Whats new in Q: Qfeedback , QFracture, QCancer

1. Whats new in Q: Qfeedback, QFracture, QCancer EMIS NUG conference September 2010 Warwick University Julia Hippisley-Cox Sessional GP Epidemiologist Director QResearch Director ClinRisk Ltd

2. Acknowledgements • EMIS & EMIS Practices contributing data • Many GPs & nurses for suggestions, piloting • University of Nottingham • Academic colleagues • ClinRisk Ltd (software) • THIN (validation data) • Oxford University – independent validation

3. Overview • Update on QSurveillance • QFeedback • Update on QScores • QIntervention • QFracture • Qcancer • General discussion

4. QSurveillance

5. QSurveillance: Overview • Real time infectious diseases surveillance system • Vaccine uptake reporting system • History • 2004 - Pilot study on QResearch in 2004 • 2005 - Upgraded to online QFLU • 2006 – Separate Flu vaccine service • 2007 – Separate Pneumo vaccine service • 2007 – upgraded to QSurveillance Avon floods • Included prospective consent for data extraction in emergency • Key part of HPA and DH emergency response

7. QSurveillance data extraction • Age/sex aggregated data • 100-150 indicators • Infectious diseases • Vaccine uptake – flu, pneumo, MMR • Daily, weekly, monthly, quarterly, annual reports • No patients can be identified • Counts < 5 suppressed

8. QSurveillance Governance • JHC custodian & responsible to practices, profession, ethics etc • No patients identifiable • Counts < 5 suppressed • Process for new indicators: • Practice consent covers additional data extracted to support emergency response • consult with relevant agency re need, ethics and advisory board (including NUG)

9. Governance Principles • Practice consent • Oversight board/review mechanism with NUG representation • Robust safeguards in place to protect patients and practices • Practices able to switch it on or off • Practice can access and benefit from data extracted

11. QSurveillance: pandemic • Incredibly busy with flu pandemic • Daily reporting over 10 months • Unexpectedly high demand across NHS • Detailed coverage by media • Under resourced • Need to ensure its scalable, resilient, properly resourced. • Decision to industrialise it • Ensure practices can access and benefit from data

13. Qfeedback System

14. QScores

15. Risk prediction tools - purpose • Population level • Risk stratification • Identification of rank ordered list of patients for recall or reassurance • Individual assessment • Who is most at risk of preventable disease? • Who is likely to benefit from interventions? • What is the balance of risks and benefits for my patient? • Enable informed consent and shared decisions

16. Overview Qscores - disease outcomes • QRISK (CVD) • QDScore (diabetes) • QFracture • QKidney (CKD3b+) • Qcancer • Range of other significant outcomes • published • published • published • published • completed • In progress Disease outcomes Status

17. Overview - risk/benefit interventions • Different approach needed • Assess baseline risk of outcomes • Then how they change with interventions • Use RCTs and meta analyses for benefits • Use database analyses for unintended effects • Starting with commonly used drugs e.g • Statins • Antidepressants • HRT • Warfarin • Antipsychotics • NSAIDS

18. Vascular Risk Engine: Requirements • Identify patients at high risk of vascular disease • CVD • Diabetes • Stage 3b,4, 5 Kidney Disease • Assessment of individual’s risk profile • Risks and benefits of interventions • Weight loss • Smoking cessation • BP control • Statins

19. QRISK2 www.qrisk.org • Risk of CVD & “Heart age” • Extensively reviewed and externally validated • Now included in • QOF • DH Vascular Guidance • NICE • Widespread use across NHS • Nearly all GP systems, many pharmacies, some hospitals, NHS Choices, Supermarkets, Occupational Health etc • Also free Open Source and Closed Software

20. QDScore – risk of Type 2 diabeteswww.qdscore.org • Predicts risk of type 2 diabetes • Published in BMJ (2009) • Independent external validation by Oxford University • Needed as epidemic of diabetes & obesity • Evidence diabetes can be prevented • Evidence that earlier diagnoses associated with better prognosis.

