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Precisely Practicing Medicine from
700 Trillion Points of
University of California Health Data
Atul Butte, MD, PhD
Chief Data Scientist, University of California Health (UC Health)
Priscilla Chan and Mark Zuckerberg Distinguished Professor
Director, Bakar Computational Health Sciences Institute, UCSF
atul.butte@ucsf.edu ▪ @atulbutte
Conflicts of Interest
• Scientific founder and
advisory board membership
– Genstruct
– NuMedii
– Personalis
– Carmenta
• Honoraria for talks
– Lilly
– Pfizer
– Siemens
– Bristol Myers Squibb
– AstraZeneca
– Roche
– Genentech
– Warburg Pincus
– CRG
– AbbVie
– Westat
• Past or present consultancy
– Lilly
– Johnson and Johnson
– Roche
– NuMedii
– Genstruct
– Tercica
– Ecoeos
– Helix
– Ansh Labs
– uBiome
– Prevendia
– Samsung
– Assay Depot
– Regeneron
– Verinata
– Pathway Diagnostics
– Geisinger Health
– Covance
– Wilson Sonsini Goodrich & Rosati
– Orrick
– 10X Genomics
– GNS Healthcare
– Gerson Lehman Group
– Coatue Management
• Corporate Relationships
– Northrop Grumman
– Genentech
– Optum
– Aptalis
– Allergan
– Astellas
– Thomson Reuters
– Intel
– SAP
– SV Angel
– Progenity
– Illumina
• Speakers’ bureau
– None
• Companies started by students
– Carmenta
– Serendipity
– Stimulomics
– NunaHealth
– Praedicat
– MyTime
– Flipora
– Tumbl.in
– Polyglot
– Iota Health
– Ongevity Health
bit.ly/tmfFDA19
Build the STRONGEST TEAM in the world in
biomedical computation and health DATA INTELLIGENCE
• Academic affinity home for faculty and staff
• Recruit the best computational, informatics and AI faculty and staff to UCSF
• Develop new educational programs
• Provide a research computing platform and operations
• Build and use our data assets for precision medicine
• Research and development (and spin out technologies)
Faculty Recruitments
2015/16
2017/18
2019
2015-17
7
D Torgerson W Brown A Sweet-Cordero U Manber J Adler-Milstein T Goldstein A Raj
Peds DOM, DPM Peds DOM DOM, DHM Hem Onc Radiology
2018-19
7 M Sirota J Hong V Ntranos J Li D Chi B Rosner F Huang
Peds Rad Onc Diabetes Ctr Neurology Dentistry DOM, DHM DOM, Onc
University of California
• 10 campuses and 3 national labs
• ~200,000 employees, ~250,000 students/yr
UC Health
• 18 health professional schools (6 med schools)
• Train half the medical students and residents in
California
• ~$2 billion NIH funding
• $13+ billion clinical operating revenue
• 5000 faculty physicians, 12000 nurses
• UCSF and UCLA are in US News top 10
• 5 NCI Comprehensive Cancer Centers, 5 NIH CTSA
• IRB reliance, centralized contracting
UC Health Data Analytics Platform
Combining healthcare data from across the
six University of California medical schools and systems
Health Data Warehouse
• Combined EHR data from UCSF, UCLA, UC Irvine, UC Davis,
UC San Diego, and UC Riverside
• Total 15 million patients with an MRN, basic diagnosis data
• Central database built using OMOP (not Epic) as a data backend
– Structured data from 2012 to the present day
– 5.1 million patients with “modern” data
– 164M encounters, 124M procedures, 682M med orders, 703M diagnosis
codes, 1.7B lab tests and vital signs,
– OSHPD data, pathology and radiology text elements, death index
– Claims data from our self-funded plans now included
– Continually harmonizing elements
• Quality and performance dashboards
The University of California has an
incredible view of the medical system
Many operational teams within UC Health now
using and benefitting from the UCHDW
• AbbVie Humira
– RA: PREMIER 2 year double-blind, active comparator-controlled, multicenter study, N=799 (542 treated
with Humira)
– RA: DE019 4-week, randomized, double-blind, placebo-controlled, multicenter study, N=619
– IBD: CLASSIC-I 4-week, randomized, double-blind, placebo-controlled, multicenter study, N=299
– IBD: CHARM 56-week randomized, double-blind, placebo-controlled, multicenter study, N=854
– University of California: ~11,000 patients treated with 60,000+ prescriptions/orders/doses
• Celgene Revlimid
– Randomized, multicenter, open-label, three-arm trial, N = 1,623
– University of California: 5,000+ patients treated with 90,000+ prescriptions/orders/doses
• Regeneron Praluent
– ODYSSEY LONG TERM double-blind, placebo-controlled study, N=2,341
– University of California: 1,300+ patients treated with 10,100+ prescriptions/orders/doses
Real world data quickly overpowers pivotal study data
Vivek Rudrapatna
bit.ly/JCIbigdata
Source: American Diabetes Association Standards of Medical Care in Diabetes (2016)
bit.ly/2NKc6dz
bit.ly/2NKda13
146817 tested
5166 positives (3.52% of tested)
1417 admitted to date (27.4% of positives)
117 expired (8.3% of admitted, 2.26% of positives)
• Switched from monthly data feeds to
daily data feeds
• Successfully sharing dashboard
elements and computer code across
campuses
• Harmonizing data elements: linking
Epic programmers with clinicians and
BRAID
• Validate quickly, update often
• Nature of the pandemic means
information flow to many responsible
agencies
23
What did we learn: How to work even more strongly together
24
Follow @UofCAHealth for
these numbers every afternoon
What did we learn: The public wants to see our data
Presentation at ISMB NIH Office of Data Science Strategy Panel

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Presentation at ISMB NIH Office of Data Science Strategy Panel

