The document discusses big data analytics opportunities, enablers, challenges and risks in healthcare. It provides examples of big data analytics being used successfully in healthcare settings to predict disease outbreaks, detect infections in premature babies, assist with cancer treatment selection, and predict hospital readmissions. Key enablers for big data analytics include appropriate governance, skills, and technical infrastructure. While progress has been slow, big data analytics is gaining traction in healthcare with early applications including cancer, chronic disease management, remote patient monitoring and predictive analytics.
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Big Data Analytics in Healthcare - Opportunities and Challenges
1. Big Data Analytics -
Opportunities, Enablers,
Challenges and Risks to
Consider in Health Care
Presented by:
Alex J Mair
Emerging Technology Group
June 20, 2013
Big Data Innovation Summit, Toronto,
Ontario
2. Agenda
• Infoway Background and Context
• BDA health care characteristics
• Economics, opportunities and examples
• Challenges and Assertions
• Call to action specific to healthcare
• Summary
• Questions
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3. Canada Health Infoway
• Created in 2001
• $2.1 billion in federal funding
• Independent, not-for-profit corporation
• Accountable to 14 federal/provincial/territorial
governments
Mission:
Fostering and accelerating the development and adoption of
electronic health information systems with compatible standards
and communications technologies on a pan-Canadian basis with
tangible benefits to Canadians. Infoway will build on existing
initiatives and pursue collaborative relationships
in pursuit of its mission.
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4. Mission
• The mission of the ETG is to identify, assess and promote
viable emerging and disruptive information and
communication technologies that can be used to support the
health care system in Canada. Demonstrations of promising
solutions are facilitated and evaluated for value and benefit to
the health system. Analyses of investigations and
recommendations are communicated to our public and private
stakeholders
Vision
• Emerging technologies are appropriately and effectively used
in promoting the health of Canadians and the sustainability of
the health care system
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Emerging Technology Group –
Mission and Vision
5. 5
The Blueprint - “Key Enabler”
- Used to define and scope over 387 EHR-related
projects across Canada
- Representation of a conceptual Blueprint for
interoperable EHR Solutions in Canada
- Jurisdictions use this Blueprint and underlying
concepts to adapt to their specific implementation of
EHR solutions
- Concept of Service Oriented Architecture
- Registries, Domain Repositories, Health Information
Access Layer (HIAL)
- Privacy & security designed into solutions, change
management implications considered for it’s use
2013 Canada Health Infoway Inc.
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6. Health information is the context for
delivering enhanced collaborative and
coordinated care experiences.
Point of service systems and mobile
devices are the platforms for effective
social networking and new ways of work.
The health IT eco-system links people to
their work and each other in new and
unexpected ways.
Digital health infostructure as
Software-as-a-Service in the cloud
enables delivery of information and
functionality to users and systems.
Nexus of forces in digital health
The forces of the Nexus are intertwined to create a
user-driven ecosystem for digital health.
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8. Big Data Analytics in Health White Paper
• 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
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9. 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
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10. “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
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11. 2013 Canada Health Infoway Inc.
Specific to health care, new types of data becoming available
for use by BDA
• Genomic data - new gene sequencing data being made
available
• Streamed data - home monitoring, telehealth, handheld and
sensor-based wireless and smart devices
• Web and social networking-based data - search engines,
internet consumer use and data from social networking sites
• Health publication and clinical reference data - text-based
publications (clinical research and medical reference material)
and clinical text based reference practice guidelines and health
product (e.g., drug information) data
• Clinical data – 80% unstructured documents, images, clinical
or transcribed notes
• Business, organizational and external data - data which
previously has not been linked such as financial, billing,
scheduling, administrative and non-health data such as
environmental data
Big Data - New Sources of Health Data
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12. Economics of BDA in Health Care