21. QKidney – risk of renal failurewww.qkidney.org • Set of algorithms • Identifies those at risk of • CKD3b+ • End Stage Renal Failure • Published BMC 2010 • So we can then • Identify high risk • Modify risk factors • Avoid nephrotoxic drugs • Monitor more closely • Prevent deterioration • Improve outcomes

22. Risks and Benefits Statins(presented at NUG 2009) • Two recent papers: • Unintended effects statins (BMJ, 2010) • Individualising Risks & Benefits of Statins (Heart, 2010) • Conclusions: • New tools to quantify likely benefit from statins • New tools to identify patients who might get rare adverse effects eg myopathy for closer monitoring

23. Why integrated tool CVD, diabetes, CKD? • Many of the risk factors over overlap • Many of the interventions overlap • But different patients have different risk profiles • Smoking biggest impact on CVD risk • Obesity has biggest impact on diabetes risk • Blood pressure biggest impact on CKD risk • Help set individual priorities • Development of personalised plans and achievable target

24. Primary prevention CVD:(slide from NICE website) • Offer information about: • absolute risk of vascular disease • absolute benefits/harms of an • intervention • Information should: • present individualised risk/benefit • scenarios • present absolute risk of events • numerically • use appropriate diagrams and text

25. Qinterventionwww.qintervention.org

26. QFracture

27. QFracture: Background • Osteoporosis major cause preventablemorbidity & mortality. • 2 million women affected in E&W • 180,000 osteoporosis fractures each year • 30% women over 50 years will get vertebral fracture • 20% hip fracture patients die within 6/12 • 50% hip fracture patients lose the ability to live independently • 1.8 billion is cost of annual social and hospital care

29. Patients with Symptomatic Vertebral Fractures • Scane et al, Osteoporosis Int 1994; 4: 89-92.

30. QFracture: challenge • Effective interventions exist to reduce fracture risk • Challenge is better identification of high risk patients likely to benefit • Avoiding over treatment in those unlikley to benefit or who may be harmed • Some guidelines recommend BMD but high cost and low specificity • Other guidelines recommend using 10 year risk of fracture

31. QFracture: development • Cohort study using patient level QResearch database • Similar methodology to QRISK • Published in BMJ 2009 • Algorithm includes established risk factors • Undertook validation against FRAX • Developed risk calculator which can • - identify high risk patients for assessment • - show risk of fracture to patients

32. QFracture vs FRAX comparison • Primary care • Works better in EMIS • Open Source • No funding • Includes extra risk factors eg • Falls • CVD • Type 2 diabetes • Asthma • Antidepressants • Detail smoking/Alcohol • HRT • Selected cohorts • Over-predicts in EMIS • Not published • Industry sponsored • NOGG guidance QFracture FRAX

33. Clinical example • 64 year old women • Heavy smoker • Non drinker • BMI 20.6 • Asthma • On steroids • Rheumatoid • H/O falls

35. Effect of interventions to reduce fracture risk in our example 64 year old women with a 20% fracture risk(note: her QRISK CVD risk is 18%)

36. Balancing risks vs benefits • Need to quantify risks of interventions • Few large long term safety studies • Bisphosphonates may increase risk of • Oesophageal cancer • Atrial fibrillation • Osteonecrosis of jaw • Atypical fracture • ? Other outcomes • Key thing for my patient is • Baseline risk of fracture • Likely benefit of intervention • risk of adverse effects of intervention • What is the overall risk/benefit ratio?

37. QCancer

38. QCancer scores • Tools to predict risk of range of common cancers • Risk stratification: • Identify those who need regular screening • Identify those who need ad hoc assessment • Patient communication • Background risk with family history – may be reassuring • Risk of cancer with “alarm” symptoms • Risks of cancer with smoking as decision aid for smoking cessation • Current • Ex smoker • Non smoker

39. QCancer Scores • Breast cancer • Prostate • Colorectal • Oesophageal • Renal/bladder • Lung • Ovary • Uterus • Breast lump • Prostatism • Rectal bleeding • Dysphagia • Haematuria • Haemoptysis • Abdo pain/distension • Post menopausal bleeding Cancers Alarm symptoms

40. See www.qresearch.org for • Information about QResearch database • Academic papers • Technical & statistical documents • Open source software • Patient information • Clinician information • Power points presentations • Information on how to contribute to the database (or email julia.hippisley-cox@nottingham.ac.uk )

41. Discussion • Questions • Comments • Suggestions • Feedback