1. Copyright © 2013 Canada Health Infoway
Big Data Analytics in Health Care Making Sense and Getting Value from the “Tsunami” of Health Data
Presented by:
Alex J Mair, Director, Architecture
Mark Nenadovic, Group Director
Emerging Technology Group, Canada Health Infoway
eHealth 2013 Conference
Copyright © 2013 Canada Health Infoway
May 27, 2013

2. Faculty/Presenter Disclosure
Presenters: Alex J Mair, Mark Nenadovic
Relationships with commercial interests:
Nothing to disclose

3. Agenda Big Data Analytics in Health Care Setting the context
Introduction to Big Data Analytics
Enablers for Success
Call to Action

4. Data Never Sleeps Consider that the average GP must stay on top of:
10,000+ diseases & syndromes
3,000+ Rx
1,100+ lab tests
PubMed has over 22.6 million records
500K added each year

5. Problem? Promise? “Practice of medicine” vs. the “science of medicine”
Technology...
mitigates human deficiencies; amplifies strengths
increases access to complete, current and synthesized medical and social sciences research

6. “Man versus Machine” Computers excel at:
organizing and recalling information
remembering complex information
integrating and balancing considerations
Computers have larger memories, and make far fewer mistakes than humans.

7. Introduction of Big Data Analytics in Health
The second white paper in the Emerging Technology Profile series
Designed to address Big Data Analytics (BDA) from a Canadian health care perspective
Intended to provide:
Insight on the potential applicability for this new technology
Context for business opportunities and challenges
Encouragement to advance activities in this space

8. BDA Defined
“Big data” characteristics include: high volume, high velocity and variety of types of information that demand cost-effective and innovative forms of information processing.
“Analytics” is the process of examining large amounts of big data to deliver new insights that can enable decisions in real or near real time.

9. Origin of BDA Key frameworks Key investments and enablers
Web based &
Social Media
Data
Hadoop, MapReduce
Data Streaming
Data
Streaming
Key investments and enablers
Cloud
R (Data Mining)
Unstructured
& clinical data
Natural Language Processing
Publication &
Reference data
Public & other
data

10. “Big” vs “Small” Data Analytics
Does not replace traditional analytics capabilities, as it is complementary and feeds results to traditional tools
Mine
Predict & Model
Generate Insights
Big Data
Information management processes are different than traditional processes
Experimental, discovery, systemic & predictive
Analytics
2013 Canada Health Infoway Inc.

11. Economics of BDA in Health Care
Note: Figure used with permission of McKinsey Global Institute
2013 Canada Health Infoway Inc.

12. Current state of BDA in Canadian healthcare
Industry research indicates progress has been slow
Activity is largely on the periphery of health care (i.e., research studies); not yet in mainstream practice
Benefits are still to be proven and documented
Privacy and security are important considerations affecting the pace of adoption
Canada tends to lag behind other countries
Infoway believes
Industry focus, for the last decade, has been on digitizing points of service & the interoperable EHR
Majority of Canadian health care organizations are small; few have the financial scale to fund a BDA program 1
1. IDC White Paper: Survey of Big Data in Canada: Challenging Complacency for Competitive Advantage, December 2012
2013 Canada Health Infoway Inc.

13. BDA Opportunities in Health Care
Building on the EHR investments, Infoway foresees opportunities for BDA to create new insights.
Public and population health solutions
Google.org Flu counts specific search terms in queries to estimate the intensity of flu levels in a geographic area, often learning from the data itself.
2013 Canada Health Infoway Inc.

14. BDA Opportunities in Health Care
Building on the EHR investments, Infoway foresees opportunities for BDA to create new insights.
Public and population health solutions
Google.org Flu counts specific search terms in queries to estimate the intensity of flu levels in a geographic area, often learning from the data itself.
Clinical operations based solutions
Toronto Sick Kids Artemis project uses big data from monitors in real-time to provide insights which allow researchers to predict when a baby is at risk of infection, so that clinicians can intervene to prevent its occurrence.
2013 Canada Health Infoway Inc.

15. BDA Opportunities in Health Care
Building on the EHR investments, Infoway foresees opportunities for BDA to create new insights.
Clinical decision support based solutions
Memorial Sloan-Kettering Cancer Center, use of “Question and Answer” probabilistic algorithms to analyze millions of pages of unstructured text in patient records and medical literature to locate and rank the most relevant answers to diagnostic and treatment-related questions.
Personalized (genomics) care solutions
Use of Genome 1000 and biomarkers investments in cancer care research to predict individual disease risk, enable early detection of disease, and improve diagnostic classification to better inform individualized treatment.
2013 Canada Health Infoway Inc.

16. BDA Opportunities in Health Care
Building on the EHR investments, Infoway foresees opportunities for BDA to create new insights.
Policy and administrative business operations and solutions
Seton Healthcare Family mines unstructured data using natural language processing and search technologies to predict which chronic health failure patients are most at risk for readmission, by identifying known risk factors like smoking, and the lack of social supports, so health professionals can focus their efforts on keeping high risk patients at home
2013 Canada Health Infoway Inc.

17. Predictions re: BDA Gaining Traction
The healthcare transition will start incrementally and develop slowly in sophistication
Early adopters will focus on use case development, experimentation and collaboration
Key areas of application include:
Cancer treatment & genomics
Clinical Decision Support
Streaming data & remote patient monitoring
Predictive analytics
2013 Canada Health Infoway Inc.

18. BDA Readiness Infoway predicts:
Larger health delivery organizations particularly those with a:
Research base
Advanced level of maturity with their EHRS, DW/BI
Established information governance capabilities
HDOs that have demonstrated some practical success with knowledge management initiatives and are ready to take the leap to BDA
2013 Canada Health Infoway Inc.

19. BDA Requires Enablers to Ensure Success
It is more than a technology project.
Business model – sustainability, business case & ROI, in-house vs. hosted service
Governance – appropriate use of patient information, custodianship frameworks
Leadership – vision, strategy roadmap, culture, investment
Skilled resources – mathematical sciences, applied statistics, machine learning, operations research, natural language processing
Information management practices – processes, data collection, knowledge generation, context and visualization
Privacy and security policy – PHI protection, legal, policy, legislation interpretation
Ethics – use, research, legal
2013 Canada Health Infoway Inc.

20. Call to Action Identify champions
Communications
Opportunities to
Collaborate
Leadership
Cautious
Execution
Identify champions
Conduct due diligence to understand BDA
Share research, lessons learned
Don’t go it alone
Look to leverage others’ work
Collaborate on use case, business cases
Address policy, legal, ethics, business model, sharing, legacy issues
Enable a supportive culture, processes, staffing for BDA
Create opportunities to bring together several emerging technologies
Limited scope pilots, solving specific clinical or business problems
Iterative, step-wise investments that limit capital requirements
Evaluate the feasibility and utility of BDA
2013 Canada Health Infoway Inc.

21. Emerging technology resource documents: https://www. infoway-inforoute
Emerging technology resource documents: Discussion & questions?
2013 Canada Health Infoway Inc.