Transforming Health and Life Sciences through Advanced Analytics

Transcription

1 Transforming Health and Life Sciences through Advanced Analytics Jason Burke Managing Director & Chief Strategist SAS Center for Health Analytics & Insights Copyright 2012 SAS Institute Inc. All rights reserved.

2 The Library at Alexandria Opened around 300 BC Unknown quantity, but likely ~300,00 scrolls Created a papyrus shortage and the promotion of parchment Could anyone find anything? Image from Wikipedia.org 2

3 Where are your analytics looking? 3 Image courtesy of

4 Innovation Opportunity Abounds TELEMEDICINE VALUE-BASED BUSINESS MODELS OPEN INNOVATION HIGH-PERFORMANCE ANALYTICS CLOUD COMPUTING EMR GENOMICS NON-TRADITIONAL DATA SOURCES PERVASIVE COMPUTING 4

5 You and 49 friends, enemies, and strangers One pen flashlight each One exit hatch somewhere Hatch is weight activated (over 5,000 lbs.) 5 Image courtesy of

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

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 7

8 The Promise of Health Analytics Health analytics is the domain of advanced analytics focused on providing strategic insights into the interdependencies in health outcomes, profitability, and customer preferences and behaviors. * Improving Health Outcomes Deepening Customer Relationships Strengthening Financial Performance 8 * Burke, J (2011) The Next Era is Here, A Shot in the Arm, SAS Institute

9 A Target Rich Environment 9 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 10

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

12 Do we care about big data or big insights? Image courtesy of 12

13 DATA Issues Storage Structure Timeliness Semantics & Language Validity Reliability Triage Pedigree INSIGHT Issues Innovation Health Outcomes Profitability Productivity Translational Science Customer Intimacy Risk Value 13 Image courtesy of

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? 14

15 15

16 16

17 Hypothesis- or Data-Driven? Theoretical Framework Data Investigation Testable Hypothesis Testable Hypothesis Empirical Study Theoretical Framework Data Investigation Empirical Study HISTORICAL VIEW ALTERNATE VIEW 17

18 Example: Health Outcomes Analysis What Happens with Patients Like This One 18

19 Policy- or Practice-Oriented? Genetic Genomic Profile Genetic Markers Demographics Medications Co-Morbidities Drug Response Broad Groups Subscriptions Social Media Website Traffic TV Habits Geography Purchasing Patterns Individuals Credit Information Adherence Environment & Behavior 19

20 Complexity Exceeds Cognition 20 Image courtesy of

21 Contact Information Jason Burke Copyright 2012 SAS Institute Inc. All rights reserved.