Big data and connected challenges in cardiovascular health

Transcription

1 Big data and connected challenges in cardiovascular health Harry Hemingway FFPH, FRCP Professor of Clinical Epidemiology Director Institute of Health Informatics, UCL Director Farr Institute, London IUCL n UCL Institute of Digital Health 22 June 2015

2 Farr Institute Sanger Institute Crick Institute Turing Institute

3 The Farr vision: Big data target Data Citizen Health Capacity Precision Medicine Platforms People Ethical, social Programmes Tool chain Data Analytics Public Health E-Infrastucture Drug Discovery Partnerships Public Learning Health Care

4 The big data tapestry Weber G, Mandl K, Kohane I, JAMA 2014

5 The big data tapestry Weber G, Mandl K, Kohane I, JAMA 2014

6 William Farr ( ) the original Mr Big Data Compiler of Scientific Abstracts at General Register Office Photo, quote And a Computing and visualisation Hospital outcomes Public health statistics and intervention The first International Classification of Disease (ICD)

7 CALIBER 2 million adults, 5 billion data points from linking 4 sources of EHR Denaxas et al., CALIBER, Intl J Epidemiology 2012 Herrett et al., CALIBER, BMJ 2013 Healthy, GP registration Stable angina Pneumonia hospitalization Myocardial infarction hospitalization See GP for follow-up Death Patient s experience Primary care New patient check: blood pressure, smoking status, alcohol use etc. Diagnosis of stable angina. Blood tests (e.g. cholesterol). Prescription of aspirin, nitrates etc. Diagnosis of myocardial infarction Blood tests, blood pressure. Prescriptions of beta blocker, statin, ACEi etc. Time Sudden death Hospitalization (HES) Admit / discharge dates. Primary diagnosis: Viral pneumonia, not elsewhere classified Admit / discharge dates. Primary diagnosis: Acute myocardial infarction Procedure: Percutaneous coronary intervention Disease Registry (MINAP) ECG, cardiac markers. Diagnosis: STEMI Death Census (ONS) Date of death. Cause: 1) Rupture of abdominal aortic aneurysm 2) Old myocardial infarction

8 What does linked record data look like?

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10 The Farr vision: Big data target Data Citizen Health Capacity Precision Medicine Platforms People Ethical, social Programmes Tool chain Data Analytics Public Health E-Infrastucture Drug Discovery Partnerships Public Learning Health Care

11 Outcomes assessment: importance of linking multiple record sources Herrett et al, CALIBER, BMJ 2013;346:f2350

12 Cardiovascular diseases: lumpers or splitters?

13 How does CVD first present? In the real world, today Abdominal aortic aneurysm 2% Intracerebral haemorrhage 2% Subarachnoid haemorrhage 1% Ventricular arrhythmia/sudden cardiac death 3% MI/Fatal CHD 18% Unstable angina 5% CHD 10% Ischaemic stroke 13% Peripheral arterial disease 11% Transient ischaemic attack 11% George et al CALIBER 2015, in revision Heart failure 12% Stable angina 12% N=1.93 million patients >110K CVD events 5 year median follow-up

14 The Farr vision: Big data target Data Citizen Health Capacity Precision Medicine Platforms People Ethical, social Programmes Tool chain Data Analytics Public Health E-Infrastucture Drug Discovery Partnerships Public Learning Health Care

15 Risk factors have heterogeneous associations with specific CVDs Example: blood pressure

16 Example Abdominal aortic aneurysm and discordance of systolic and diastolic BP associations Rapsomaniki et al CALIBER Lancet 2014

17 Higher resolution epidemiology: type 2 diabetes and 12 CVDs Shah et al CALIBER The Lancet D&E 2014

18 EHR added to omic/imaging biobanked cohorts EHR record linkages for CVD and other disease outcomes EHR Phenotype algorithms

19 EHR added to genomic sequence 100, 000 Whole genome sequences patients with cancer, infections, rare diseases (including cardiac) NHS Transformation Project

20 The Farr vision: Big data target Data Citizen Health Capacity Precision Medicine Platforms People Ethical, social Programmes Tool chain Data Analytics Public Health E-Infrastucture Drug Discovery Partnerships Public Learning Health Care

21 Personalised trajectories..for risk prediction Crowther et al., CALIBER, 2015

22 Using all the data for prediction 1000s of events in one patient cosmos all clinical data over time: Diagnoses, drugs, blood tests, consultations Events Luscombe Lab, CALIBER, 2015

23 The Farr vision: Big data target Data Citizen Health Capacity Precision Medicine Platforms People Ethical, social Programmes Tool chain Data Analytics Public Health E-Infrastucture Drug Discovery Partnerships Public Learning Health Care

24 Global reality: data-free medicine The Learning Health System series Institute of Medicine of the National Academies, 2012

25 Better outcomes Sure But better than what?

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27 Hospitals: NIHR Health Informatics Collaboration

28 A revolution in science? Nearly all that we know about how to maintain and improve our health in general and cardiovascular health in particular comes from an era where data, information and knowledge were Small Simple Sequestered (not shared) Expensive And interrogated in mono disciplines

29 Farr London Investigators CARDIOVASCULAR Mike Barnes, Director of Bioinformatics James Carpenter, Professor of Medical Statistics John Deanfield, Professor of Paediatric Cardiology Mark Caulfield, Professor Clinical Pharmacology Spiros Denaxas, Health Informatics Senior Research Associate Nicholas Freemantle, Professor of Clinical Epidemiol and Biostatistics Harry Hemingway, Professor of Clinical Epidemiology Aroon Hingorani, Professor of Genetic Epidemiology Steffen Petersen, Reader in Advanced Cardiovascular Imaging John Robson, GP, Clinical lead for the Clinical Effectiveness Group Liam Smeeth, Professor of Epidemiology Adam Timmis, Professor of Clinical Cardiology INFORMATICS Anne Blandford, Professor of Human Computer Interaction Peter Coveney, Professor of Physical Chemistry James Freed, Head of Health Intelligence and Standards Dipak Kalra, Professor of Health Informatics John Shawe-Taylor, Professor of Computing Paul Taylor, Reader in Health Informatics Alan Wilson, Professor of Urban Regional Systems MOTHER & CHILD Peter Brocklehurst, Professor of Women's Health Tito Castillo, Chief Operating Officer, LIFE Study Carol Dezateux, Professor of Paediatric Epidemiology Ruth Gilbert, Professor of Clinical Epidemiology Irene Petersen, Senior Lecturer Epidemiology and Medical Statistics Judith Stephenson, Professor of Reproductive and Sexual Health Phil Koczan, Chief Clinical Information Officer Irwin Nazareth, Professor of Primary Care and Population Science Max Parmar, Director of MRC Clinical Trials Unit INFECTION Mike Catchpole, Head of Epidemiology and Surveillance Andrew Hayward, Senior Clinical Lecturer in Infection Richard Pebody, Head of the Seroepidemiology Programme Deenan Pillay, Professor of Virology PHASE 2 CLINICAL WORKSTREAMS Andy Goldberg, Senior Lecturer in Trauma and Orthopaedics Anthony Moore, Professor of Ophthalmology Kathy Pritchard-Jones, Professor of Paediatric Oncology Martin Rossor, Professor of Neurology & Director of DeNDRON

30 Farr Institute s First International Conference, St Andrews, Scotland, Aug 2015

31 Thank you!