KEYNOTE #1:

INTRODUCING THE BIG DATA PHENOMENON AND EXPLORING THE IMPLICATION OF THIS DISRUPTIVE FORCE ON THE STATUS QUOBig Data Insights Group Forum

November, 2012

ABOUT ARIDHIA

Founders:Dr David Sibbald, Professor Andrew Morris, University of Dundee & NHS Scotland

Founders:Dr David Sibbald, Professor Andrew Morris, University of Dundee & NHS Scotland

Multi-disciplinary Team:In-house team includes 60+ clinicians,

computer, data & life scientists working with external Clinical Faculty

Multi-disciplinary Team:In-house team includes 60+ clinicians,

computer, data & life scientists working with external Clinical Faculty

Focus:Integrated chronic disease management, healthcare analytics for system improvement and stratified medicine

Focus:Integrated chronic disease management, healthcare analytics for system improvement and stratified medicine

Clinically led, technology driven

Aim: To improve patient and public health outcomes by improving quality of health services and R&D, while driving down costs

Aim: To improve patient and public health outcomes by improving quality of health services and R&D, while driving down costs

TACKLING HEALTHCARE & TECHNOLOGY CHALLENGES

Integration and analysis of big data accelerates the ability to solve complex healthcare problems and enables stratified

medicine

Connected data solution for chronic disease management across healthcare sectors

Shared Care Clinical Record

Accurate, real-time disease specific data at patient, organisational or population level

Disease Registry

Data integration and analysis for quality improvement, performance management, governance and assurance

Healthcare Analytics

Repository and complex data analysis for linked, de-identified clinical, bioimage, genomic and proteomic data

Research Safe Haven

Condition specific symptom management, self-reporting, monitoring and risk stratification Patient Self Management

EXPLOSION OF DIGITAL DATA

35% of all digital data is

healthcare related

2011

1.8

zettabytes

2020

90 zettabytes

Source: IDC, Digital Universe Study, June 2012

CHRONIC DISEASE IMPACT

The World Economic Forum estimates that chronic

diseases will cost the world economy

$47 trillion over next 20 years

75% of the population has one chronic disease and 50% have two or more conditions

Patients with a chronic disease use > 60% of hospital bed days

75% of patients admitted as medical emergencies have an exacerbation of a chronic condition

The 15% of patients with 3+ chronic conditions account for 30% of total inpatient days

10% patients account for 55% of total inpatient days

75% of the population has one chronic disease and 50% have two or more conditions

Patients with a chronic disease use > 60% of hospital bed days

75% of patients admitted as medical emergencies have an exacerbation of a chronic condition

The 15% of patients with 3+ chronic conditions account for 30% of total inpatient days

10% patients account for 55% of total inpatient days

Diabetes Affects 366 million2010 annual cost: $500 billion2030 annual cost: $6.0 trillion

Cancer 13.3 million new cases/year2010 annual cost: $290 billion2030 annual cost: $458 billion

Cardiovascular disease32 million MIs & CVAs/year2010 annual cost: $863 billion2030 annual cost: $1.04 trillion

COPDAffects 210 million2010 annual cost: $2.1 trillion 2030 annual cost: $4.8 trillion

Reactive rather than proactiveclinical management

CHALLENGES TO INTEGRATED CARE

Organisation-centric rather than patient-centric

Data silos make it difficult to assess quality of care and outcomes across health system

Fragmented services across primary and secondary care

Clinical focus on individual diseases, not multiple diseases

simultaneously

Data often not integrated into national information systems

Little or no chronic disease surveillance

Lack of data sharing agreements

SYSTEM FRAGMENTATION

“ System fragmentation means that

chronically ill patients receive episodic

care from multiple providers who rarely

coordinate the care they deliver.

Because of this structural deficiency,

patients with chronic illnesses receive

only 56 percent of clinically

recommended care.”

