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Making More Than the Sum of the Parts: How CTSA Hubs Can Leverage CD2H Collaborative
Informatics for Greater Translational Impact
CG Chute, MD DrPH
Acknowledgements
cd2h.org/cloud
● Melissa Haendel
● Justin Guinney
● Adam Wilcox
● Dave Eichmann
● Julie McMurry
The Center for Data to Health (CD2H) Team
GITHUB.COM/DATA2HEALTH/RESOURCE-DISCOVERY
The CD2H team
Expensive and insecure local and legacy
infrastructure
Legal and technical barriers to
meeting data sharing mandates and
multi-site research needs
Difficulty finding and sharing
resources and expertise
Data in different formats and shapes
makes it hard to do multi-site research
Common CTSA challenges Shared CD2H solutions
CD2H’s role is to coordinate and deliver shared informatics solutions for diverse Hub needs
Recurring
needs
across Hubs
Workforce Development
Collaboration
Integration
Methods & Processes
Informatics
Investigator
Trainee
Staff
Clinical research
Laboratory science
Population health
Basic research
Entrepreneurship
Regulatory
Co
res
Dis
cip
lin
es
Ca
ree
r st
ag
es
CONVENE DESIGN
IMPLEMENT
Increased Hub
capacity and
collaboration
CT
SA
HU
BS
Individuals
NCATS/CD2H Cloud Infrastructure
Cloud and Tool Core
GITHUB.COM/DATA2HEALTH/RESOURCE-DISCOVERYcd2h.org/cloud
Cloud & tool architectureExemplar Projects:● DREAM Challenges● LEAF● Competitions
Best Practices
Tool registry
Build & Test
Framework
Benchmarking
Hosted Tools
Sandboxes
Built-in Security
Get involved with the CD2H Tool and Cloud Infrastructure
Community Corecd2h.org/cloud
CTSA Cloud Hub
QA Pipeline
Hosted Resources
Benchmarking Environment
Build & Test Framework
Software Dashboard
Tool Registry
App Store
Best Practices Documentation
Analysis Sandbox
Models & Algorithms
Ontologies
Web Services
Web Applications
CTSA Tools
Cloud & tool architecture: RFC
Interactive web portal for CTSA users
Cloud-hosted web backend & service
orchestration
Distributed services for portal features
2019-09-27
cd2h.org/cloud
Journey of a software tool
CTSA Cloud HubVerified
⚪ Licence
⚪ Docs
⚪ Tests
This tool is missing several
required ingredients.
Elements needed to complete
verification of this tool:
Tool Registry
Detected Registered BenchmarkedValidatedVerified Portable
Assessing and supporting best practices for software development
Ryan completes
the registration, but now notices
that the status indicator suggests
that the software might not be
very easy to access or use. Busy
with another project, he asks his
trainee, Cynthia, to “fix it.”
PROBLEM
Cynthia looks at what’s
missing, but doesn’t really
know what to do...
Cloud Architecture
2019-09-27
cd2h.org/cloudCloud & tool architecture: RFC
DREAM Challenge Updates
● EHR Challenge in 1st Leaderboard Phase
● 241 registered participants
● Onboarding Wash U & Mt Sinai as additional
data hosts
● RA Challenge (winner of Idea Challenge) set to
launch in November
● $50k prize money donated by BMS
COMPETITIONSA platform to run NIH-style grant competitions across the CTSA
including pilot projects and research awards
USE COMPETITIONS NOW!
● Navigate to competitions.cd2h.org
● Log in using your institutional credentials
● Try it out
● Browse resources and documentation
● Sign up for demos and webinars
● Contribute feedback or feature requests to
competitions-cd2h@northwestern.edu
competitions.cd2h.org/
LEAF A lightweight, open-source, model-agnostic
web application for querying clinical data
● Flexible: Leaf can work data models:
OMOP Common Data Model, i2b2 and
SHRINE, or other proprietary or non-
standard data models.
● User Friendly: Leaf is a simple drag-
and-drop web application that queries
clinical databases, so users can focus
on accomplishing research, not
waiting for data.
● Secure: Leaf implements current best
security practices to make clinical data
both accessible and safe.
● Open: Leaf is an open-source project
by CTSAs, for CTSAs.cd2h.org/leaf
CTSA Search: Making CTSA resources more discoverable
GITHUB.COM/DATA2HEALTH/RESOURCE-DISCOVERY
Enabling discovery of resources and expertise within the CTSA program and beyond
Etc
Try it at labs.cd2h.org/search
GITHUB.COM/DATA2HEALTH/RESOURCE-DISCOVERY
CTSAsearchYour path to discovering CTSA resources
Try it at labs.cd2h.org/search
Informatics Maturity & Best PracticesAdam Wilcox, PhD University of Washington
Chunlei Wu, PhD, Scripps Boyd Knosp, MS, Iowa
Informatics maturity and best practices community core
GITHUB.COM/DATA2HEALTH/RESOURCE-DISCOVERYcd2h.org/maturity
Maturity Models: Research
Informatics and Open Science
Maturity (RIOSM) Model
Average Maturity Score by Domain
cd2h.org/maturitymodel
Informatics maturity and best practices community core
GITHUB.COM/DATA2HEALTH/RESOURCE-DISCOVERYcd2h.org/maturity
Maturity Models |
Convening of iDTF members based on break-outs
from spring meeting ● Reviewing and prioritizing additional models
Maturity of Maturity Models
What’s new We are creating a MM tool to:● Collect information on health informatics maturity at
various CTSA sites.
