IEEE

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Overview
Transforming Behavioral Medicine
Cyberinfrastructure in Cancer Prevention and
Control
Abdul R Shaikh, PhD, MHSc Bradford Hesse, PhD
Health Communication and Informatics Research
Branch Division of Cancer Control and Population
Sciences National Cancer Institute
March 25, 2009
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What is Behavioral Medicine?

• An interdisciplinary field concerned with the
  development and integration of behavioral,
  psychosocial, and biomedical scienceand the
  application of this knowledge to prevention,
  diagnosis, treatment and rehabilitation.
• (Society of Behavioral Medicine www.sbm.org)

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Theories and Frameworks (bread and butter)

• Theory interrelated concepts, definitions,
  propositions that present a systematic view of
  situations/events by specifying relations among
  variables to explain and predict the
  situations/events (Kerlinger, 1986)
• Parsimoniously present complex information
• Help to narrow research topics into specific
  questions
• Designate variables to be operationalized
• A priori hypotheses and parametric statistics

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Theories of Behavioral Medicine

• Individual
• Health Belief Model (Janz Becker, 1984), Theory
  of Planned Behavior (Ajzen, 1991),
  Transtheoretical model (Prochaska, 1979)
• Interpersonal
• Social Cognitive Theory (Bandura, 19781997),
  social networks and social support (Israel, 1982
  House, 1981)
• Group/community/mass-media
• Community building/empowerment (Minkler
  Wallerstein, 2002), Diffusion of Innovations
  (Rogers, 1983)
• Ecological
• - Ecological approach (Stokols, 1992),
  PRECEDE-PROCEED (Green Kreuter, 1991)

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Ecological Framework for Diet Communication
Program Announcement PA-08-239 Impact of Health
Communication Strategies on Dietary Behaviors
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MISSION DCCPS aims to reduce the risk,
incidence, and deaths from cancer as well as
enhance the quality of life for cancer
survivors. The Division conducts and supports
an integrated program of the highest quality
behavioral, epidemiologic, genetic, social, and
surveillance cancer research.
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DCCPS Cancer Control Framework
Reducing the cancer burden
Adapted from the 1994 Advisory Committee on
Cancer Control, National Cancer Institute of
Canada.
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Surveillance
Intervention Research
Knowledge Synthesis
Basic Science
Surveillance
Application Program Delivery
Reducing the Cancer Burden
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Basic Science Intervention
Intervention Research
Knowledge Synthesis
Basic Science
Surveillance
Application Program Delivery
Reducing the Cancer Burden
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Application
Intervention Research
Knowledge Synthesis
Basic Science
Surveillance
Small Business Innovation Research Grants (SBIR)
Application Program Delivery
Reducing the Cancer Burden
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Synthesis Health Informatics
Informatics in Action
Intervention Research
Knowledge Synthesis
Basic Science
Surveillance
Application Program Delivery
Reducing the Cancer Burden
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Public Health Informatics

• IT for improving cancer-related care and
  ultimately, cancer-related outcomes
• 15 years bench to bedside
• Accelerate discovery cognitive support
• Bioinformatics biology, genomics/proteomics
• Imaging informatics tissues and organs
• Clinical informatics whole organisms
• Public Health Informatics populations
• Cancer Causes Control (2006) 17861869

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Public Health Informatics Engineering
PHI the systematic application of information
and computer science and technology to public
health practice, research, and learning. A.
Friede, H.L. Blum, and M. McDonald (1995) Public
health informatics is primarily an engineering
discipline, that is, a practical activity,
undergirded by science, oriented to the
accomplishment of specific tasks. J Public Health
Management Practice, 2000, 6(6), 6775
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Behavioral Medicine and the Information Landscape
Islands of datasets, documents, analytic
tools, and research communities
Peter Schad, 2008
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Behavioral Data
Local Interventions
Field based data
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Behavioral Medicine and the Information Landscape
- Overwhelming volume of data - Multitude of
sources/levels
Slide source Peter Schad, 2008
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The End of Science?
The Petabyte Age Sensors everywhere. Infinite
storage. Clouds of processors. Our ability to
capture, warehouse, and understand massive
amounts of data is changing science, medicine,
business, and technology. As our collection of
facts and figures grows, so will the opportunity
to find answers to fundamental questions. Because
in the era of big data, more isn't just more.
More is different. - Chris Anderson
06.23.08
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.
Enter Cyberinfrastructure
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Expand the Scope of Discovery
Pattern Detection Tools
Application Layer
Users

