A Successful Academic Medical Center Must be a Truly Digital
Enterprise
Philip E. Bourne, PhD, FACMIAssociate Director for Data Science
National Institutes of Health
Nina Matheson LectureAAMC November 7, 2015
Available on Slideshare
My Experiences
https://commons.wikimedia.org/wiki/File:Geisel_West,_UCSD.JPG
21 Years 1.8 Years
What is My Job?
Change the Culture of NIH
What Do I Do Next Week?
The NIH Data Timeline
6/12 2/14 3/14
• Recommendations:• Sharing data & software through catalogs• Support methods and applications development• Need more training• Need campus-wide IT strategy• Hire CSIO• Continued support throughout the lifecycle
11/15
A Question I ask Myself A Lot…
Are we at a point of deception soon to see a major disruption to our
institutions?
Some Folks Think So…
Evidence:– Google car– 3D printers– Waze– Robotics– Sensors
From: The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson & Andrew McAfee
Example - Photography
DigitizationDeception
Disruption
Demonetization
Dematerialization
Democratization
Time
Vol
ume,
Vel
ocity
, Var
iety
Digital camera invented byKodak but shelved
Megapixels & quality improve slowly; Kodak slow to react
Film market collapses;Kodak goes bankrupt
Phones replacecameras
Instagram,Flickr become thevalue proposition
Digital media becomes bona fide form of communication
We Are At a Point of Deception The 6D Exponential Framework
Digitization of Basic & Clinical Research & EHR’s
Deception
We Are Here
Disruption
Demonetization
Dematerialization
Democratization
Open science
Patient centered health care
For Academic Medical Centers What Are the Implications of Such a Future?
Opportunities exist to improve the efficiency and value of the enterprise
Open collaborative science becomes of increasing importance
The value of data and associated analytics becomes of increasing value to scholarship
Current training content and modalities will not match supply to demand
Balancing accessibility vs security becomes more important yet more complex
For Academic Medical Centers What Are the Implications of Such a Future?
Opportunities exist to improve the efficiency and value of the enterprise
Open collaborative science becomes of increasing importance
The value of data and associated analytics becomes of increasing value to scholarship
Current training content and modalities will not match supply to demand
Balancing accessibility vs security becomes more important yet more complex
Hypothetical Example of That Value Jane scores extremely well in parts of her graduate on-line neurology class.
Neurology professors, whose research profiles are on-line and well described, are automatically notified of Jane’s potential based on a computer analysis of her scores against the background interests of the neuroscience professors. Consequently, professor Smith interviews Jane and offers her a research rotation. During the rotation she enters details of her experiments related to understanding a widespread neurodegenerative disease in an on-line laboratory notebook kept in a shared on-line research space – an institutional resource where stakeholders provide metadata, including access rights and provenance beyond that available in a commercial offering. According to Jane’s preferences, the underlying computer system may automatically bring to Jane’s attention Jack, a graduate student in the chemistry department whose notebook reveals he is working on using bacteria for purposes of toxic waste cleanup. Why the connection? They reference the same gene a number of times in their notes, which is of interest to two very different disciplines – neurology and environmental sciences. In the analog academic health center they would never have discovered each other, but thanks to the Digital Enterprise, pooled knowledge can lead to a distinct advantage. The collaboration results in the discovery of a homologous human gene product as a putative target in treating the neurodegenerative disorder. A new chemical entity is developed and patented. Accordingly, by automatically matching details of the innovation with biotech companies worldwide that might have potential interest, a licensee is found. The licensee hires Jack to continue working on the project. Jane joins Joe’s laboratory, and he hires another student using the revenue from the license. The research continues and leads to a federal grant award. The students are employed, further research is supported and in time societal benefit arises from the technology.
From What Big Data Means to Me JAMIA 2014 21:194
How to Get There?
Recognize an institutions assets are increasingly digital
Recognize the value of those assets
Recognize that those assets are siloed
Put in place a governance, financial and infrastructure model that breaks down those silos while maintaining community trust
That is, protect the integrity of the assets
http://cdn.makeagif.com/media/4-01-2014/Km_F3w.gif
Today’s Data Landscape
EducationalData
AdministrativeData
PreclinicalResearch
Data
ClinicalResearch
Data
Consider the NIH Governance Model
NIH Director
Scientific Data Council
Working Groups
Advisory Committee
Example Work Product
NIH Genomic Data Sharing (GDS) Policy
Purpose– Sets forth expectations, responsibilities that ensure broad,
responsible sharing of genomic research data in a timely manner
Scope– All NIH-funded research generating large-scale human or
non-human genomic data – and their use for subsequent research
• Data to be submitted to NIH-designated data repositories (e.g., dbGaP, GEO, GenBank, WormBase, FlyBase, Rat Genome Database)
– Applies to all funding mechanisms (grants, contracts, intramural support) with no minimum threshold for cost
Released August 2014; effective January 25, 2015
gds.nih.gov
Other Areas I Hope the SDC Will Address
Sharing of other data types
Machine readable data sharing plans
Data citation
For Academic Medical Centers What Are the Implications of Such a Future?