● Summarize that information for dissemination to the
CTSA community.
Fast Healthcare Interoperability Resources (FHIR) and the NIH Perspective
Christopher G. Chute, M.D., Dr.PH. (Johns Hopkins University) & Jerry Sheehan, M.S. (National Library of Medicine)
GITHUB.COM/DATA2HEALTH/RESOURCE-DISCOVERY
NIH encourages use of FHIR in research
Fast Healthcare Interoperability Resources (FHIR®)
Standard. Notice Number: NOT-OD-19-122
Release Date: July 30, 2019
“To encourage NIH researchers to
explore the use of the Fast Healthcare
Interoperability Resources (FHIR®)
standard to capture, integrate, and
exchange clinical data for research
purposes and to enhance capabilities to
share research data.”
cd2h.org/FHIR
GITHUB.COM/DATA2HEALTH/RESOURCE-DISCOVERY
NIH investing in FHIR tools for research
Small Business (SBIR & STTR) Applications Directed at the Adoption of the Fast
Healthcare Interoperability Resources (FHIR®) Standard
Notice Number: NOT-OD-19-127 Release Date: July 30, 2019
● Integration of patient- and population-level data from EHR systems
● Access to and management of electronic health information
● Development of clinical decision support systems
● Exchange of EHR data and health documentation
● Enhancement of privacy and security for electronic health information
● Inclusion of common data elements (CDEs) and clinical terminologies to improve interoperability of EHR
data for research and clinical care
● Support for a common structure for sharing clinical research data
● Integration of EHR and patient-originated data with clinical research data
● Design and monitoring of clinical trial protocols
● Enhancement of patient recruitment, enrollment, and consent in clinical trials
GITHUB.COM/DATA2HEALTH/RESOURCE-DISCOVERY
Transforming the clinical data landscape with FHIR
cd2h.org/FHIR
UNIFIED SOLUTIONCURRENT WORKAROUNDS
EXAMPLE
FHIR PAYLOADS
GITHUB.COM/DATA2HEALTH/RESOURCE-DISCOVERY
How does FHIR help?
EXAMPLE
FHIR
“shapes”
(Resources)
OBSERVATION 2
{PSA, 2.6 ng/mL}
{Serum Sodium,133 mEq/L}
OBSERVATION 1
OBSERVATION
“shape”OBSERVATION
SLOTS:
WHO, WHAT WHEN,
WHERE
TEST {coded type,
value}REFERENCE RANGE
OBSERVATION
“shape”
cd2h.org/FHIR
OMOP
PCORI
Sentinel
EHR
ACT
FHIR power for data model interoperability
CDC - Surveillance
NIH Clinical Research
FDA - Safety
National
InstituteCancerNLM
FHIR and i2b2 (applied to ACT)
Given:
● Core i2b2 is very flexible – i2b2 is more of a
meta-model than a model
● FHIR exists and is being implemented and
deployed
Would it be possible to transform FHIR data to
the i2b2 CRC cell and…
… represent the FHIR model as one i2b2 ontology
and…
… create / re-use i2b2 ontologies to provide
different views on the i2b2 FHIR data?
FHIR
Model
ACT
FHIR
HOT
Peter.Robinson@jax.org | Aaron.Zhang@jax.org GITHUB.COM/DATA2HEALTH/EHR2HPO.PRJ
Scalable tools for harvesting Human
Phenotype Ontology from the EHRCORE
ICON
● Build on success of LOINC to HPO demonstration (PMID:31119199)
● Tactical focus on demonstrating LOINC to HPO for biomarker discovery
● Opportunity to expand HPO discovery to other domains beyond labs
■ Radiology, Clinical Notes● Balance clinical vs. research application in
diagnosis and phenotyping● Recognize that only a subset of HPO can be
algorithmically discovered from the EHR● In current phase extension to radiology,
application at JHU, OHSU, new algorithms
CD2H COMMUNITY CORES:
● Join a core’s monthly call
● Signal interest in any project
● Contribute to use cases
● Explore code demos and training
● Make a feature request
● Provide feedback
● Help draft manuscripts, best practices
● Implement best practices
● Review options for technical implementation
● Contribute to data standards
● Contribute content (eg. FHIR mappings, DUAs, interviews)
● Participate in the mortality challenge
Where to start
cd2h.org/sharing
cd2h.org/discovery
cd2h.org/cloud
cd2h.org/maturity
Ways to engage
@data2health
HHS Consortium for FHIR Stack
National
InstituteCancerNLM
NCATS Biomedical Data Translator
Integrated genotype-phenotype and other biomedical
data is a resource for researchers to interrogate data
for integrative and translational science
https://ncats.nih.gov/translator
The Biolink
Model as a
foundation
Adapt from proposed NCATS Translator Methods
31
October 11, 2018
Application of
Ontology:
Crucial to
Translational
Research
Program overview / Team
introductions
Community
Development
(lead: Volchenboum;
co-lead Vasilevsky)
Data Model
harmonization
(lead: Chute)
Ontology & Terminology
Ecosystem
(lead: Solbrig)
Tools & Data Quality
(lead: Balhoff)
Program Management and operations:
(lead: Haendel, co-lead McMurry)
Programmatic oversight:
CBIIT: Sherri De Coronado, Allen Dearry
FNL: Todd Pihl
Thoughts
cd2h.org/cloud
● Coordination of effort to achieve shared goals makes sense
● CD2H, CCDH, and CDMH projects all seek to advance this
● CD2H functions as collaboration coordinators
● Participation is welcome and fostered
● The tasks are challenging
Thank You
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