What’s new in Qnew tools for commissioning &

early diagnosis

Professor Julia Hippisley-Cox

EMIS NUG,

Warwick 2011

Acknowledgements

• Contributing practices • EMIS NUG (Chris, Charlie + others)• EMIS (Sean, David, Andy, Shaun+ others)• University of Nottingham• QResearch Advisory Board• ClinRisk (software) • Co-authors/researchers

Overview

• QFeedback• QData Linkage Project• Risk stratification tools for commissioning• QCancer – assess risk of existing cancer• Questions/Discussion/Suggestions

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ideally all practices to contribute to both QResearch & QSurveillance

Email julia.hippisley-cox@nottingham.ac.uk

QFeedback

QFeedback: update

• Interactive tool based on QSurveillance• Allows practices to view own data compared

• PCT, SHA, UK• Similar practices

• Graphs, Maps, Export data to excel• Deployed to 3,400 EMIS LV in early 2011• Uptake 2885 practices in 1st 6 months• Final of E Heath innovation awards

QFeedback in LV

QFeedback dashboard

Example maps

QResearch Data Linkage Project

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

QResearch Linkage Project

Data source• Hospital Episode

Statistics

• Cancer registry

• MINAP ‘Myocardial Infarction National Audit Project’

Content • Inpatient, outpatient,

A&E, maternity

• Cancer type, grade stage

• Heart attack type and treatment

New approach pseudonymisation

• 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

Pseudonymisation: method

• 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 EMIS• Apply identical software to external dataset• Allows two pseudonymised datasets to be linked

QScores – risk prediction tools

QScores – family of Risk prediction tools

• 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

Criteria for chosing clinical outcomes

• Major cause morbidity & mortality• Represents real clinical need• Related intervention which can be targeted• Related to national priorities (ideally)• Necessary data in clinical record• All then available as Open Source software

QScores: summary 1Outcome Intervention tool NHS/NICE

10 yr risk Cardiovascular disease (2008)

smoking cessation; weight loss; BP controllipid control

qrisk.org NHS Health ChecksQOFNICE (CG67)

10 yr riskType 2 diabetes (2009)

Exclude undiagnosed diabetesWeight lossExercisemedication

qdscore.org NHS Health Checks

5 yr risk moderate or severe Chronic kidney failure(2010)

Lifestyle measuresavoid nephrotoxic drugsLower BPmore frequent follow up of kidney function to allow earlier referral.

qkidney.org NHS Health Checks

QScores: summary 2Outcome Intervention tool NHS/NICE

Adverse effects of statins Myopathy Acute renal failure Serious liver

dysfunction

Review of dose as effects increase with dose Increased monitoring of U&E, LFT and CK for high risk

qintervention.org NICE (CG67)

Osteoporotic fractureHip/spine/wrist(2009)

regular weight bearing exercise Stop smoking, reduce alcohol Diet – vitamin D and calciumReduce risk of falling ;Check eye sight; medication review (eg antihypertensives, tricyclics)Hip protectorsVitamin d3 and calciumBisphophonates

qfracture.org NICE draft osteoporosis & fragility riskPilot for QOF

QScores: summary 3Outcome Intervention tool NHS/NICEVenous thromboembolism(2011)•Age, sex, BMI•Smoking•Varicose veins•Chronic renal disease•Heart failure•COPD•IBS•Hospital admission•Antipsychotics•HRT•COP•Tamoxifen

Prophylaxis/anticoagulationEg on hospital admission review of medication which increases risk (COP, HRT, antipsychotics, tamoxifen)

qthrombosis.org Related to NICE (CG92)

Population risk stratification for PCTs/CG

• Possible to apply all algorithms at PCT level• view the risk profile of population, • estimate the likely burden of disease• model the costs and benefits of interventions at

different thresholds of risk • set local targets• determine search strategies which the practice or

community staff can use for call/recall• evaluate outcomes & reset priorities.

Risk Stratification: questions

• QRISK & QDScore now being used at PCT level for recall

1. How useful has QRISK been for PCTs/practices

2. Useful to do this for other existing QScores?

3. Suggestions for new outcomes which would be useful • at PCT level?• at patient level?

Risk of Hospital Admission

• Requests from PCTs/CG to develop new tool identify patients • At risk of hospital admission• At risk of re-admission

• Problems with PARR ++ and the Combined Tool • Never properly validated• Difficult to implement• Not been updated

QAdmission (QA) Scoreshall we do it?

• Utility• To identify patients high risk (re) admission

• Intervention• Virtual wards• Community matrons

• Implementation• Needs to be simpler to implement• Integrated into any clinical system• Regularly updated coefficients

QCancer

Tools to help earlier diagnosis

www.qcancer.org

Username: nuguser

Password: ATouchOfSpice

Cancer: The problem of diagnosis

• Some cancers diagnosed very late when curative Rx not possible

• Symptoms very common in general practice• Single symptoms not very specific• Earlier diagnosis improves options &

outcome• NICE guidelines

• Complicated • Miss patients & false positive• No indication of risk of patient having cancer

Key predictive symptoms & factors

• Loss weight/appetite• Rectal bleeding• Haematemesis• Dysphagia• Haemoptysis• Haematuria• PMB• Abdominal pain• Constipation/diarrhoea• Cough

• Age, sex, ethnicity• deprivation• Smoking• Alcohol • Family history• Chronic diseases• Prior cancers• Anaemia (Hb<11)

Six common cancers so far

• Lung cancer• Colorectal cancer• Gastro-oesophageal cancer• Pancreatic cancer• Ovarian cancer• Renal cancer

New approach needed

• Need information based on patients record• combines symptoms + patient characteristics

(age, sex, deprivation, PMH, FH)• Absolute risk of different type of cancer • Needs to be available WITHIN the consultation to

guide management• Also as batch processing to identify patients with

alarm symptoms/high risk but no investigations or outcome BEFORE or AFTER consultation

QCancer methods

• Used 2/3 sample of QResearch database• Identified all patients with new onset alarm

symptoms in last 10 years• Followed up over 2 yr for diagnoses of cancer • Developed set of models which incorporates

symptoms and profile to give risk calculation• Tested performance of models on rest of

QResearch database & THIN database (INPS)• External validation by Oxford academics• Publication due Winter 2011/12

Using QCancer in practicesdemo

• www.qcancer.org• Either use as standalone or integrated• Template to help better recording positive and

negative symptoms triggered by code for alarm symptom?

• system calculates background risk before consultation and alerts to high risk of undiagnosed alarm symptoms?

• Run in batch mode to pick up those with high risk and/or undiagnosed alarm symptoms

Discussion/questions

• QFeedback• QLinkage project/pseudonymiation• Risk stratification tools• QAdmission Score – shall we do it• QCancer tools • Suggestions for future work.

Questions on pseudonymisation

• Pseudonymisation needed for QResearch • Do we need it for other purposes in clinical

system?• Eg generating list of patients for recruitment to

studies• Any more examples?• Any questions?

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General application