2013 Canada Health Infoway Inc.
Note: Figure used with permission of McKinsey Global Institute
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13. 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
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14. • Big Data - weekly, millions of users search Internet for
health information online
• Functionality or Scope – how can search data be
leveraged for predicting disease outbreaks
• Analytics - gathers data from Google search, estimates
how much flu is circulating in different countries and regions
across the world, determines flu activity levels
• Outcomes - detects regional outbreaks of influenza weekly
- gets smarter, producing higher-quality predictions, and
faster, as it ingests more data
Google.org Flu
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15. • Big Data - 1,000+ recordings per second of measures such
as body temperature, heart & respiratory rate and blood
pressure
• Functionality or Scope - hospital-acquired infections a
serious issue, premature babies (both immature and
inexperienced immune systems), late onset neonatal sepsis
(LONS) can be deadly unless acted on fast
• Analytics - real-time analytics and algorithms predict when
baby is at risk of infection by detecting subtle changes in
measures
• Outcomes - physicians alerted of life-threatening infection
before signs of illness, intervening an hour earlier,
improving outcomes dramatically, such as shorter hospital
stays and reduced costs
Toronto Sick Kids – Artemis
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16. • Big Data – million+ inpatients and outpatients over 20 years
- 80% of data unstructured, along with significant # medical
journals and research
• Functionality or Scope – too much data for clinician to
read, 2,000+ order sets to choose from for cancer treatment
- determining the best fit for each patient no easy task
• Analytics - Watson, cloud based service uses probabilistic
algorithms to analyze millions of pages of unstructured text
in patient records and the medical literature - locates most
relevant answers, while understanding expressions in the
English language
• Outcomes - helps oncologists by following the protocol and
providing a list of diagnostic and treatment options for
physicians to choose from, with confidence ratings for each
option
Memorial Sloan-Kettering Cancer Center–
Question and Answer
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17. • Big Data - 80% of data unstructured - physician notes,
registration forms, discharge summaries and other medical
documents
• Functionality or Scope - 500,000 new cases of congestive
health failure (CHF) diagnosed every year and more than
half of patients are readmitted within six months after
treatment
• Analytics - mines unstructured data using natural language
processing and search technologies to predict patients at
most risk for readmission, based on risk factors
• Outcomes - combined with structured data, provides a
more accurate picture of trends, patterns and deviations,
supporting clinician treatment decisions and predicting
probability of a person's readmission to the hospital
Seton Healthcare Family – Natural Language
Processing
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18. • Big Data - largest dataset of human genetic variation
available on Amazon Web Services (AWS) cloud,
researchers pay for computing services
• Functionality and Scope – BioMe program - 25,000
people participating in DNA sequencing and longitudinal
studies related to data embedded in their EHRs
• Analytics – identification and development of biomarkers
which can predict individual disease risk, early detection of
disease, and improved diagnostic classification to better
inform individualized care
• Outcomes – decision support engine delivers knowledge
based on genetic variants informed by the patients geotype
data and longitudinal clinical data sourced from their EHR
Mount Sinai Medical Center of NYC -
Personalized Care (Genomics)
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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
• Operational – new experimental & data driven knowledge
management approaches
• Information management practices – processes, data
collection, data quality, knowledge generation, context and
visualization
• Privacy and security policy – PHI protection, legal, policy,
legislation interpretation
• Ethics – use, research, legal
• Technical and infrastructure - availability, flexibility,
performance, scalability and usability
2013 Canada Health Infoway Inc.
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20. Infoway Predictions: BDA Gaining Traction
• The healthcare transition will start incrementally
and develop slowly in sophistication
− Cautious, business case driven
− Early adopters will focus on use case development,
experimentation and collaboration
• Key areas of application include:
− Cancer treatment & genomics
− Clinical Decision Support (Chronic Disease Management,
1% or 5% at risk populations)
− Streaming data & remote patient monitoring
− Predictive analytics
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21. Infoway predictions: BDA Readiness
• 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
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22. Communications
Opportunities to
Collaborate 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
Cautious
Execution
• Don’t go it
alone
• Look to
leverage
others’
work
• Collaborate
on use
case,
business
cases
Call to Action
2013 Canada Health Infoway Inc.
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23. Synopsis of Key Messages
• Big Data ≠ Small data
• Visualization and contextualization
• Skills Shortage
• Governance and privacy
• Applying science to medicine
• It’s not just about the data or IT
• Standards
• Canada is behind the curve
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For this slide, the key here is contextualization, visualization. Data and analytics on that data is no good if it can’t be put in front of clinicians, administrators and operators and acted on… Visualize into clinical value….
Put a note in about EHR AND EMR DATA
Much of BDA is still to be proven or documented Barriers such as privacy and security are slowing down adoptionActivity on the periphery of health care (i.e., in research studies) and not yet in mainstream practiceNo production ready solutions yetLots of different vendors, products and approaches Those that have invested, its been larger Canadian health care organizations, as few have the financial scale to fund a BDA program
What is the connection between search queries and flu outbreaksCan the use of aggregated search data track the flu in "near real-time" More flu-related searches during flu season, more allergy-related searches during allergy season, and more sunburn-related searches during the summer.Not a replacement for traditional data from health agencies, but rather as a complement that can help public health officials detect disease outbreaks early on, and hopefully limit the number of people affected.Detects regional outbreaks of influenza 7–10 days before conventional Centers for Disease Control and Prevention Surveillance systems.Traditional disease outbreak systems limited to a single country, vs Google near-global reach. January 2008, detected a significant increase in flu activity in the U.S. mid-Atlantic region. By comparison, published CDC reports were about two weeks behind, and hadn't yet shown this increase. January 8, 2013, Google listed flu activity in the U.S. as "intense," in line with CDC reports of severe flu outbreaks across much of the country. System gets smarter, producing higher-quality predictions, faster, as it ingests more data.