Opportunities exist to improve the efficiency and value of the enterprise
Open collaborative science becomes of increasing importance
The value of data and associated analytics becomes of increasing value to scholarship
Current training content and modalities will not match supply to demand
Balancing accessibility vs security becomes more important yet more complex
Laying the Foundation for Open Access:
HGP, Bermuda, 1996
“The HGP changed the norms around data sharing in biomedical research.”
Data Sharing Goes Global: GA4GHGlobal Alliance for Genomics and
Health Accelerating the potential of genomic medicine to
advance human health, by:– Establishing common framework of approaches to enable
effective, responsible sharing of genomic and clinical data– Catalyzing data sharing projects that drive and demonstrate
value of data sharing Alliance*: >350 leading institutions (healthcare, research,
advocacy, life science, IT) representing 35 countries Working groups (Clinical, Data, Security, Regulatory &
Ethics) assess, prioritize needs– Form task teams to produce tools, solutions, demonstration
projects
*Statistics as of October 5, 2015
A Culture of Sharing
1999 20042003 2007 20142008
Research Tools Policy
NIH Data Sharing Policy
Model Organism Policy
Genome-wide Association (GWAS) Policy
2012
NIH Public Access Policy (Publications)
Big Data to Knowledge (BD2K) Initiative
Genomic Data Sharing (GDS) Policy
Modernization of NIH Clinical Trials
White House Initiative
(2013 “Holdren Memo”)
Guiding Principle of NIH GWAS Policy
The greatest public benefit will be realized if data from GWAS are made available, under terms and conditions consistent with the informed consent provided by individual participants, in a timely manner to the largest possible number of investigators.
NIH expectation that data would be shared in the NIH database of Genotype and Phenotype (dbGaP)
Data Access Requests Per Year 2007–September 2015
A Culture of Sharing
1999 20042003 2007 20142008
Research Tools Policy
NIH Data Sharing Policy
Model Organism Policy
Genome-wide Association (GWAS) Policy
2012
NIH Public Access Policy (Publications)
Big Data to Knowledge (BD2K) Initiative
Genomic Data Sharing (GDS) Policy
Modernization of NIH Clinical Trials
White House Initiative
(2013 “Holdren Memo”)
NIH Public Access Policy for Publications
Ensures public access to published results of all research funded by NIH since 2008– Recipients of NIH funds required to submit final peer-
reviewed journal manuscripts to PubMed Central (PMC) upon acceptance for publication
– Papers must be accessible to the public on PMC no later than 12 months after publication
A Culture of Sharing
1999 20042003 2007 20142008
Research Tools Policy
NIH Data Sharing Policy
Model Organism Policy
Genome-wide Association (GWAS) Policy
2012
NIH Public Access Policy (Publications)
Big Data to Knowledge (BD2K) Initiative
Genomic Data Sharing (GDS) Policy
Modernization of NIH Clinical Trials
White House Initiative
(2013 “Holdren Memo”)
Harnessing Data to Improve Health: BD2K (Big Data to Knowledge)
NIH’s 6-year initiative to use data science to foster an open digital ecosystem that will accelerate efficient, cost-effective biomedical research to enhance health, lengthen life, and reduce illness and disability
Programs and activities:Advance discovery for biomedical researchFacilitate use and re-use of biomedical dataDevelop analytical methods and softwareEnhance biomedical data science training
BD2KCenter
BD2KCenter
BD2KCenter
BD2KCenter
BD2KCenter
BD2KCenter
DDICC
Software
Standards
Infrastructure - The Commons
Labs
Labs
Labs
Labs
The Commons: Components
The CommonsDigital Object Compliance: FAIR
Attributes of digital objects in the Commons Initial Phase
• Unique digital object identifiers of some type• A minimal set of searchable metadata • Physically available in a cloud based Commons provider• Clear access rules (especially important for human subjects data)• An entry (with metadata) in one or more indices
– Future Phases• Standard, community based unique digital object identifiers • Conform to community approved standard metadata for enhanced
searching• Digital objects accessible via open standard APIs• Are physically and logical available to the commons
For Academic Medical Centers What Are the Implications of Such a Future?
Opportunities exist to improve the efficiency and value of the enterprise
Open collaborative science becomes of increasing importance
The value of data and associated analytics becomes of increasing value to scholarship
Current training content and modalities will not match supply to demand
Balancing accessibility vs security becomes more important yet more complex
Avoid The Google Bus
BD2K and Clinical Data Science Research
BD2K Centers of Excellence for Big Data Computing
BD2K Targeted Software Topics
Challenges and Prizes1. NIH-NSF IDEAS Lab
• Promotes New Collaborations • Round 1 on Precision Medicine (August 2015), round 2 in
planning.
