New tools to support decisions and diagnoses
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New tools to support decisions and diagnoses. Julia Hippisley-Cox, GP, Professor Epidemiology & Director ClinRisk Ltd EMIS NUG 12 06 Sept 2012. A cknowledgements. Co-authors QResearch database EMIS & contributing practices & User Group University of Nottingham ClinRisk (software )

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New tools to support decisions and diagnoses

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New tools to support decisions and diagnoses

Julia Hippisley-Cox,

GP, Professor Epidemiology & Director ClinRisk Ltd


06 Sept 2012


  • Co-authors

  • QResearch database

  • EMIS & contributing practices & User Group

  • University of Nottingham

  • ClinRisk (software)

  • Oxford University (independent validation)


  • QSurveillance in EMIS Web

  • QResearch data linkage project/Openpseudonymiser

  • QFracture

  • QCancer

  • QDiabetes - Dr Tim Walter

  • Work in progress

  • Discussion

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 in Enquiry manager

QFeedback in LV

QFeedback for EMIS LV and Web

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

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

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

  • 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

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!”

all LV and Web practices welcome to contribute to both QResearch & QSurveillance


Get switched on

Clinical Research Cycle

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

Current published & validated QScores

Today we will cover three tools

  • QFracture

  • QCancer

  • QDiabetes – Dr Tim Walters

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

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

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

Two new indicators recommended QOF 2013 for Rheumatoid Arthritis

Comparison of QFracture vs 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

QFracture Web calculator

  • Example:

  • 64 year old women

  • History of falls

  • Asthma

  • Rheumatoid arthritis

  • On steroids

  • 10% risk hip fracture

  • 20% risk of any fracture

QScoreson the app store

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

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

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.

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

‘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

Qcancer now predicts risk all major cancers including













Results – the algorithms/predictors

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

Using QCancer in practice – v similar to QRISK2

  • Standalone tools

    • Web calculator

    • 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

  • QCancer – women


    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%

    QCancer – men


    • 64yr old man,

    • Heavy smoker

    • FH GI cancer

    • Loss appetite

    • Recent VTE

    • Weight loss

    • Indigestion


    • 71% risk of no cancer

    • 29% risk any cancer

      • Lung = 9%

      • Pancreas =6%

      • Prostate =2%

      • Other =5%

    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

    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.

    Comparison other cancer risk tools


    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

    • Next steps - pilot work in clinical practice supported by DH

    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


    • 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


    • Already integrated into EMIS Web

    • Evaluation in London and Berkshire

    Preventing type 2 diabetes - risk identification & interventions for individuals at high risk


    Thank you for listeningQuestions & Discussion

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