Seton "Hospitals are penalized [by Medicare] for having too many patients who need to be readmitted,".With 1.9 million people in central Texas, Seton looking for a way to reduce readmissions for patients with congestive heart failure (CHF), which was costly -- to the tune of an estimated $35 billion in the United States."This has the potential to reduce the need to provide a data field for every possible piece of data and of making everyone type everything into every single field ... which drives people up a wall. Intuitively we believe there is a cost benefit.“"Highly skilled clinicians are spending inordinate amounts of time entering data into structured fields and this can reduce the time and effort it takes."
Outcomes / BenefitsMany of the lessons being learned in oncology, however, should be applicable to other chronic diseases. In just two weeks, Dr. Hide Winston Hide, associate professor of bioinformatics at Harvard School of Public Health, joined a cancer database with a stem cell dataset—and got a big payoff. “We discovered a single gene that we think is responsible for the initiation of a whole class of leukemia's.” states Dr. Hide. This past summer, Dr. Stephen Sherry, Chief of the National Center Biotechnology Information, was able to confirm a recent discovery of a rare genetic mutation that may offer protection against Alzheimer’s disease.
Communications:Identify champions – Invest in their developmentConduct due diligence to understand BDA -- How it fits into health strategy?Share research – share lessons learnedCommunicate what BDA is aboutIdentify internal champions from the clinical, business and technical professions. Invest in their learning and development.Education on what it is, what its impacts may beAssess the lessons learned from initial BDA pilots to understand how to approach future investments, experiment with analytics, determine resource and skill requirements, and determine changes to data collection processes.Opportunities to collaborateDon’t go it alone or start from scratch Look to leverage work done elsewhere Look for private/public partnerships & research opportunitiesCollaborate on use case, business casesDon’t go it alone. Join or form communities of interest especially with peers in your sector. Form partnerships with trusted public and/or private sector organizations that have common interests, experience, BDA solutions and services.Understand how to leverage and invest in the BDA research agenda in Canada, especially as it applies to health.LeadershipLook to understand how leverage EHRS and health analyticsCreate opportunities to bring together several emerging technologies such as cloud computing, mobile health, remote patient monitoring, big data analyticsAddress policy, legal, ethics, business model, sharing, legacy issuesEnable a culture, processes, staff for BDAData policies. As an ever larger amount of data is digitized and travels across organizational boundaries, there are policy issues that will become increasingly important, including, but not limited to: privacy, security, intellectual property and liability.Legacy technology and techniques. Today, legacy systems and incompatible standards and formats prevent the integration of data and sophisticated analytics that can create value. Organizations will need to deploy or refresh those technologies.Business and operational models. Those models that tackle the cost curve head-on must be prioritized over going it alone with in-house programs. Outsourced cloud computing services for BDA should be evaluated. Culture of innovation and experimentation. Increasingly, organizations will need to acquire access to third-party data sources and integrate this external information with their own, to capture the full potential of big data. Enabling experimentation to discover needs and to improve performance requires cultural alignment around innovation. Look for new greenfield opportunities where innovative technologies may come together (e.g., remote patient monitoring devices that transmit sensor data to the cloud where BDA is used to process it).Cautious ExecutionLimited scoped pilots, solving specific clinical or business problems, while allowing for some experimentationIterative, step-wise investments that limit capital requirements and allow the organization to study the feasibility and utility of BDAFocus initial efforts on developing or adapting other health delivery organizations’ use cases, business cases, strategies and road maps, data governance, privacy and security approaches, and BDA deployment models.In the immediate to Near termUse cases, benefits, ROI, business casesUnderstand implications of rolling out across enterprise, externally, sustainabilityCollaboration on sharing, successes, communicationsIn the Mid to longer termFor areas where ROI and business cases evidentStart looking at P&S, policy, enablers - enterprise, externally, sustainabilityFrameworks for rolling out, sustainabilityInfoway will regularly monitor, review, validate, and adapt evolving BDA strategies and best practices for the digital health community in Canada by monitoring and reporting on:Investments in BDA internationally and their impacts on the Canadian health care market. The U.S. has invested heavily in BDA and has targeted the U.S. health care sector for significant improvements. IT vendor investments in BDA solution offerings. Multi-national and domestic vendors that operate in Canada may be impacted by these investments. BDA developments in the Canadian health care marketplace.