it’s an important statistical concept, which also happens to be widely misunderstood. Sometimes with important consequences.

Last week, I blogged about a claim that student tuition fees had not put off disadvantaged applicants. The research was flawed, because it defined disadvantage on the basis of postcode areas, and not on the individual characteristics of applicants. This means that an increase in university applications from disadvantaged areas could have simply been due to regression to the mean (ie the most disadvantaged areas becoming less disadvantaged) rather than more disadvantaged individual students applying to university.

Today, we have a story in the news where exactly the same statistical phenomenon is occurring. The story is that putting hospitals into “special measures” has been effective in reducing their death rates, according to new research by Dr Foster.

The research shows no such thing, of course.

The full report, “Is [sic] special measures working?” is available here. I’m afraid the authors’ statistical expertise is no better than their grammar.

The research looked at 11 hospital trusts that had been put into special measures, and found that their mortality rates fell faster than hospitals on average. They thus concluded that special measures were effective in reducing mortality.

Wrong, wrong, wrong. The 11 hospital trusts had been put into special measures not at random, but precisely because they had higher than expected mortality. If you take 11 hospital trusts on the basis of a high mortality rate and then look at them again a couple of years later, you would expect the mortality rate to have fallen more than in other hospitals simply because of regression to the mean.

Maybe those 11 hospitals were particularly bad, but maybe they were just unlucky. Perhaps it’s a combination of both. But if they were unusually unlucky one year, you wouldn’t expect them to be as unlucky the next year. If you take the hospitals with the worst mortality, or indeed the most extreme examples of anything, you would expect it to improve just by chance.

This is a classic example of regression to the mean. The research provides no evidence whatsoever that special measures are doing anything. To do that, you would need to take poorly performing hospitals and allocate them at random either to have special measures or to be in a control group. Simply observing that the worst trusts got better after going into special measures tells you nothing about whether special measures were responsible for the improvement.

Dodgy reporting, Economics, Politics

Student tuition fees and disadvantaged applicants

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Those of you who have known me for a while will remember that I used to blog on the now defunct Dianthus Medical website. The Internet Archive has kept some of those blogposts for posterity, but sadly not all of them. As I promised when I started this blog, I will get round to putting all those posts back on the internet one of these days, but I’m afraid I haven’t got round to that just yet.

But in the meantime, I’m going to repost one of those blogposts here, as it has just become beautifully relevant again. About this time last year, UCAS (the body responsible for university admissions in the UK) published a report which claimed to show that applications to university from disadvantaged young people  were increasing proportionately more than applications from the more affluent, or in other words, the gap between rich and poor was narrowing.

Sadly, the report showed no such thing. The claim was based on a schoolboy error in statistics.

Anyway, UCAS have recently published their next annual report. Again, this claims to show that the gap between rich and poor is narrowing, but doesn’t. Again, we see the same inaccurate headlines in the media that naively take the report’s conclusions at face value, and we see exactly the same schoolboy error in the way the statistics were analysed in the report.

So as what I wrote last year is still completely relevant today, here goes…

One of the most significant political events of the current Parliament has been the huge increase in student tuition fees, which mean that most university students now need to pay £9000 per year for their education.

One of the arguments against this rise used by its opponents was that it would put off young people from disadvantaged backgrounds from applying to university. Supporters of the new system argued that it would not, as students can borrow the money via a student loan to be paid back over a period of decades, so no-one would have to find the money up front.

The new fees came into effect in 2012, so we should now have some empirical data that should allow us to find out who was right. So what do the statistics show? Have people from disadvantaged backgrounds been deterred from applying to university?

A report was published earlier this year by UCAS, the organisation responsible for handling applications to university. This specifically addresses the question of applications from disadvantaged areas. This shows (see page 17 of the report) that although there was a small drop in application rates from the most disadvantaged areas immediately after the new fees came into effect, from 18.0% in 2011 to 17.5% in 2012, the rates have since risen to 20.5% in 2014. And the ratio of the rate of applications from the most advantaged areas to the most disadvantaged areas fell from 3.0 in 2011 to 2.5 in 2014.

So, case closed, then? Clearly the new fees have not stopped people from disadvantaged areas applying to university?

Actually, no. It’s really not that simple. You see, there is a big statistical problem with the data.

That problem is known as regression to the mean. This is a tendency of characteristics with particularly high or low values to become more like average values over time. It’s something we know all about in clinical trials, and is one of the reasons why clinical trials need to include control groups if they are going to give reliable data. For example, in a trial of a medication for high blood pressure, you would expect patients’ blood pressure to decrease during the trial no matter what you do to them, as they had to have high blood pressure at the start of the trial or they wouldn’t have been included in it in the first place.

In the case of the university admission statistics, the specific problem is the precise way in which “disadvantaged areas” and “advantaged areas” were defined.

The advantage or disadvantage of an area was defined by the proportion of young people participating in higher education during the period 2000 to 2004. Since the “disadvantaged” areas were specifically defined as those areas that had previously had the lowest participation rates, it is pretty much inevitable that those rates would increase, no matter what the underlying trends were.

Similarly, the most advantaged areas were almost certain to see decreases in participation rates (at least relatively speaking, though this is somewhat complicated by the fact that overall participation rates have increased since 2004).

So the finding that the ratio of applications from most advantaged areas to those from least advantaged areas has decreased was exactly what we would expect from regression to the mean. I’m afraid this does not provide evidence that the new tuition fee regime has been beneficial to people from disadvantaged backgrounds. It is very had to disentangle any real changes in participation rates from different backgrounds from the effects of regression to the mean.