• Users
• Epidemiologists
• Behavioral scientists
• Public health planners
• Geneticists

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Visualization
Application Layer
Users

• Users
• Applied/Basic
• scientists
• Policy makers
• State/City public
• health planners

Courtesy Ben Shneiderman, 2006 NCI Speaker Series
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Decision Support Policy Planning
Portfolio Analysis Tools
Application Layer
Users

• Users
• Science directors
• State health planners
• Resource allocation
• Clinicians

Courtesy Katy Börner, 2006 NCI Speaker Series
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Connecting Stove-piped Data

• Users
• Survey methodologists
• Population scientists
• Federal planners

Application Layer
Users
Advanced Analytic Tools
University Research
National Systems
International Systems
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Populomics and the Grid
Personalized Health Care Systems Integration,
from cells to society


Populomics
Personalized Medicine Pharmaco-genomics
Proteomics
Nanotechnology
Genomics
Slide source David Abrams, 2008
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caBIG cancer Biomedical Informatics Grid

• .

• caBIG Goal
• A virtual web of interconnected data,
  individuals, and organizations that redefines how
  research is conducted, care is provided, and
  patients/participants interact with the
  biomedical enterprise.
• caBIG Vision
• Connect the cancer research community through a
  shareable, interoperable infrastructure
• Deploy and extend standard rules and a common
  language to more easily share information
• Build or adapt tools for collecting, analyzing,
  integrating and disseminating information
  associated with cancer research and care

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.
caBIG Capabilities Enable Discovery gt Clinical
Research gt Clinical Care
Molecular Medicine

• .

caBIG Goal
Clinical Research
Imaging
Pathology
Molecular Biology
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.
caGrid High-Level Architecture

• .

caBIG Goal
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.
caBIG Cancer Center Deployment

• .

caBIG Goal

• caBIG adoption is unfolding in
• 49 NCI-designated Cancer Centers
• 16 NCI Community Cancer Centers
• caBIG being integrated into federal health
  architecture to connect National Health
  Information Network
• Global Expansion
• UK, China, India,
• Latin America

NCI-Designated Cancer Centers, Community Cancer
Centers, and Community Oncology Programs
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Take a Slice of the Cake
PopSciGrid 1.0
Application layer
GRID infrastructure
CDEs, vocabularies, metadata
Consortium in Abbas, A. (2004) Grid Computing A
Practical Guide to Technology and Applications.
Hingham, MA Charles Hingham (p. 319).
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PopSciGrid 1.0

• Proof of concept for CI in population health and
  cancer control
• Use state-of-the-science technology to link data,
  researchers, and resources
• Expert Panel Workshop (March 08) caBIG Annual
  Mtg (June08) DCCPS Fall Forum (November 08)
  HICSS, SBM
• Noshir Contractor, PhD, Yun Huang, PhD, York Yao,
  MS
• Science of Networks in Communities (SONIC)
  Laboratory, Northwestern University

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PopSciGrid 1.0 (cont.)

• ChallengesNot just technology infrastructure
• Collaboration
• Within and across disciplines
• Privacy, de-identification, and data ownership
• Data Harmonization
• Standardize data collection
• Different national surveys, codebooks, and
  datasets
• Different measures/instruments for same phenomena
• Legacy datasets

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Behavioral Medicine - Getting Grid-ified

• Implement services on the Grid
• HINTS, NHIS, and tobacco tax data
• Basic statistics, categorical analysis, and
  prevalence analysis
• Visualization by region
• Demonstrate the power of the Grid
• Publish data
• Analyze data from multiple sources
• Visualize data on the Grid

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PopSciGrid

• 14 datasets spanning 6 years
• Real-time access/analysis of public health and
  economic data

