Dynamic Data in Action: better patient care, improved public health

1. Dynamic Data in Action:better patient care, improved public health Sheila Teasdale Julie Richardson Dr Michael Soljak

2. What do we mean: ‘dynamic data’? Sheila Teasdale, PRIMIS Service Director Using Dynamic Data: Case Study Julie Richardson, Greenwich PCT Why ‘Choosing Health’ needs you Dr Michael Soljak, Health Improvement Directorate, DoH Current activities, future plans Sheila Teasdale Overview of session

3. Recorded at the point of care High quality Complete, accurate, relevant, accessible and timely Supports direct patient care avoidance of error medicolegal aspects cohort care (chronic disease management) preventive care and health promotion clinical audit and clinical governance GMS quality indicators PCT data requirements data for other clinicians and other health sectors national data requirements ‘Dynamic Data’

4. A case study Julie Richardson Greenwich PCT

5. Why ‘Choosing Health’needs you Dr Michael Soljak Health Improvement Directorate Department of Health

6. Current activities,future plans Sheila Teasdale

7. Supporting public health campaigns NCASP National Diabetes Audit Flu Smoking and obesity Pneumococcal vaccine Diabetes screening CHD risk Current activities, future plans

8. Queries to assess activity for Diabetes NSF web interface to transmit to NCASP database merging primary and secondary care data analysis available online (PIANO) started April 2004 report on first year due out June 2005 this year’s queries being prepared National Diabetes Audit

9. Health Protection Agency recommended use of PRIMIS Flu query sets at-risk cohort vaccine uptake in at-risk groups done in report-style, analyse-style and CHART formats September 2004 – January 2005 now discussing this year’s campaign Flu campaign

10. Health Improvement Directorate, Department of Health Phase 1: query sets to support preparation of Local Delivery Plans report-style with LDP analysis tool and email feedback proforma analyse-style with feedback proforma January – March 2005 Phase 2: query sets to support monitoring of LDPs queries and tools as above new CHART version with possibility of web transmission later starts soon, awaiting new guidance Smoking and obesity

11. Vaccine Tracking Unit, Department of Health Phase 1: query sets to support reporting of achievement to 31/3/05 subset-style for transcription of data into VTU website CHART with summary sheet for transcription of data into VTU website starts April 2005 Phase 2: development plan for next year queries and tools as above discussing new CHART version to try out web transmission Pneumococcal vaccine

12. Continue work on all the above Diabetes screening research collaboration screening uptake rates for at-risk group obese patients aged over 40 CHD primary prevention Health Improvement Directorate, Department of Health in discussion about criteria Need for co-ordination Future through SUS Future plans

13. Dynamic Data in Action:better patient care, improved public health Sheila Teasdale Julie Richardson Dr Michael Soljak

14. Using Dynamic Data:Case Study Julie Richardson Greenwich Primary Care Trust

15. Immunising against influenza: why bother? • Deaths in vulnerable people • Increased morbidity with other conditions • Increased vulnerability to external injuries • Source of transmission to others • PCT/GP targets!

16. Flu vaccination scheme - background • Local reporting for incentive scheme • Focus on over 65s only • (65% - 50p/patient. 70% - £1/patient) • National reporting to feed the machine

17. How I got involved • Complaints / requests for help from practices around reporting • All filling in forms • All trying to find their own solutions

18. Flu co-ordinators’ meeting Explain how PRIMIS / MIQUEST can help SELHPU

19. Identify all at-risk patients Raise profile of under 65s at risk Proactive not reactive Simpler for practices Uniform reporting Robust data for planning Benefits of MIQUEST

20. Agreed good idea but: - 3 PCTs wanted to do their own thing 2 PCTs had no PRIMIS facilitator Greenwich went on alone SELHPU

21. Flu seminar - explain process September - identify at-risk patients October - uptake query set November - uptake query set December - uptake query set Action

22. Download query set from PRIMIS website Use MIQUEST Query Manager to customise query set for individual practices Email queries to practices with instructions on how to run through MIQUEST Practice runs queries & views results in Excel Practice either fills in form or anonymises data & returns to PCT Process

