This is a great audit based on our work in a nearby practice to me within the PreDM project
The previously described CES results are no completed their first year.
Results in from the practices reporting back (covering 55,000 patients) we have
Average increase in Diabetic Register 24 patients per practice
Average increase in Pre Diabetes Register 78 patients per practice
Average reduction in miscoded / uncoded Diabetes 18 patients per practice
Falkland Surgery reported an increase in Diabetes Prevalence of 100 patients over a two year period.
Emis Health have now integrated QDiabetes into EmisWEB much more closely as this snippet from their support centre describes.
From EmisWEB go to the support link and then search for the term QDiabetes
Recent diabetes prevention guidelines issued by NICE recommend the use of a validated computer-based risk-assessment tool, such as QDiabetes, to identify patients who may be at high risk of developing type 2 diabetes.
The QDiabetes tool has been integrated into EMIS Web so you can easily meet the NICE recommendations and put your own prevention strategies into place.
This page on the Emis Support site tells you how to use the QDiabetes tool, also known as QDScore, in EMIS Web and then explains how to use the batch add process to update your patient records with their score. You can then run a search to find your at-risk patients and invite them in for testing.
We have just assessed our results from Falkland Surgery. For a total list size of 14500 patients we had 503 patients 2 years ago with Diabetes. Today our Diabetic population has just turned 600. That means 97 patients net increase in Diabetes population in two years or virtually one new diabetic per week. We are currently collating the results from the other practices on the CCG.
We continue integrating pre-diabetes care and identification within the practice.
Although not directly as a result of the project, one surgery has recorded a rise in their diabetic population of 28 patients (rising from 489 to 517 diabetics) in the four months of the screening process. Some patients were identified by the screening letters and blood tests, but some were identified because of a review of pre-existing blood tests, and a migration to using HbA1c as a part of the screening armamentarium. Much of it was assisted by the heightened awareness within practice staff and patients of diabetes caused by the project.
Other practices within the patch are being invited to participate in the same way.
Earlier today I posted a message saying we had a fantastic 33/133 responses to our invitation to undergo a drop in / point of care HbA1c blood test this morning, for those with a 15% QDiabetes risk. By the close of play (we had to stay open an extra 1/2hr) and had performed 63 tests, a massive 48% response to a single invitation letter.
Of these we found one diabetic (HbA1c 65) and 5 with borderline results/IGT (HbA1c 42-47 and BS 7-9.9) enrolled 9 into our E4H lifestyle sessions, and agreed lifestyle changes with many of the others.
Here are some instructions for patients who turn up at the pre-diabetes screening day event
And the general instructions for clinical staff (1 receptionist, two nurses, two doctors and 3 Infinion PoC HbA1c machines)
EmisWEB template we used
Today we are running our drop in screening clinic at Falkland Surgery. So far the morning rush has seen a fantastic response of 33 attendees from an invitation letter to 133 patients (10.15am so far). Still working through the tests and luckily no diabetics identified so far.
We have now picked up 5 new diabetics out of 19 respondents, so virtually 25% positive identifications of diabetes with the same number of borderline results. This is higher than the 14% we got in the first cohort (though probably random variation)
One participating surgery has just reported that although only 9 out of 50 people responded to our invite (for those over 30% QDiabetes risk) of those 9 patients, 2 have been shown to have undiagnosed Diabetes, and 4 have borderline HbA1c between 42 and 47. Thats a 22% pickup rate. How do we catch the non responders?
So far we are averaging about 14% pickup rate for those responders