K. THORPE, ET AL: “CHRONIC CONDITIONS ACCOUNT FOR RISE IN MEDICARE SPENDING FROM 1987 TO 2006”;

HEALTH AFFAIRS 29 NO. 4 (2010)

MAKING SENSE OF DISEASE-SPECIFIC BIG DATA WORKS

Scottish Care Information Diabetes Collaboration

• Nationwide real-time, web-based national IT solution in support of diabetes patient and clinical activity

• All 247,768 patients with type I and type II diabetes in Scotland have a SCI-DC electronic record

• 8,265 of these patients have agreed to take part in research on diabetes, including clinical trials

• Single care record for all 5,000+ primary, secondary and tertiary clinical care users at the point of care and 4 university research departments

• Integrates data from 1,015 GP practices, 39 hospital- based diabetes clinics, 7 lab systems, national diabetic retinopathy screening system, master patient index plus multiple specialist forms & direct data entry

• Patient self-management via “My Diabetes My Way” website.

Source: Diabetes Care 2008Source: Diabetic Medicine 2009

EVIDENCE OF IMPROVED CLINICAL OUTCOMES

40% reduction in amputations

43% reduction in diabetic retinopathy

JOIN THE REVOLUTION

“If you live in Scotland and suffer from diabetes, you have recently been taking part in a medical revolution.”

SIR MARK WALPORT, THE TIMES, MAY 2011

INFORMATICS CAN HELP….

“..the Department [of Health] estimates that 24,000 people with diabetes die prematurely each year because their diabetes has not been managed effectively.”

“An estimated 80% of the costs of diabetes in the NHS are attributable to the treatment and management of avoidable diabetic complications.

Fewer than one in five people with diabetes have achieved the recommended levels for blood glucose, blood pressure and cholesterol. Failure to carry out these simple checks heightens the risk of diabetic patients developing complications. If people develop complications they are more likely to die early and also cost the NHS more money.”

“…information is not being used effectively by the NHS to assess quality and improve care...”

Public Accounts Committee - Seventeenth Report Department of Health: The management of adult diabetes services in the NHS (22 October 2012)

CONSIDERATIONS: SAFETY & REGULATORY

Data needs to be presented in a clear, unambiguous manner

Clinicians should be aware of data quality and completeness so they can make an informed decision about interpretation

Data should be presented in most appropriate format to avoid misinterpretation

Anything that is seen as clinical decision support will require future regulation – in the interests of patient safety

Increasing recognition of the need for safe clinical systems

CONSIDERATIONS: CULTURAL AND PATIENT

IT companies traditionally very reluctant to share knowledge and information - need for more openness and transparency

Encourage end user feedback so that systems continue to meet needs

Improve bench to bedside time - need for flexible systems that can be adapted to include up to date research findings and translation into clinical care

Enable patients to take more control of conditions - access to their own data; self monitoring/reporting; feedback on delivery of care

Move away from data control by clinical teams/organisations towards patients providing access to information

THE WORLD POPULATION IS GROWING & GETTING OLDER

• Number of people with chronic disease will rise substantially in coming decades

• Changing demographic with ageing population

• Chronic disease disproportionately affects those > 60 years

• Increasing prevalence of key risk factors for developing chronic disease

smoking

obesity

alcohol

lack of exercise

Source: United Nations Population Division 2011

STRATIFIED MEDICINE = BETTER PATIENT OUTCOMES

It will allow us to offer

• The right drug

• To the right patient

• For the right disease

• At the right time

• With the right dosage

• .Minimise adverse reactions .to medications

• .Reduce the costs of clinical .trials by enabling pre-screening .of potential trial participants and .enabling the faster identification .of possible failures

Prevent premature deaths

Enhance quality of life for chronic disease patients

Enable faster recovery

Deliver positive experiences of

care

Prevent avoidable harm

WHERE IT ALL STARTED

• In 1951 James Watson travelled from the United States to work with Francis Crick at Cambridge University

• Watson and Crick used the “Model Building” approach

• They physically built models out of wire, sheet metal, nuts and bolts to come up with the structure of DNA.

Why did they build models?

