QOF Data for England 2020/21

The data for the QOF in England has now been published on the site for they year 2020-21. You won't need me to tell you that it was quite an unusual year. Inb QOF terms most of the indicators were suspended through the year. Prescribing indicators were suspended a bit later on through the year than other but, in the end, all that remained were the flu and cervical screening indicators. These all had their points doubled.

The other area that was still active was the prevalence adjustment. Effectively this meant that practices were still paid for the number of patients on their disease registers. It still paid to add patients to disease registers.

Of course there were a lot of other complications and this is probably one of the reasons that NHS Digital did not publish points totals this year. There were several new indicators in there as well and points would not really have made a lot of sense and certainly would not have tallied with payments. However the data was still collected and is presented on the site. As with many things 2020-21 is going to stand out a bit on the charts. Please do have an explore of the data.

Although most of the indicators are down the figures are a testement to the huge amount of work that was done by practices to some of the most vulnerable members of our practice lists. Even with all of the restrictions that were necessary through the year large numbers of patients continued to get appropriate care for chronic disease.

I hope to have data from Northern Ireland in a few weeks. QOF no longer takes place in Scotland and Wales has a very minimal system and I could not find published data last year.

What I know so far about QCovid, Shielding and Gestational Diabetes

QCovid is the latest predictive formula from QResearch. Currently based at the University of Oxford and headed by Professor Julia Hippisley-Cox it has been doing this sort of thing for a while now. QRisk is well known and respected but there are several other score derived from a big bank of patient records. I think that we have to assume that they know what they are doing.

They are also reasonably open about their methods. They published in the BMJ way back in October with all of the factors listed. There are a number of medical conditions along with deprivation scores and demographic information. There is no mention of gestational diabetes in that paper. In fact the only mentions of pregnancy at all are in reference to previous shielding criteria (pregnancy with significant heart disease) and that there were too few events to include pregnancy in the analysis. The latter is quite telling in itself given that they looked at over 4300 deaths in their initial analysis - a large effect is likely to have been spotted.

They have also published the algorithm itself. The maths are complicated and largely beyond me to follow but it is easy to see that the inputs do not include gestational diabetes, only types one and two.

When it came to implementation NHS Digital said that the categories for diabetes were :

Type 1 diabetes

Type 2 diabetes (including other forms such as gestational diabetes)

Gestational diabetes is high blood sugar (glucose) that develops during pregnancy and can resolve after giving birth. Women who have had gestational diabetes are at increased risk of developing type 2 diabetes or having undiagnosed diabetes.

Some patients with past gestational diabetes have been identified in combination with other factors by the QCovid model as being potentially at high risk from COVID-19.

Somewhere along the line Gestational Diabetes has been classified as being the same as type two diabetes – even when the GD has resolved. It is not clear where this decision came from. There is no sign that it was intended by the QResearch team.

The Royal College of Obstetrics and Gynaecology tweeted

The effect of this is likely to increase the risk assessment of some pregnant women and those who have given birth in the past. Of course that does not mean that they should shield. For the most part these are likely to be relatively young women with a low Covid risk. However the next part is the shielding criteria.

The detailed criteria are on a site that I cannot access when not at work but it seems to be an absolute risk over over 0.5% of death in the first wave (that was the data they used to create the formula) or a relative risk of 10 times above a person without risk factors or the same age.

I put a woman of 35 years into the calculator. She was white, had a BMI of 31 (150cm,70kg) and a postcode of SN1 2DQ (that is my surgery postcode in the centre of Swindon). I ticked the box for Type 2 diabetes.

The absolute risk of death was 1 in 9709 but the relative risk of 17. Risk of hospital admission was 1 in 558 – relative risk of 7.7. The risk of death is enough to trigger shielding. Nearly ten thousand people would have to shield perfectly to prevent one death. The relative risk was about ten times less than for the population as a whole.

(Without the Type 2 diabetes the relative risks were 1.7 and 2 respectively). If you want to know more about absolute and relative risk see this article.

The effect of the inclusion of a history of gestational diabetes as equivalent to type II diabetes and the relative risk criteria for shielding has had a significant effect on these women.

My personal view is that, although these women would not normally be on the flu vaccine programme it would be reasonable to offer them a Covid vaccination soon, as part of cohort 6. This is the cohort to which most patients with diabetes would belong and is being vaccinated now. I feel that the argument for shielding is much weaker.

If you are reading this having received a notice to shield out of the blue then don’t panic. Your absolute risk may be quite low. Have a try on the calculator to see. We are in lockdown now so still be careful but not paranoid. If you are offered the vaccine though, I see no reason to put it off. Go for it!