• Prospective geo-spatial analytics

• Potential links to GEM database
• http//129.105.36.86/GridServer/c/index.html

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Web 2.0 / Science 2.0

• Architectures for Participation
• Collective Intelligence
• Data as the new Intel Inside

Volume 22 No. 2, February 2008 Psychology and
the Gridby Steven Breckler, Executive Director
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Virtual Organizations Interdisciplinary Science
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PopSciGrid 2.0
CISNet Decision Aids
State Cancer Profiles
Data Widgets
Application layer (e.g., Enhanced State Cancer
Profiles Dashboards, CDC Data Widgets)
PopSciGrid
GRID Middle Ware (Globus toolkit, XMi, security
layer, discovery mechanisms)
caBIG BIRN, NHIN
Common Vocabularies Shared ontologies, common
data elements
DATA SOURCES

• Biomedical
• Biological
• Genomic/proteomic

• Public Surveillance
• NHIS
• BRFSS
• HINTS
• Tax, Census,...

• Grantees
• CECCRS
• TREC
• TTURCS
• CPHHD
• GEI

• Mobile/Remote Sensing
• Behavioral data
• Environmental data
• GIS
• RTDC

• Clinical/Health System
• CRN
• QCCC projects
• PopSci SIG
• Registries (SEER)

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PopSciGrid 2.0 Priming the Pump

• (Grid Enabled Measures) Database

A grid-enabled, interoperable, dynamic website
for behavioral and social science theoretical
constructs and measures
Program Lead Rick Moser, PhD (Behavioral
Research Program, DCCPS)
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Beyond Behavioral Medicine GEI

• GEI Genes, Environment, and Health Initiative
• NIH-wide, led by NHGRI and NIEHS
• Goal to accelerate understanding of the genetic
  and environmental contributions to health and
  disease
• 2007-2011, 46.5 million
• 30 environmental technology projects
• 8 genome-wide association studies
• 2 genotyping centers and coordinating center

• Program Leads Jill Reedy (NCI), Amy Subar (NCI),
  Catherine Loria (NHLBI)

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GEI Genes and Environment

• .

EXPOSURE BIOLOGY PROGRAM
GENETICS PROGRAM
Develop technology and biomarkers
Identify genetic variants
GXE

• Diet and
• Physical Activity
• Psychosocial Stress and
• Addictive Substances
• Chemical Sensors
• Biological Response Indicators

• GWA Studies
• Data Analysis
• Replication
• Sequencing

• Database
• Function
• Translation

• Program Leads Jill Reedy (NCI), Amy Subar (NCI),
  Catherine Loria (NHLBI)

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GEI - Timeline

• .

FY07 FY08 FY09 FY10
FY11

• Environmental Sensors
• Diet/Physical Activity (NCI/NHLBI)
• Psychosocial Stress/Addictive Substances (NIDA)
• Chemical Sensors (NIEHS)

U01
DEVICES
U01
U01
U01
U54
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GEI Technology (cont.)

• .

• Innovative technologies to measure diet, PA,
  stress, addictive substances, chemical sensors,
  biological response indicators
• 5 use cell phones to capture and/or transmit data
• 3 combine accelerometers with physiologic sensors
  (e.g., heart rate) to improve estimates of energy
  expenditure
• 3 pair camera/video/audio components with
  automated processing (e.g., image detection,
  voice recognition)
• 2 use GPS coordinates to track location of
  activities
• 1 uses web-based multimedia software as a tool
  for reporting diet among children

• Program Leads Jill Reedy (NCI), Amy Subar (NCI),
  Catherine Loria (NHLBI)

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GEI PALMS (Physical Activity Location
Measurement System)
PI Kevin Patrick, University of California San
Diego
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Looking Ahead Institute for the Future
Mike Liebhold (2008) www.IFTF.org

• .