23. "The problem is not that there are problems. The problem is expecting otherwise and thinking that having problems is a problem." -Theodore Rubin

24. All practices need an e-mail account

25. … and they need to know how to use it

26. Need to be able to send query files… Dr X flu.julie Dr X flu.zip

27. …and flu co-ordinators need to learn how to read Instructions

28. …and practices need the software to open them

29. … and to use them

30. Emphasise deadlines

31. Maximising the impact of immunisation • we want to identify those practices for the • greatest impact • Practice A: 414 immunised out of 444 • Practice B: 44 immunised out of 144 • Practice C: 144 immunised out of 444

32. Maximising the impact of immunisation

33. Maximising the impact of immunisation

34. What else can we learn? • Integrity of practice-based registers • Relationship of immunisation to consultation rates • Influenza • Other morbidity • Indication of practice capacity • Alternative strategies to reduce transmission

35. For PCT Uniform, comparable data from all practices Baseline for future years Targeted planning Outcome

36. For Practice Identify and vaccinate at-risk patients Vaccine ordering Simpler reporting Outcome

37. For Patients Better health? Outcome

38. November ’03 – January ’04 St Thomas’ Hospital had 27 confirmed cases of flu - all under 65 (3 adults, 24 children) 12 of the 27 were in ‘at-risk’ groups 3 had hospital acquired infection, 24 were community acquired Of those that were community acquired, 1 attended a special needs playgroup where none of the children were vaccinated. He died. The human element

39. Why “Choosing Health” Needs You Dr Michael Soljak Health Improvement Directorate

40. What On Earth Is A PSA Target? • Every two years (2004) HM Treasury conducts a Spending Review • As part of the review, Public Service Agreement targets are agreed with Government Departments • PSA targets were converted into the 2005-8 Priorities & Planning Framework • The PPF is converted into PCT Local Delivery Plan (LDP) “lines” like the smoking and obesity queries

41. The Wanless Report: Securing Good Health For The Whole Population 3.135 “…practice based patient registers could be developed to record information on disease, medication and risk factors. Such knowledge could be used not only to improve chronic disease management, but to guide local activity aimed at health improvement and the primary prevention of disease”. Recommendation 9.14 “An experiment should be established across primary care to assess the benefits of monitoring risk… It would also produce evidence about the effectiveness of information to assist personalised risk management and disease prevalence in local populations. The experiment should be directed towards areas of inequality”. PRIMIS IT Facilitator

42. The National Priority Areas

43. Local Delivery Plan Lines Smoking status among people aged 15 to 75 years, as recorded in GP records • Line 1: Number of people aged 15 to 75 years on a GP register, recorded as being a smoker in the last 15 months • Line 2: Number of people aged 15 to 75 years on a GP register, with a smoking status recorded in the last 15 months • Line 3: Total number of people aged 15 to 75 years on a GP register Obesity among people aged 15 to 75 years, as recorded in GP records Line 1: Total number of people aged 15 to 75 years on GP register, recorded as having a BMI of 30 or greater in the last 15 months Line 2: Total number of people aged 15 to 75 years on GP register, with a BMI recorded in the last 15 months. Line 3: Total Number of people aged 15 to 75 years on GP register.

44. Synthetic Smoking Prevalence Source: Health Development Agency

45. Baselines & Trajectories: Smoking

46. Baselines & Trajectories: Smoking Health Survey = 26% smokers

47. Baselines & Trajectories: Obesity

48. Baselines & Trajectories: Obesity Health Survey = 21.4% obese

49. The Future • There is a big task ahead, firstly in loading queries/CHART and obtaining baseline data from all practices • Secondly in beginning to improve data quality and timeliness • A submission has been made to the QOF review to incentivise recording and intervention for smoking and obesity from April 2006 • In the meantime, PCTs will need to support practices to improve data quality through the “traditional” routes- overtime, loan of data entry staff etc • A Primary Prevention Query Library will be developed to enable interested PCTs to obtain further data e.g. age-sex breakdowns, other health risk factor prevalences etc