© 2014 IBM Corporation 1

IBM – Big Data for Healthcare Using Data, Analytics and Insight to Improve Health

John Crawford, Healthcare Industry Leader, IBM Europe

6 May 2014

© 2014 IBM Corporation 2

What is Big Data and why is it important?

Characteristics of Big Data

Source: IBM Institute for Business Value, 2012

© 2014 IBM Corporation 3

Foundational

• What happened?

• When and where?

• How much?

Advanced, Predictive

• What will happen?

• What will be the impact?

• Dashboards

• Clinical data repositories

Data integration

Data warehouse

• Basic reporting

• Spreadsheets

Transaction

reporting

• Enterprise analytics

• Evidence-based medicine

• Outcomes analytics

Decision support

analytics

• Personalised healthcare

• Population risk models

• Optimising care systems

Predictive

analytics

Prescriptive

• What are potential scenarios?

• What is the best course?

• How can we pre-empt and

mitigate the crisis?

How is Big Data changing Analytics?

© 2014 IBM Corporation 4

Exploiting Big Data to support Personalised Medicine and Public Health

Capturing and using data enables new insights into populations and individualized care

Analytics innovations

Advanced analytics apply Natural Language Processing and

Artificial Intelligence to complement tools that surface

patterns and anomalies

New platforms Collaborative and mobile technology platforms facilitate a holistic view of the individual and enable new ways to coordinate care delivery

New and numerous

data sources Transactional,

application, mobile, social, care provider,

publications, research, and individual

information

of the world’s data was generated in just

the last two years

90%

expected compound annual growth rate

(CAGR) in the big data marketplace by 2016*

31.7%

*IDC Worldwide Big Data Technology and Services 2012-2016 Forecast, doc #238746, Dec 2012

© 2014 IBM Corporation 5

Big Data & Analytics

5

The State University of New

York (SUNY) Buffalo gains

insights from Big Data to

slow progression of multiple

sclerosis

5

Need

• Researchers needed to quickly build models

using a range of variable types and run them

on a high-performing environment on huge

data sets spanning more than 2,000 genetic

and environmental factors that may contribute

to multiple sclerosis (MS) symptoms

Benefits

• Able to reduce the time required to conduct

analysis from 27.2 hours to 11.7 minutes

• Researchers are empowered to look for

potential factors contributing to the risk of

developing MS

© 2014 IBM Corporation 6

Big Data & Analytics University of Ontario

Institute of Technology

(UOIT) uses Big Data to

improve quality of care for

neonatal babies

Need

• Performing real-time analytics using

physiological data from neonatal babies

• Continuously correlates data from medical

monitors to detect subtle changes and alert

hospital staff sooner

• Early warning gives caregivers the ability to

proactively deal with complications

Benefits

• Detecting life threatening conditions 24

hours sooner than symptoms exhibited

• Lower morbidity and improved patient care

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© 2014 IBM Corporation 7

Big Data & Analytics

7

EuResist GEIE Network

uses Big Data to predict

response of HIV patients to

treatment based on viral

genomics

7

Need

• Predicting best treatment strategy for HIV

sufferers from a cocktail of drugs, comparing

new cases with a database of over 61,000

previous cases, over 150,000 therapy options

and nearly 700,000 viral loads

Benefits

• Using decision support delivers 78% accuracy

in treatment plans

• EuResist prediction engine outperformed 9 out

of 10 human experts in predicting outcome

© 2014 IBM Corporation 8

What is Watson?

© 2014 IBM Corporation 9

Understands natural language

and physician / patient

communication

Adapts and learns from user

selections and responses

Generates and evaluates

evidence-based hypothesis to

improve quality of patient care

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IBM Watson – cognitive computing to transform healthcare