  • 1. Precisely Practicing Medicine from 700 Trillion Points of University of California Health Data Atul Butte, MD, PhD Chief Data Scientist, University of California Health (UC Health) Priscilla Chan and Mark Zuckerberg Distinguished Professor Director, Bakar Computational Health Sciences Institute, UCSF atul.butte@ucsf.edu ▪ @atulbutte
  • 2. Conflicts of Interest • Scientific founder and advisory board membership – Genstruct – NuMedii – Personalis – Carmenta • Honoraria for talks – Lilly – Pfizer – Siemens – Bristol Myers Squibb – AstraZeneca – Roche – Genentech – Warburg Pincus – CRG – AbbVie – Westat • Past or present consultancy – Lilly – Johnson and Johnson – Roche – NuMedii – Genstruct – Tercica – Ecoeos – Helix – Ansh Labs – uBiome – Prevendia – Samsung – Assay Depot – Regeneron – Verinata – Pathway Diagnostics – Geisinger Health – Covance – Wilson Sonsini Goodrich & Rosati – Orrick – 10X Genomics – GNS Healthcare – Gerson Lehman Group – Coatue Management • Corporate Relationships – Northrop Grumman – Genentech – Optum – Aptalis – Allergan – Astellas – Thomson Reuters – Intel – SAP – SV Angel – Progenity – Illumina • Speakers’ bureau – None • Companies started by students – Carmenta – Serendipity – Stimulomics – NunaHealth – Praedicat – MyTime – Flipora – Tumbl.in – Polyglot – Iota Health – Ongevity Health
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  • 9. Build the STRONGEST TEAM in the world in biomedical computation and health DATA INTELLIGENCE • Academic affinity home for faculty and staff • Recruit the best computational, informatics and AI faculty and staff to UCSF • Develop new educational programs • Provide a research computing platform and operations • Build and use our data assets for precision medicine • Research and development (and spin out technologies)
  • 10. Faculty Recruitments 2015/16 2017/18 2019 2015-17 7 D Torgerson W Brown A Sweet-Cordero U Manber J Adler-Milstein T Goldstein A Raj Peds DOM, DPM Peds DOM DOM, DHM Hem Onc Radiology 2018-19 7 M Sirota J Hong V Ntranos J Li D Chi B Rosner F Huang Peds Rad Onc Diabetes Ctr Neurology Dentistry DOM, DHM DOM, Onc
  • 11. University of California • 10 campuses and 3 national labs • ~200,000 employees, ~250,000 students/yr UC Health • 18 health professional schools (6 med schools) • Train half the medical students and residents in California • ~$2 billion NIH funding • $13+ billion clinical operating revenue • 5000 faculty physicians, 12000 nurses • UCSF and UCLA are in US News top 10 • 5 NCI Comprehensive Cancer Centers, 5 NIH CTSA • IRB reliance, centralized contracting
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  • 14. UC Health Data Analytics Platform Combining healthcare data from across the six University of California medical schools and systems Health Data Warehouse
  • 15. • Combined EHR data from UCSF, UCLA, UC Irvine, UC Davis, UC San Diego, and UC Riverside • Total 15 million patients with an MRN, basic diagnosis data • Central database built using OMOP (not Epic) as a data backend – Structured data from 2012 to the present day – 5.1 million patients with “modern” data – 164M encounters, 124M procedures, 682M med orders, 703M diagnosis codes, 1.7B lab tests and vital signs, – OSHPD data, pathology and radiology text elements, death index – Claims data from our self-funded plans now included – Continually harmonizing elements • Quality and performance dashboards The University of California has an incredible view of the medical system
  • 16. Many operational teams within UC Health now using and benefitting from the UCHDW
  • 17. • AbbVie Humira – RA: PREMIER 2 year double-blind, active comparator-controlled, multicenter study, N=799 (542 treated with Humira) – RA: DE019 4-week, randomized, double-blind, placebo-controlled, multicenter study, N=619 – IBD: CLASSIC-I 4-week, randomized, double-blind, placebo-controlled, multicenter study, N=299 – IBD: CHARM 56-week randomized, double-blind, placebo-controlled, multicenter study, N=854 – University of California: ~11,000 patients treated with 60,000+ prescriptions/orders/doses • Celgene Revlimid – Randomized, multicenter, open-label, three-arm trial, N = 1,623 – University of California: 5,000+ patients treated with 90,000+ prescriptions/orders/doses • Regeneron Praluent – ODYSSEY LONG TERM double-blind, placebo-controlled study, N=2,341 – University of California: 1,300+ patients treated with 10,100+ prescriptions/orders/doses Real world data quickly overpowers pivotal study data Vivek Rudrapatna bit.ly/JCIbigdata
  • 18. Source: American Diabetes Association Standards of Medical Care in Diabetes (2016)
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  • 22. 146817 tested 5166 positives (3.52% of tested) 1417 admitted to date (27.4% of positives) 117 expired (8.3% of admitted, 2.26% of positives)
  • 23. • Switched from monthly data feeds to daily data feeds • Successfully sharing dashboard elements and computer code across campuses • Harmonizing data elements: linking Epic programmers with clinicians and BRAID • Validate quickly, update often • Nature of the pandemic means information flow to many responsible agencies 23 What did we learn: How to work even more strongly together
  • 24. 24 Follow @UofCAHealth for these numbers every afternoon What did we learn: The public wants to see our data