Unless anyone can point me to any better statistics on university applications from disadvantaged backgrounds, I think the question of whether the new tuition fee regime has helped or hindered social inequalities in higher education remains open.

Cancer, Dodgy reporting, Politics, Psychology

The Saatchi Bill

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I was disappointed to see yesterday that the Saatchi Bill (or Medical Innovations Bill, to give it its official name) passed its third reading in the House of Lords.

The Saatchi Bill, if passed, will be a dreadful piece of legislation. The arguments against it have been well rehearsed elsewhere, so I won’t go into them in detail here. But briefly, the bill sets out to solve a problem that doesn’t exist, and then offers solutions that wouldn’t solve it even if it did exist.

It is based on the premise that the main reason no progress is ever made in medical research (which is nonsense to start with, of course, because progress made all the time) is because doctors are afraid to try innovative treatments in case they get sued. There is, however, absolutely no evidence that that’s true, and in any case, the bill would not help promote real innovation, as it specifically excludes the use of treatments as part of research. Without research, there is no meaningful innovation.

If the bill were simply ineffective, that would be one thing, but it’s also actively harmful. By removing the legal protection that patients  currently enjoy against doctors acting irresponsibly, the bill will be a quack’s charter. It would certainly make it more likely that someone like Stanislaw Burzynski, an out-and-out quack who makes his fortune from fleecing cancer patients by offering them ineffective and dangerous treatments, could operate legally in the UK. That would not be a good thing.

One thing that has struck me about the sorry story of the Saatchi bill is just how dishonest Maurice Saatchi and his team have been. A particularly dishonourable mention goes to the Daily Telegraph, who have been the bill’s “official media partner“. Seriously? Since when did bills going through parliament have an official media partner? Some of the articles they have written have been breathtakingly dishonest. They wrote recently that the bill had “won over its critics“,  which is very far from the truth. Pretty much the entire medical profession is against it: this response from the Academy of Royal Medical Colleges is typical. The same article says that one way the bill had won over its critics was by amending it to require that doctors treating patients under this law must publish their research. There are 2 problems with that: first, the law doesn’t apply to research, and second, it doesn’t say anything about a requirement to publish results.

In an article in the Telegraph today, Saatchi himself continued the dishonesty. As well as continuing to pretend that the bill is now widely supported, he also claimed that more than 18,000 patients responded to the Department of Health’s consultation on the bill. In fact, the total number of responses to the consultation was only 170.

The dishonesty behind the promotion of the Saatchi bill has been well documented by David Hills (aka “the Wandering Teacake”), and I’d encourage you to read his detailed blogpost.

The question that I want to ask about all this is why? Why is Maurice Saatchi doing all this? What does he have to gain from promoting a bill that’s going to be bad for patients but good for unscrupulous quacks?

I cannot know the answers to any of those questions, of course. Only Saatchi himself can know, and even he may not really know: we are not always fully aware of our own motivations. The rest of us can only speculate. But nonetheless, I think it’s interesting to speculate, so I hope you’ll bear with me while I do so.

The original impetus for the Saatchi bill came when Saatchi lost his wife to ovarian cancer. Losing a loved one to cancer is always difficult, and ovarian cancer is a particularly nasty disease. There can be no doubt that Saatchi was genuinely distressed by the experience, and deserves our sympathy.

No doubt it seemed like a good idea to try to do something about this. After all, as a member of the House of Lords, he has the opportunity to propose new legislation. It is completely understandable that if he thought a new law could help people who were dying of cancer, he would be highly motivated to introduce one.

All of that is very plausible and easy to understand. What has happened subsequently, however, is a little harder to understand.

It can’t have been very long after Saatchi proposed the bill that many people who know more about medicine than he does told him why it simply wouldn’t work, and would have harmful consequences. So I think what is harder to understand is why he persisted with the bill after all the problems with it had been explained to him.

It has been suggested that this is about personal financial gain: his advertising company works for various pharmaceutical companies, and pharmaceutical companies will gain from the bill.

However, I don’t believe that that is a plausible explanation for Saatchi’s behaviour.

For a start, I’m pretty sure that the emotional impact of losing a beloved wife is a far stronger motivator than money, particularly for someone who is already extremely rich. It’s not as if Saatchi needs more money. He’s already rich enough to buy the support of a major national newspaper and to get a truly dreadful bill through parliament.

And for another thing, I’m not at all sure that pharmaceutical companies would do particularly well out of the bill anyway. They are mostly interested in getting their drugs licensed so that they can sell them in large quantities. Selling them as a one-off to individual patients is unlikely to be at the top of their list of priorities.

For what it’s worth, my guess is that Saatchi just has difficulty admitting that he was wrong. It’s not a particularly rare personality trait. He originally thought the bill would genuinely help cancer patients, and when told otherwise, he simply ignored that information. You might see this as an example of the Dunning Kruger effect, and it’s certainly consistent with the widely accepted phenomenon of confirmation bias.

Granted, what we’re seeing here is a pretty extreme case of confirmation bias, and has required some spectacular dishonesty on the part of Saatchi to maintain the illusion that he was right all along. But Saatchi is a politician who originally made his money in advertising, and it would be hard to think of 2 more dishonest professions than politics and advertising. It perhaps shouldn’t be too surprising that dishonesty is something that comes naturally to him.

Whatever the reasons for Saatchi’s insistence on promoting the bill in the face of widespread opposition, this whole story has been a rather scary tale of how money and power can buy your way through the legislative process.

The bill still has to pass its third reading in the House of Commons before it becomes law. We can only hope that our elected MPs are smart enough to see what a travesty the bill is. If you want to write to your MP to ask them to vote against the bill, now would be a good time to do it.