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

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

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

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

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

“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.

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

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.

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

“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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

Emerging technology resource documents: https://www. infoway-inforoute Emerging technology resource documents: https://www.infoway-inforoute.ca/index.php/resources/presentations/emerging-technology Discussion & questions? 2013 Canada Health Infoway Inc.