Whats new in Q: Qfeedback, QFracture, QCancer

Julia Hippisley-CoxSessional GP

EpidemiologistDirector QResearch

Director ClinRisk Ltd

EMIS NUG conferenceSeptember 2010Warwick University

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

Update on QSurveillance QFeedback Update on QScores

◦ QIntervention◦ QFracture◦ Qcancer

General discussion

Overview

QSurveillance

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

QSurveillance: Overview

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

QSurveillance data extraction

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)

QSurveillance Governance

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

Governance Principles

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

QSurveillance: pandemic

Qfeedback System

QScores

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

Overview Qscores - disease outcomesDisease outcomes Status

QRISK (CVD) QDScore (diabetes) QFracture QKidney (CKD3b+) Qcancer Range of other

significant outcomes

published published published published completed In progress

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

Overview - risk/benefit interventions

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

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

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.

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

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

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

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

Qintervention www.qintervention.org

QFracture

Osteoporosis major cause preventable morbidity & 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

QFracture: Background

29

30

Patients with Symptomatic Vertebral Fractures

Wake Early

Hard to Stand

Hard to Bend

Daily Analgesia

In Constant Pain

Not Worth Living

0 10 20 30 40 50 60 70 80

% Patients

Scane et al, Osteoporosis Int 1994; 4: 89-92.

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

QFracture: challenge

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

QFracture: development

QFracture vs FRAX comparisonQFracture FRAX

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

64 year old women Heavy smoker Non drinker BMI 20.6 Asthma On steroids Rheumatoid H/O falls

Clinical example

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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%)

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?

Balancing risks vs benefits

QCancer

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

QCancer scores

QCancer ScoresCancers Alarm symptoms

Breast cancer Prostate Colorectal Oesophageal Renal/bladder Lung Ovary Uterus

Breast lump Prostatism Rectal bleeding Dysphagia Haematuria Haemoptysis Abdo pain/distension Post menopausal

bleeding

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 )

Questions Comments Suggestions Feedback

Discussion