Transforming Epidemiology in an Era of Big Data and Small Budgets Michael S Lauer, MD, FACC, FAHA Director, Division of Cardiovascular Sciences NHLBI/NIH June 19, 2013 Disclosures: None (I trained at Framingham…) National Heart, Lung, and Blood Advisory Council Meeting
Matthew Fontaine Maury “Depot of Charts and Instruments” “Patterns Everywhere” Inventories of barometers, compasses, sextants, chronometers, log-books, maps, and charts – “rubbish” Standard log forms and “bottles in the sea” Mayer-Schonberger V, Cukier K, Houghton Miflin, 2013
The Result: Data as A Disruptive Technology 1.2 million data points Transformed shipping “Conceived outside traditional academic circles” “Unearthing data from material that no one thought had any value” Data use many times http://www.raremaps.com/gallery/detail/18671?view=print
“Datafication” Anything into data See things on a big scale that cannot be seen on a small one “It will bring fundamental changes” OK to re-use data N = All Mayer-Schonberger V, Cukier K, Houghton Miflin, 2013
Leveraging Data Frolkis J, Lauer MS. N Engl J Med 2003;348:781-90
Take a Step Back “Whether or not the correction of these abnormalities once they are discovered will favorably alter the risk of development of disease, while reasonable to contemplate and perhaps attempt, remains to be demonstrated…” 6 Annals Internal Med 1961;55:33-50
Our Primary Model Develops 1983 1985 1987 1988 1992 1999 2000 2006 1948
Despite New Era, Continued Successes 8
CV Epidemiology Financials (~$160M/Yr) 29 18% RPGs 62 39% Cohort, WHI Contracts Grants other than RPGS 68 43% 9
Big Picture: ($M/Year averages 2009-12) 68 293 309 2% 11% 11% Other Contracts Cohort, WHI Contracts RPGs Grants other than RPGS 2,080 76% 10
Lots of Critics… 11
Transformation is in the Air… “US models are being eclipsed by non-US studies that are much larger, yet considerably less expensive.” “These themes [include] integrating ‘big data’ science into the practice of epidemiology…foster integration with trials.” “A large sample size does not solve every problem. But it allows us to do a lot more, and sometimes it is just what we need.” JAMA 2012;308:1804-5; Cancer Epidemiol Biomarkers Prev 2013;22:508-16; 12 Epidemiology 2013; 24:349-51
An Increasingly Complex World 13 Schadt EE. Nature 2009;461:218-23; Barbabasi A. NEJM 2007;357:404-7
Disruptive Models UK Biobank Danish National Registries HMO, integrated systems Regional opportunities: Delaware, SEER Professional registries: NCDR, GWTG, STS Ontario Health Study Claims data (CMS, Aetna, Optum, MPCD) PCORI 14
Disruption: Investigator-Initiated Grants… Wells JM et al. N Engl J Med 2012;367:913-21 15
Patient-Initiated Internet Research “Attempting to establish the efficacy of a treatment in a prospective manner inevitably draws comparisons with methodologies that have the highest standards of rigor, and by comparison this discipline is in its infancy.” Wicks P et al. Nature Biotechnology 2011;29:411-414 16
Creative (Disruptive) Business Model s L Large LEveraged E Embedded External V aluable I’ Inexpensive Integrated Investments S ound science 17
Next Steps Council BEE Working Group Veronique Roger, Chair Bruce Psaty, NHLBAC BEE members to be named Caroline Fox and David Gordon, NHLBI Preserving investments Short-term renewals of FHS and MESA Note CHS example Consider models for cohorts, other opportunities
Thank You (Incomplete List) Diane Bild Jim Kiley Gary Gibbons Keith Hoots Susan Shurin Denise Bonds Alan Michelson Nakela Cook Paul Sorlie Gail Pearson Richard Fabsitz David Gordon Jean Olson Sonia Skarlatos Gina Wei Denis Buxton Cheryl Jennings Zorina Galis Larry Fine Nancy Geller Yves Rosenberg Chris O’Donnell Denise Simons-Morton Nancy Miller Daniel Levy Richard Hodes Steve Mockrin Deborah Zarin Bob Balaban Francis Collins James Crapo Chris Granger Zak Kohane Robert Califf 19
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