QOF changes

A couple of weeks ago the BMA issued its guidance on the QOF changes for this year. Basically some organisational areas were cut and the points transferred to two new areas to be based on surveys of patients.

The survey questions seem likely to be very similar, if not identical, to those asked about appointment booking in the 2007 patient survey.

As we have some data to go on, for England at least, the effect of the changes can be modelled at practice level. In fact I have done this for all practices in the UK, simply the results are likely to be less reliable outside England. In particular the square rooting of the COPD prevalence is based on the English average - slightly overestimating losses outside England.

To find the data for individual practices just use the search or browse pages to find the practice and then select from the menu on the left side.

Exception reporting (again)

The beast of exception reporting is rearing its head once again, this time in an article in the Health Service Journal (registration required) and in an editorial. What is being looked at here is raw practice data, similar to that produced routinely in Scotland without very much statistical analysis.

Helpfully there are some selected practice level details published by HSJ (5.6Mb Excel) and a summary at PCT level (PDF). In the articles this has been looked at in a journalistic way by finding the extremes and putting them in the headlines (and of course the blogging style is gross generalisation!). Simple things like the standard deviations are essential to give some idea of whether these extremes are the result of chance or other factors. For instance if we measured the height of all GPs we would be surprised if the tallest were ten times as tall as the average. However if we measured the number of suits owned it would be less surprising.

For a start I have looked at a box/whisker plot. In these the box contains the middle 50% of practices and the whiskers contain most of the rest with outliers plotted individually. We see from this that most practices are within quite small ranges.

I have written quite a lot about exception reporting. Analysis is difficult due to multitude of potential reasons for exceptions. We do not see any breakdown on the reason for exceptions in these statistics. QMAS collects the reasons to some extent, and this is visible at practice and PCT level. Although practices with high list growth are removed practices with high list turnover remain in the table. As new patients are automatically excepted this could have a significant effect on the data.

It is difficult to draw any conclusions. That would make the editorial a little dull though.

Many GPs will have made countless calls, sent innumerable letters, to try to goad their wayward patients to face up to their health risks. But the suspicion must remain that many patients have to all intents been dumped out of the NHS; the GP has given up on them, and too many PCTs are failing to bring these patients back.

I would suggest quite the opposite. These patients have given up on the GP and treatment. It is the place of the health service to inform and not to coerce. You can only try so hard. What is suggested is what has been described as a tyranny of health. The words goad and wayward suggest an extremely paternalistic view of the healthcare system. We can look back on the removal of patients from practice list for failure to comply with previous targets and are thankful that exception reporting has taken us away from there. We must not go back.

Updated 8th April

I have updated the boxplots with better ones (see the comment below). I should probably just leave the defaults on my stats package! There are quite a lot of points plotted but it is important to remember that there are around 8000 practices being plotted here. Even 1% of practices represents eighty of them.