1. 10 points. Diabetes Practice Profile 2011 Greg.fell@bradford.nhs.uk Jonathan.stansbie@bradford.nhs.uk Helen.Mcauslane@bradford.nhs.uk Simon.grant@bradford.nhs.uk

2. What we did was simple. Routinely available data QOF - 07/08 to 09/10 Admits – NHS comparators 07/08 to 09/10 Px – Epact. 2011 only Only the simplest level of analysis is incorporated here.

3. Point 1 Growth in prevalence. Variation in prevalence

4. There is substantial variation in prevalence of diagnosed diabetes at practice level. 09 10 there the prevalence of DM was 5% (95%CI 4.9 – 5.1), 26,000 cases. There has been growth in prevalence diagnosed – 13% growth in list size over 3 years estimated true prevalence is approx

5. Prevalence varies across practices

6. Not all diabetes is diagnosed. 77% of diabetes is diagnosed, a slightly higher proportion in Bradford than elsewhere. ?case finding?

7. Point 2 there has been improvement in achievement in key indicators of CV risk DM 12 - BP DM 17 – Cholesterol there is variation

8. Achievement DM12 and DM17 Exceptions - DM12 and DM17

9. Point 3 There is variation in achievement of HBA1C targets, and exception coding rates DM 23, 24, 25 – HBA1C target of 7,8 and 9

12. Point 4 City Care is consistently exception coding more patients from glycaemic indicators the picture is less clear for macro- vascular indicators

13. Alliance DM23 numerator DM23 denominator DM23 exceptions DM23 exception rate Airedale1,8943,73060413.9% BANCA2,4294,70560311.4% City Care2,8196,9111,41517.0% Independ ent2063945311.9% S&W3,7727,17591611.3% Alliance DM24 numerator DM24 denominator DM24 exceptions DM24 exception rate Airedale3,0283,9184169.6% BANCA3,8064,9233857.3% City Care5,1427,35697011.7% Independ ent324404439.6% S&W5,7537,4076848.5% Practice code DM25 numerator DM25 denominator DM25 exceptions DM25 exception rate Airedale3,6144,0303047.0% BANCA4,5015,0262825.3% City Care6,4417,6436838.2% Independ ent375413347.6% S&W6,7137,5645276.5% Alliance DM12 numerator DM12 denominator DM12 exceptions DM12 exception rate Airedale3,19939473878.9% BANCA3,92349823266.1% City Care6,18176217058.5% Independ ent335411368.1% S&W5,96275555366.6% Alliance DM17 numerator DM17 denominator DM17 exceptions DM17 exception rate Airedale3,1093,80253212.3% BANCA3,8814,7985109.6% City Care5,9237,49683010.0% Independ ent2993945311.9% S&W5,8087,23685510.6% Micro vascular Macro vascular

14. Point 5 Of the top 10 highest achieving practices for DM23 (HBA1C 7), half are in the lowest 50% spending practices for DM meds. There seems a poor relationship between med spend and control Only 1 of the top 10 spending practices is in the top 10 achieving practices

15. Spend / DM patient (medicines) and glycaemia control

16. Point 6 Quadrant charts can give indicators to spend and outcomes

17. Practice level spend (meds) and glycaemia control

18. Point 7 The prescribing bill for diabetes is approx £3m. There is significant spend per head variation

19. We spend £54 per diabetic patient per year on testing strips £1.4m per year. The correlation between spend per head on test strips and spend per head on insulin is moderate – R2 = 0.68 - but cant un itself totally explain the variation.

20. Point 8 It is relatively expensive to manage people to tight HBA1C targets it costs twice as much per patient to meet the HBA1C target of 7 as it does 9. are the outcomes twice as good?

21. Is the additional spend to get p to target of 7 worth it in terms of the additional health it buys The evidence might suggest it is NOT – ACCORD tailored prescribing rather than blanket approach Squaring this with QOF points for meeting stringent targets will be interesting.

22. The nature of the evidence, and interpretation of the evidence re blanket approach to tight control appears to be shifting. The evidence to support tight glycaemic control in either macro or micro vascular complications is weak, especially when expressed epidemiologically and in absolute terms. There is growing evidence highlighting limited significant differences between different classes of third line agents. Large expense might not be justified.

23. Point 9 There is a large variation in spend to get people to the HBA1C target. Concordance and compliance might be an issue.

24. Variation in spend to get DM patients to each of the 3 targets – 7,8 and 9 Practice level. All DM Medicines.

25. Point 10 There is moderate correlation between ethnicity in the practice and glycaemic control same for deprivation profile poorer populations have worse outcomes Asian populations have worse outcomes.

26. NB treat with caution. This is not adjusted for % exception coded. correlation between spend / pt at 9 target and % S Asian = 0.60. Practices with higher % S Asian spend more / pt to get them to the HBA1C target of 9 correlation between deprivation score and HBA1C 9 - DM25Acheivement = -.051 Practices with poorer populations have lower achievement oftheDM25 indicator correlation between % S Asian score and HBA1C 9 - DM25Acheivement = -0.47 Practices with high % S Asian have lower achievement of the DM25 indicator

27. And so what?

28. 1.QIPP – scope for improving quality and reducing cost 2.Targeting services and support where outcomes are least good 3.More nuanced interpretation 4.Formulary. 5.Nuanced vs blanket approach to prescribing 3 rd line agents – taking into account pt preferences, circumstances AND cost. 6.Systematic approach – DH HI NST 7.Quality Improvement methodology 8.Targeted and focused approach to reducing spend