New tools to support decisions and diagnoses

1. New tools to support decisions and diagnoses Julia Hippisley-Cox, GP, Professor Epidemiology & Director ClinRisk Ltd EMIS NUG 12 06 Sept 2012

2. Acknowledgements • Co-authors • QResearch database • EMIS & contributing practices & User Group • University of Nottingham • ClinRisk (software) • Oxford University (independent validation)

3. Outline • QSurveillance in EMIS Web • QResearch data linkage project/Openpseudonymiser • QFracture • QCancer • QDiabetes - Dr Tim Walter • Work in progress • Discussion

4. QSurveillance live in EMIS Web • Infectious diseases surveillance to the HPA • Automated vaccine returns DH • QFeedback system • Available all LV and EMIS Web • For existing sites, check activation EMAS manager • If new, then email qsurveillance@qsurveillance.org

6. QSurveillance in Enquiry manager

7. QFeedback in LV

8. QFeedback for EMIS LV and Web

9. QResearch Database • Over 700 general practices across the UK, 14 million patients • Joint venture between EMIS and University of Nottingham • Patient level pseudonymised database for research • Available for peer reviewed academic research where outputs made publically available • Open to all EMIS LV and Web practices including Scotland • Data linkage – deaths, deprivation, cancer, HES

10. QResearch Data Linkage Project • QResearch database already linked to • deprivation data • cause of death data • Very useful for research • better definition & capture of outcomes • Health inequality analysis • Improved performance of QRISK and similar scores • Planning additional linkages • HES • Cancer registries

11. New approach pseudonymisation • member of ECC of NIGB. s251 approvals for use of identifiable data where public interest but consent not possible and no practical alternative • Need approach which doesn’t extract identifiable data but still allows linkage • Legal, ethical and NIGB approvals • Secure, Scalable • Reliable, Affordable • Generates ID which are Unique to Project • Applied within the heart of the clinical system • Minimise disclosure

12. www.openpseudonymiser.org • Scrambles NHS number BEFORE extraction from clinical system • Takes NHS number + project specific encrypted ‘salt code’ • One way hashing algorithm (SHA2-256) • Cant be reversed engineered • Applied twice in to separate locations before data leaves source • Apply identical software to external dataset • Allows two pseudonymised datasets to be linked

13. Open Pseudonymiser • Open P has been accepted as a standard by a number of major organisations including • NIGB • EMIS NUG • EMIS & other GP suppliers • BMA • NHS Information Centre • Office National Statistics • EMIS is integrating it into so practices can ‘pseudonymised at source’ • This is the ‘practical alternative’ to using identifiable data when consent is impossible and helps protect patient confidentiality. • “If in doubt, pseudonymise it!”

15. all LV and Web practices welcome to contribute to both QResearch & QSurveillance Email julia.hippisley-cox@nottingham.ac.uk Get switched on

16. Clinical Research Cycle

17. QScores – new family of Risk Prediction tools • 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 • Population level • Risk stratification • Identification of rank ordered list of patients for recall or reassurance • GP systems integration • Allow updates tool over time, audit of impact on services and outcomes

18. Current published & validated QScores

19. Today we will cover three tools • QFracture • QCancer • QDiabetes – Dr Tim Walters

20. QFracture: Background • Osteoporosis major cause preventablemorbidity & mortality. • 300,000osteoporosis 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 • 2 billion is cost of annual social and hospital care

22. QFracture: challenge • Effective interventions exist to reduce fracture risk • Challenge is better identification of high risk patients likely to benefit • Avoid over treatment in those unlikely to benefit or who may be harmed • Some guidelines recommend BMD but expensive and not very specific

23. QFracture in national guidelines • Published August 2012 • Assess fracture risk all women 65+ and all men 75+ • Assess fracture risk if risk factors • Estimate 10 year fracture risk using QFracture or FRAX • Consider use of medication to reduce fracture risk

24. Two new indicators recommended QOF 2013 for Rheumatoid Arthritis http://www.nice.org.uk/media/D76/FE/NICEQOFAdvisoryCommittee2012SummayRecommendations.pdf

25. Comparison of QFracture vs FRAX QFracture FRAX • Developed in UK primary care • Better identifies high risk • Less likely to over predict • Independent external validation • Risk over different time periods • Includes extra factors known to affect fracture risk eg • Antidepressants • Nursing home • Falls • Will be integrated EMIS Web • Mostly non-UK research cohorts • Industry sponsored • Over predicts leading to over treatment • Lack of independent validation • Not published and open to scrutiny

26. QFracture Web calculator www.qfracture.org • Example: • 64 year old women • History of falls • Asthma • Rheumatoid arthritis • On steroids • 10% risk hip fracture • 20% risk of any fracture

27. QScoreson the app store

28. Early diagnosis of cancer: The problem • UK has relatively poor track record when compared with other European countries • Partly due to late diagnosis with estimated 7,500+ lives lost annually • Later diagnosis due to mixture of • late presentation by patient (alack awareness) • Late recognition by GP • Delays in secondary care

29. Symptoms based approach • Patients present with symptoms • GPs need to decide which patients to investigate and refer • Decision support tool must mirror setting where decisions made • Symptoms based approach needed (rather than cancer based) • Must account for multiple symptoms • Must have face clinical validity eg adjust for age, sex, smoking, FH • updated to meet changing requirements, populations, recorded data

30. QCancer scores – what they need to do • Accurately predict level of risk for individual based on risk factors and multiple symptoms • Discriminate between patients with and without cancer • Help guide decision on who to investigate or refer and degree of urgency. • Educational tool for sharing information with patient. Sometimes will be reassurance.