2. BD2K-Wellcome Trust-HHMI Open Science Prize• Prize competition announced October 20, 2015.• Supports development of technology platforms and tools that
make open biomedical data more discoverable, accessible, analyzable, and citable
BD2K Targeted Software TopicsSupports innovative analytical methods and software tools that address critical current and emerging needs of the biomedical research 2015 Topics (18 awards, U01s)
– Data Compression– Data Provenance– Data Visualization– Data Wrangling
2016 Topics (U01s, under review)– Data Privacy– Data Repurposing– Applying Metadata
– 2016: Crowdsourcing and interactive Digital Media (UH2)
For Academic Medical Centers What Are the Implications of Such a Future?
Opportunities exist to improve the efficiency and value of the enterprise
Open collaborative science becomes of increasing importance
The value of data and associated analytics becomes of increasing value to scholarship
Current training content and modalities will not match supply to demand
Balancing accessibility vs security becomes more important yet more complex
The BD2K Training and Diversity Landscape
For Academic Medical Centers What Are the Implications of Such a Future?
Opportunities exist to improve the efficiency and value of the enterprise
Open collaborative science becomes of increasing importance
The value of data and associated analytics becomes of increasing value to scholarship
Current training content and modalities will not match supply to demand
Balancing accessibility vs security becomes more important yet more complex
The Problem Statement
Access to digital research objects when, how, and by whom are authorized to access them in
accordance of the wishes of the owner and/or laws and policies which
define accessibility
The Landscape
The Holdren Memo
Revisions to the Common Rule
Meaningful Use
Centralized IRBs
….
Let Me Close on A Promising Note
“And that’s why we’re here today. Because something called precision medicine … gives us one of the greatest opportunities for new medical breakthroughs that we have ever seen.”
President Barack ObamaJanuary 30, 2015
An Example of That Promise:Comorbidity Network for 6.2M Danes
Over 14.9 Years
Jensen et al 2014 Nat Comm 5:4022
I not only use all the brains I have, but all I can borrow.
– Woodrow Wilson
The Team
45
NIHNIH……Turning Discovery Into HealthTurning Discovery Into Health
[email protected]://datascience.nih.gov/
http://www.ncbi.nlm.nih.gov/research/staff/bourne/
A Culture of Sharing
1999 20042003 2007 20142008
Research Tools Policy
NIH Data Sharing Policy
Model Organism Policy
Genome-wide Association (GWAS) Policy
2012
NIH Public Access Policy (Publications)
Big Data to Knowledge (BD2K) Initiative
Genomic Data Sharing (GDS) Policy
Modernization of NIH Clinical Trials
White House Initiative
(2013 “Holdren Memo”)
A Culture of Sharing
1999 20042003 2007 20142008
Research Tools Policy
NIH Data Sharing Policy
Model Organism Policy
Genome-wide Association (GWAS) Policy
2012
NIH Public Access Policy (Publications)
Big Data to Knowledge (BD2K) Initiative
Genomic Data Sharing (GDS) Policy
Modernization of NIH Clinical Trials
White House Initiative
(2013 “Holdren Memo”)
Modernizing NIH Clinical Trials Activities:The Need
NIH-Funded trials published within 100 months of completion
Less than 50% published within 30 months of completion
BMJ 2012;344:d7292
Modernizing NIH Clinical Trials Activities:
Call to Action
Increasing Clinical Trial Transparency Proposed November 2014; Final Spring 2016 (est.)
Notice of Proposed Rulemaking: Clinical Trials Registration and Results Submission (FDAAA, Section 801)– Further implements statutory requirements on private and
public sponsors to register; report results on phase 2, 3, and 4 trials
– Includes drugs, biologics, and devices (except small feasibility)
Draft NIH Policy on Clinical Trial Information Dissemination – Extends Section 801 requirements to all NIH-funded clinical
trials– Includes phase 1 trials and trials of non-FDA regulated
interventions such as behavioral trials
Consider This Response from 3 Intersecting Perspectives
Community Policy
Infrastructure
BD2K Targeted Software Topics
Supports innovative analytical methods and software tools that address critical current and emerging needs of the biomedical research 2015 Topics (18 awards, U01s)
– Data Compression– Data Provenance– Data Visualization– Data Wrangling
2016 Topics (U01s, under review)– Data Privacy– Data Repurposing– Applying Metadata
– 2016: Crowdsourcing and interactive Digital Media (UH2)
Why Revisions to the Common Rule
is not sufficiently risk-based, resulting in both over- and under-regulation of research activities;,,
is not tailored to new and emerging areas of research, including social and behavioral research and research involving the collection and use of genetic information Infectious Disease Society of America. Grinding to a halt: The effects of the increasing regulatory burden on research and quality improvement efforts.
may not effectively inform subjects of psychological, informational, or privacy risks;,, ,
does not adequately account for the needs of a “learning” health-care system for continual quality improvement;,, and
provides insufficient mechanisms to ensure the consistency, quality, and accountability of IRB decision-making.,,,
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