Data Sharing: Biomedical Research Data versus Personal Health Data

1
Data Sharing Biomedical Research Data versus
Personal Health Data

• Belinda Seto, Ph.D.
• Deputy Director
• National Institute of Biomedical Imaging and
  Bioengineering

2
President Obamas Health IT Vision

• A secure, nationwide, interoperable health
  information infrastructure that will connect
  providers, consumers, and others involved in
  supporting health and healthcare.

3
Nationwide Health Information Network

• Improve coordination of care across providers
• Ensure that consumers health information is
  secure and confidential
• Enable consumers control and decision making
• Reduce risks from medical errors
• Enable evidence-based decision support systems
• Lower health care costs

4
Healthcare is the Largest Sector of the Economy
Medicare alone is currently 3.2 of GDP and
increasing rapidly!
BCBS Medical Cost Reference Guide 2008
5
National Health Expenditure (NHE), 2003-2015
The NHE is projected to increase by more than 70
percent between 2007 and 2015, with healthcare
expected to account for almost 20 percent of GDP.
BCBS Medical Cost Reference Guide 2008
6
Projected Growth in Imaging Procedures, US Market
1998-2008

• The use of diagnostic imaging is increasing
  rapidly.

BCBS Medical Cost Reference Guide 2006
7
Aggregate Imaging Growth Was the Fastest for
Physician Services 1999-2004
8
Image Data Sharing NIBIB Activities

• Contract awarded to Radiological Society of North
  America Image Sharing Network, PI Dr. David
  Mendelson
• Grant awarded to Wake Forest University
• Grant awarded to University of Alabama

9
Wake Forest Project

• Develop a patient controlled platform for medical
  image sharing
• Test a model using electronic keys to access data
  
• Integrate image data with electronic health
  records
• Include imaging facilities in rural and urban
  southeast U.S.

10
Alabama Project

• Establish regional health image exchange system
  among hospitals in Alabama
• Design a web accessible point for physicians and
  patients to view images
• Adopt standards of National Health Information
  networks, 2007
• Initial targeting trauma patients
• Scalable

11
Health Information Technology (HIT) The Means
toward Better Care

• HIT is not the end itself but a means to
  improving quality of health care, Dr. David
  Blumenthal
• Data is the fuel that drives HIT

12
Data Sharing to Support Better Decisions
13
Decision Support in Health Information Systems

• Patient data need to be integrated and assessed
  to provide real-time, point-of-care information
  regarding the right care
• Improves clinical decision support with enriched
  data
• Develop algorithms to use comparative
  effectiveness findings to optimize outcomes

14
Comparative Effectiveness Research

• Purpose to improve health outcomes by providing
  evidenced-based information to patients and
  providers.
• Mandate to conduct study of outcomes and to
  derive conclusions to inform medical
  choices/decisions.

15
Cost Savings from Clinical Decision Support System
Health Care Savings
Health Information Exchange
Clinical Decision Support
EHR
16
Sharing Research Data

• Open access no personal health data, no
  identifiers
• Tiered access data use agreements

17
PHS Grants Policy StatementApril 1994
Restricted availability of unique resources upon
which further studies are dependent can impede
the advancement of research and the delivery of
medical care. Therefore, when these resources are
developed with PHS funds and the associated
research findings have been published or after
they have been provided to the agencies under
contract, it is important that they be made
readily available for research purposes to
qualified individuals within the scientific
community. This policy applies to grants,
cooperative agreements, and contracts.
18
NIH Data Sharing Policy
Effective with October 1, 2003 receipt date for
NIH applications

• NIH expects timely release and sharing of final
  research data for use by other researchers.
• NIH expects grant applicants to include a plan
  for data sharing or to state why data sharing is
  not possible, especially if 500K or more of
  direct cost is requested in any single year
• NIH expects contract offerors to address data
  sharing regardless of cost

19
Data Sharing Models

• NIH serves as central data repository
• A federated model with grantee institutions
  provide data repositories

20
NIH Central Data Repositories

• Genome-wide association study
• GenBank
• Protein Cluster
• PubChem
• Many others at http//www.nlm.nih.gov/databases/

21
Alzheimer Diseases and Neuroimaging Initiative
22
Goals of the ADNI Longitudinal Multi-Site
Observational Study

• Major goal is collection of data and samples to
  establish a brain imaging, biomarker, and
  clinical database in order to identify the best
  markers for following disease progression and
  monitoring treatment response
• Determine the optimum methods for acquiring,
  processing, and distributing images and
  biomarkers in conjunction with clinical and
  neuropsychological data in a multi-site context
• Validate imaging and biomarker data by
  correlating with neuropsychological and clinical
  data.
• Rapid public access of all data and access to
  samples