31. Methods – development algorithm • Huge representative sample from QResearch aged 30-84 • Identify new alarm symptoms (eg rectal bleeding, haemoptysis) and other risk factors (eg age, COPD, smoking, family history) • Identify cancer outcome - all new diagnoses either on GP record or linked ONS deaths record in next 2 years • Established methods to develop risk prediction algorithm • Identify independent factors adjusted for other factors • Measure of absolute risk of cancer. Eg 5% risk of colorectal cancer

32. ‘Red’ flag or alarm symptoms (identified from studies including NICE guidelines 2005) • Haemoptysis • Haematemesis • Dysphagia • Rectal bleeding • Vaginal bleeding • Haematuria • dysphagia • Constipation, cough • Loss of appetite • Weight loss • Indigestion +/- heart burn • Abdominal pain • Abdominal swelling • Family history • Anaemia • Breast lump, pain, skin tethering

33. Qcancer now predicts risk all major cancers including Lung Pancreas Kidney Ovary Colorectal Testis Gastro Cervix Breast Prostate Blood Uterus

34. Results – the algorithms/predictors

35. Methods - validation is crucial • Essential to demonstrate the tools work and identify right people in an efficient manner • Tested performance • separate sample of QResearch practices • external dataset (Vision practices) at Oxford University • Measures of discrimination - identifying those who do and don’t have cancer • Measures of calibration - closeness of predicted risk to observed risk • Measure performance – Positive predictive value, sensitivity

36. Using QCancer in practice – v similar to QRISK2 • Standalone tools • Web calculator www.qcancer.org/2013/female/php www.qcancer.org/2013/male/php • Windows desk top calculator • Iphone – simple calculator • Integrated into clinical system • Within consultation: GP with patients with symptoms • Batch: Run in batch mode to risk stratify entire practice or PCT population

37. QCancer – women http://qcancer.org/2013/female/index.php PROFILE 64yr old woman, Moderate smoker Loss appetite Abdo pain Abdo swelling 72% risk of no cancer 28% risk any cancer - ovarian = 20% - colorectal = 1.5% - pancreas =.16% - Other 3.4%

38. QCancer – men http://qcancer.org/2013/male/index.php • PROFILE • 64yr old man, • Heavy smoker • FH GI cancer • Loss appetite • Recent VTE • Weight loss • Indigestion • RESULTS • 71% risk of no cancer • 29% risk any cancer • Lung = 9% • Pancreas =6% • Prostate =2% • Other =5%

39. GP system integration: Within consultation • Uses data already recorded (eg age, family history) • Use of alerts to prompt use of template • Automatic risk calculation in real time • Display risk enables shared decision making • Information stored in patients record and transmitted on referral letter/request for investigation • Allows automatic subsequent audit of process and clinical outcomes

40. GP systems integrationBatch processing • Similar to QRISK which is in 95% of GP practices– automatic daily calculation of risk for all patients in practice based on existing data. • Identify patients with symptoms/adverse risk profile without follow up/diagnosis • Enables systematic recall or further investigation • Systematic approach - prioritise by level of risk.

41. Comparison other cancer risk tools QCancer The “RAT” • Large UK sample with data until 2012 • Symptoms based approach • Takes account of risk factors including age, sex, smoking, FH • Independent external validation by Oxford university • Can be updated and integrated into computer systems into workflow • 30-40 Exeter practices; paper records from 10 yrs ago • Focused on single symptoms and pairs where enough data • Doesn’t adjust for age although cancer risk clearly changes with age • Not been validated (independently or by authors) • Distributed as a mouse mat for each cancer

42. Next steps - pilot work in clinical practice supported by DH

43. Work in progress; QAdmissions • New tool to identify patients at risk of emergency admission “QAdmissions” • Based on pseudonymised linked primary and secondary care data on QResearch • Will predict overall admission risk but also top most common type of admission • cardiovascular • Asthma etc • So that interventions can be better targeted to prevent admission • In partnership with East London. Hear more at Kambiz Boomla session tomorrow

44. QDiabetes • Type 2 diabetes epidemic • Potential for prevention • Risk assessment using validated risk tools including QDiabetes • Individual assessment and also batch processing • QDiabetes is UK & fully validated • Includes deprivation & ethnicity • Ages 25-84 • Efficient as 2 extra questions on top of QRISK • www.qintervention.org • Already integrated into EMIS Web • Evaluation in London and Berkshire Preventing type 2 diabetes - risk identification & interventions for individuals at high risk 2012

45. Thank you for listeningQuestions & Discussion