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Talk is cheap
American Recovery and Reinvestment Act 2009
http//www.cancer.gov/recovery NIH Challenge
Grants in Health and Science Research
(RC1) http//grants.nih.gov/grants/guide/rfa-files
/RFA-OD-09-003.html Application Due Date
4/27/2009 Peer Review Date 6-7/2009 Council
Review Date 8/2009 Anticipated Start Date
9/30/2009
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Funding Challenge Grants
(10) Information Technology for Processing Health
Care Data 10-CA-101 Cyber-Infrastructure for
Health Building Technologies to Support Data
Coordination and Computational Thinking. The
National Science Foundation has identified
research based on cyberinfrastructure as the
single most important challenge confronting the
nations science laboratories (http//www.nsf.gov/
news/special_reports/cyber/index.jsp). The
challenge is based on a grand convergence of
three trends (a) maturation of the Internet as
connective data technology (b) ubiquity of
microchips in computers, appliances, and sensors
and (c) an explosion of data from the research
enterprise. The NIH, for example, has invested
millions within its Genes, Environment, and
Health Initiative (GEI) to develop new
technologies for measuring environmental exposure
to accompany the millions already spent on data
from Genome Wide Association studies. The DHHS is
spending millions to catalyze the deployment of
interoperable electronic health records as a
springboard for research (i.e., in the learning
health system). Relatively little has been spent
on accommodating the petabytes (i.e., 10 15 bytes
of data) of data expected from these investments.
What is needed is a focused concentration of
resources to stimulate the creation of new
technologies to accommodate these data and
accelerate knowledge discovery through
computational means. Such a stimulus should help
bootstrap a new sector of the knowledge economy,
one that is dedicated to accelerating the pace by
which data are turned into population health.
Contact Dr. Bradford Hesse, 301-594-9904,
hesseb_at_mail.nih.gov
NIH Challenge Grants in Health and Science
Research (RC1) http//grants.nih.gov/grants/guide/
rfa-files/RFA-OD-09-003.html
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Funding Challenge Grants (cont.)
(10) Information Technology for Processing Health
Care Data 10-EB-101 Engineering improved
quality of health care at a reduced cost.
10-HL-101 Develop data sharing and analytic
approaches to obtain from large-scale
observational data, especially those derived from
electronic health records, reliable estimates of
comparative treatment effects and outcomes of
cardiovascular, lung, and blood diseases .
10-LM-101 Informatics for post-marketing
surveillance. 10-LM-102 Advanced decision
support for complex clinical decisions. 10-OD-101
Adapt existing genetic and clinical databases
to make them interoperable for pharmacogenomics
studies. 10-RR-101 Information Technology
Demonstration Projects Facilitating Secondary Use
of Healthcare Data for Research
NIH Challenge Grants in Health and Science
Research (RC1) http//grants.nih.gov/grants/guide/
rfa-files/RFA-OD-09-003.html
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Funding SBIR / STTR
SBIR (Small Business Innovation Research) PI
from small company (51) with academic
consultants STTR (Small Business Technology
Transfer Research) PI from non-profit org.
working with small businesses Established to
promote collaborations between small businesses
and non-profit organizations for the purpose of
developing science-based commercially viable
products that help meet the goals of different
federal agencies. Phase I 100k, 6-12 months
feasibility, pilot/prototype Phase II 750k 2-4
years implementation evaluation
(moving to Phase I 300,000 Phase II up to
2.2 million)
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Funding SBIR / STTR
Products Examples cancer-related PC software
interactive DVDs wireless devices web/TV/radio
programs videos or PSAs EHR apps. Target
Audience cancer survivors and their families,
decision making tools educational and/or
training tools devices that improve health
behaviors or change lifestyle habits and
screening, assessment, or management
programs. NCI DCCPS SBIR/STTR Program
Advisor Connie Dresser, RDPH, LN HCIRB,
BRP, DCCPS, NCI 301-435-2846,
cd34b_at_nih.gov www.cancercontrol.cancer.gov/hcir
b/sbir
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Acknowledgements

• .

• NCI
• Rick Moser
• Glen Morgan
• Erik Augustson
• Frank White
• Jill Reedy (GEI)
• Amy Subar (GEI)
• NHLBI
• Catherine Loria (GEI)

• BAH
• Paul Courtney
• Northwestern University
• Noshir Contractor
• Yun Huang
• York Yao