23
Study Design

• MCI (n 400) 0, 6, 12, 18, 24, 36 months
• AD (n 200) 0, 6, 12, 24 months
• Controls (n 200) 0, 6, 12, 24, 36 months
• Clinical/neuropsychological evaluations, MRI (1.5
  T) at all time points
• FDG PET at all time points in 50
• 3 T MRI at all time points in 25
• PIB sub-study on 120 subjects
• Blood and urine at all time points from all
  subjects CSF from 50 of subjects 0, 1 yr, 2 yr
  (subset) DNA and immortalized cell lines from
  all subjects
• GWAS study

24
Data and Sample Sharing

• Goal is rapid public access of all raw and
  processed data
• Central repository for all QAd MRI and PET
  Laboratory of Neuroimaging, UCLA (LONI)
• Clinical data base at UCSD is linked to LONI
• Databases- in the public domain, available to all
  qualified investigators
• Sample sharing-Resource Allocation Review
  Committee
• No special access
• Data Sharing Publication Committee (DPC)
• -ADNI Data Use Agreement

25
Genome-wide Association Studies (GWAS) Purpose,
Goals

• To identify common genetic factors that influence
  health and disease
• To study genetic variations, across the entire
  human genome, that are associated with observable
  traits
• To combine genomic information with clinical and
  phenotypic data to understand disease mechanism
  and prediction of disease
• To develop the knowledge base for personalized
  medicine

26
GWAS Data Sharing Policy

• All GWAS-funded investigators are expected to
  submit to the NIH data repository descriptive
  information, curated and coded phenotype,
  exposure, genotype, and pedigree data as soon as
  quality control procedures are completed at the
  grantee institutions.

27
Database of Genotype and Phenotype (dbGP)

• Serves as a single point of access to GWAS data
• To archive and distribute results from studies of
  the interaction of genotype and phenotype
• Provides pre-competitive data, no IP protection
• Encourages use of primary data from dbGP to
  develop commercial products or tests

28
Protection of Research Participants
De-Identification

• NIH does not possess direct identifiers of
  research participants does not have access to
  link between data keycode and identifiable
  information such information resides with the
  grantee institutions
• Research institutions submitting dataset must
  certify that an IRB and/or Privacy Board has
  considered and approved the submission
• Investigators must stripped the data of all
  identifiers before data submission
• Optional Certificate of Confidentiality

29
Protection of Research Participants Informed
Consent

• NIH expects specific discussion and documentation
  that participants genotype and phenotype data
  will be shared for research purposes through dbGP
  
• If participants withdraw consent for sharing
  individual-level genotype and phenotype data, the
  submitting institution will be responsible for
  requesting the dbGP to remove the data involved
  from future data distributions.

30
Data Access

• Requesters are expected to meet data security
  measures physical security, information
  technology security and user training
• Requires signed data use certification
• Proposed research use of data
• Follows local laws
• Not sell data elements
• Not share with individuals not listed in proposal
• Provide annual progress reports

31
dbGP Access Two Levels

• Open-access data includes
• Summaries of studies
• Study documents, reports
• Measured variables, e.g., phenotypes
• Genotype-phenotype analyses

32
dbGP Controlled-Access

• Requires varying levels of authorization
• Provides data on a per-study basis
• Controlled-access data includes
• De-identified phenotypes and genotypes for
  individual study subjects
• Pedigrees
• Pre-computed univariate association between
  genotype and phenotype

33
Controlled-Access Data Requests

• Requester must submit a Data Use Certification
• Access is granted by an NIH Data Access Committee
• Approval of proposed research use will be
  consistent with patient consent and data
  providers institutional terms and conditions

34
Intellectual Properties?

• Discourages premature claims on pre-competitive
  information that may impede research
• Encourages patenting of technology for downstream
  product development, e.g.,
• Markers for assays
• Drug targets
• Therapeutics
• Diagnostics
• Up to one year of exclusivity is allowed for the
  primary investigators to submit GWAS data
  analyses for publication
• Clock begins when the GWAS datasets is first made
  available to the NIH data repository

35
NIH Viewpoint

• Data should be made as widely and freely
  available as possible while safeguarding the
  privacy of participants, and protecting
  confidential and proprietary data.
• -- NIH Statement on Sharing Research Data
• February 26, 2003