“Sometimes the fingers can grasp what the mind

cannot” (Biology the Science of Life)

Treatment A

Treatment B

Treatment C

0%

25%

50%

75%

100% Response Rate (%)

FROM TRIAL & ERROR TO PERSONALISED MEDICATIONS

Adapted from Vaidyanathan, Cell 2012;148:1079

Given limited ability to predict responders, doctors practice

trial-and-error medicine

INNOVATIVE TECHNOLOGIES MAKE THIS POSSIBLE

The convergence of big data and life sciences enables healthcare to

become truly patient-centric:

• integrate data-intensive biology with medicine• understand clinical & genetic correlations• genomics has a network effect to catalyze changes

in information technology, medicine, and society

Support research genomics and beyond

Build a more responsive healthcare delivery infrastructure

Support patient self-reporting & management

Enable providers to improve patient care

Transform health data into actionable information

Single Variant (100 Snps; 103 Genotypes)

Detailed Study Of Individual Genes(102 Snps; 105+ Genotypes)

Complete Resequencing (108 Snps / 1012 Genotypes)

TECHNOLOGY IS THE ENABLER

Genome-wide Association (106 Snps; 1010 Genotypes)

Regional Studies (104 Snps; 108 Genotypes )

GENOME-WIDE SCAN FOR TYPE 2 DIABETES

IS IT WORTH STUDYING GENETICS FOR CHRONIC DISEASES?

Diabetes Life Time Risk0 Parent 10%1 Parent 30%Brother/sister 40%Both parents 70%Identical twin 80-100

%

Current Resolution Future Resolution

WE ARE THE START OF THE GENOMICS JOURNEY

OPEN & COMPREHENSIVE COLLABORATION IS KEY

Industry Bioinformatics

Diagnostics

Clinical Research

Biotechnology

NGS

Pharmaceuticals

Therapeutics

AcademiaHealth Informatics

Genetics

Clinical

Biostatistics

Skilled Workforce Training

Government Healthcare Agencies

Policy Makers

• A strong scientific informatics infrastructure with vibrant PHD and post doctorate communities

• Academic health science centres with a tripartite mission and significant infrastructure investment

• A commitment to linking information from medical and non-medical sources using electronic patient records to support better treatment, safety and research

• A new pathway for the regulation and governance of health research

• Collaborative arrangements with the biotechnology pharmaceutical and medical devices industries.

AS COSTS DROP, WE FACE A TIDAL WAVE OF DATA

• Full genome sequence ~£3,000 [2012]• Dropping in price 10x every 2-4 years• Existing NHS genetic test ~£1,000

• Disk cost to store raw sequence ~£100• Disk cost to store individuals variations ~10p

• Needed for accessing, manipulating, visualizing• Requires entirely new perspective• Emergent evidence for clinical validation, clinical utility

and patient stratification Hokusai, K. The Great Wave

Current Costs

Future Approaches

NOW WE HAVE THE GENES…

STRATIFIED MEDICINEThe right medicine to

the right person at the right time

PHYSIOLOGYWhat are the physiological

correlates of these variants?

PHARMACOGENETICSDo these variants also influence complication risk, or response to

available treatments?

CLINICAL MEDICINEDo the variants allow us to predict

disease progression and the effect of lifestyle interventions?

MICROBIOLOGYWhat are the pathogenic

organisms?

GENETIC EPIDEMIOLOGYHow does variation

here interact with variation at other sites?

EPIDEMIOLOGYWhat is the population risk

and are there importantinteractions with exposures?

Confirmedvariants

AHSCsBRUs

HTA

Imaging

Stem cells

Cohorts

Biologics

Biobanks

Chemistry

RNAi

Large trials

Genetics

CRFs

GMP facilities

Stratification

Cyclotrons

Molecular pathology

Biomarkers

High throughput screening

Trial Methodology

Preclinical models

Regulation

Enabling technology

Technology transfer

THE COMPLEX BIG DATA ENVIRONMENT OF MEDICINE

Laboratory data

INTEGRATION OF PATIENT & HETEROGENEOUS DATA

Genomic data

Imaging GP records

Hospital admissions

E-health Record

ARCHITECTURE

2011: STRATIFIED MEDICINES INNOVATION PLATFORM

Technology Strategy Board invests £5.6m in collaborative R&D projects in

“tumour profiling and data capture to improve cancer care by providing cancer specialists with information specific to the patient’s

tumour which will enable more targeted treatment to be provided.”

in partnership with

Inclusion of breast, lung, colorectal, prostate, skin & ovarian cancer patients

DR LUKAS WARTMAN’S STORY

Lukas Wartman, 25 was finishing medical school when he was first

diagnosed with acute lymphoblastic leukaemia.

QUESTIONS?

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