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

Big Data Analytics in Health CareMaking 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

May 27, 2013eHealth 2013 Conference Copyright © 2013 Canada Health Infoway

2© 2012 Canada Health Infoway Inc.©2013 Canada Health Infoway Inc.

Faculty/Presenter Disclosure

• Presenters: Alex J Mair, Mark Nenadovic

• Relationships with commercial interests:− Nothing to disclose


AgendaBig 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?• “Practice of medicine”

vs. the “science of medicine”

- Promise?- 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.


Web based & Social MediaData

Publication &Reference data

Data Streaming

Unstructured& clinical data

Public & other data

Origin of BDA

− R (Data Mining)

• Key investments and enablers

• Key frameworks

− Cloud

− Natural Language Processing

− Hadoop, MapReduce− Data Streaming


“Big” vs “Small” Data Analytics

2013 Canada Health Infoway Inc.

Mine

Predict & Model

Generate Insights

Information management processes are different than traditional processes

Does not replace traditional analytics capabilities, as it is complementary and feeds results to traditional tools

Experimental, discovery, systemic & predictive

Big Data

Analytics


Economics of BDA in Health Care


Note: Figure used with permission of McKinsey Global Institute


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. IDC White Paper: Survey of Big Data in Canada: Challenging Complacency for Competitive Advantage, December 2012


1


BDA Opportunities in Health CareBuilding 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.



BDA Opportunities in Health CareBuilding 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.



BDA Opportunities in Health CareBuilding 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.



BDA Opportunities in Health CareBuilding 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



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



BDA ReadinessInfoway 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



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



CommunicationsOpportunities toCollaborate Leadership

• Identify champions

• Conduct due diligence to understand BDA

• Share research, lessons learned

• 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

CautiousExecution

• Don’t go it alone

• Look to leverage others’ work

• Collaborate on use case, business cases

Call to Action



Emerging technology resource documents:

https://www.infoway-inforoute.ca/index.php/resources/presentations/emerging-technology

Discussion & questions?




Documents

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