My slides from a recent keynote on how advanced analytics can help transform the health and life sciences industries. To hear the talk track along with the slides, see http://www.jasonburke.us/my-health-analytics-talk

1. Transforming
Health and Life Sciences
through Advanced Analytics
Jason Burke
Principal

2. The Library at Alexandria
• Opened around 300 BC
• Unknown quantity, but likely
~300,000 scrolls
• Created a papyrus shortage
and the promotion of
parchment
Could anyone find anything?
Image from Wikipedia.org

3. Where are your analytics looking?
Image courtesy of http://www.flickr.com/photos/urbanwoodchuck/3941783849

4. Innovation Opportunity Abounds
OPEN
INNOVATION
VALUE-
BASED
BUSINESS EMR
MODELS CLOUD
HIGH- COMPUTING
PERFORMANCE
ANALYTICS NON-
TRADITIONAL
TELEMEDICINE DATA SOURCES
GENOMICS
PERVASIVE
Image courtesy of http://www.flickr.com/photos/ishmaelo COMPUTING

5. You and 49 friends, enemies, and strangers
One pen flashlight each
One exit hatch somewhere
Hatch is weight activated (over 5,000 lbs.)
Image courtesy of http://www.flickr.com/photos/smemon

6. Emerging from the Dark
Alignment of Shared
Incentives & Data &
Goals Insights
Structural
Organization

7. Convergence
The transformations needed in the
healthcare ecosystem require shared
data and insights across previously
siloed markets
(payers, providers, regulators, and
pharma)
An era of collaboration around health analytics

8. The Promise of Health Analytics
Clinical
Health analytics is the domain of
advanced analytics focused on
providing strategic insights into
the inter-dependencies in health
outcomes, profitability, and
preferences and behaviors. *
Patient-
Individual Centered Financial
Health
Operational
* Burke, J (2011) “The Next Era is Here”, A Shot in the Arm, SAS Institute

9. A “Target Rich Environment”
Source: Burke, J., The World of Health Analytics”, in “Healthcare Informatics: Improving Efficiency and
Productivity”, CRC Press, 2010

10. Example:
National Collaborative for Bio-Preparedness

11. Other Examples
Clinical Trials Bundled Contract Health Risk
Optimization Payment Effectiveness Stratification &
Analytics Optimization

12. Do we care about “big data” or “big insights”?
Image courtesy of http://www.flickr.com/photos/strangrthancandy

13. DATA Issues INSIGHT Issues
Storage Innovation
Structure Health Outcomes
Timeliness Profitability
Semantics & Language Productivity
Validity Translational Science
Reliability Customer Intimacy
Triage Risk
Pedigree Value
Image courtesy of http://www.flickr.com/photos/jdhancock

14. PQRI, Meaningful Use, ACO, Medicare, NQF, NCQA, AHRQ…
In an industry with more than
1,000 measures, how will we
know which ones actually
matter?

16. Hypothesis- or Data-Driven?
Theoretical Data
Framework Investigation
Testable Testable
Hypothesis Hypothesis
Empirical Study Theoretical
Framework
Data Empirical Study
Investigation
HISTORICAL VIEW ALTERNATE VIEW

17. Example: Health Outcomes Analysis
What Happens with “Patients Like This One”
Credits: Flickr user jonicdao

18. Policy- or Practice-Oriented?
Genetic
Genomic Profile Genetic Markers
Demographics Medications
Co-Morbidities Drug Response
Broad
Individuals
Groups
Subscriptions Adherence
Credit
Social Media
Information
Purchasing
Website Traffic
Patterns
TV Habits Geography
Environment & Behavior

19. Complexity Exceeds Cognition
Image courtesy of http://www.flickr.com/photos/wonderlane

20. CONTACT INFORMATION
Jason Burke
Web: http://BurkeAdvisoryGroup.com
Blog: http://jasonburke.us
Twitter: @JaBurke
http://twitter.com/jaburke
Credits: Dot pattern by Flickr user vectorportal