1. NIH Common Data Elements Repository
Systems Demonstration - Systems for Knowledge Management
Session 87
Liz Amos, Vojtech Huser, Lisa Lang, and Christophe Ludet
National Library of Medicine, National Institutes of Health
Twitter: #AMIA2017

2. Disclosures
Authors have no financial conflicts to disclose. Amos, Huser and Lang are employed by the National Library of Medicine, National Institutes of Health and are supported by the Intramural Research Program at NLM. Ludet is an employee of Medical Science & Computing, LLC (MSC), and is a contractor to NLM; his work is supported by NLM and the Office of the Secretary (HHS) Patient-Centered Outcomes Research Trust Fund for Data Infrastructure.
AMIA | amia.org

3. Policies to increase access to data from NIH-funded scientific research
Notice of Proposed Rulemaking on Clinical Trial Registration and Results Submission Proposed NIH Policy on Dissemination of NIH-Funded Clinical Trial Information NIH Plan for Increasing Access to Scientific Publications and Digital Scientific Data from NIH Funded Scientific Research Genomic Sharing Data Policy
Increasing encouragement and policies around data sharing and access to federally funded data. A few examples of different guidelines, policy and recommendations are listed here and more can be found on the NIH Data Sharing Policy website.
The NIH encourages registration and results reporting for all NIH-supported clinical trials, regardless of whether or not they are subject to FDAAA.

4. Example: accessing clinical trials data and metadata
ClinicalTrials.gov contains information about medical studies in human volunteers
It is a registry and results database
257,336 registered trials as of November 7, 2017
Of those, 28,853 trials have reported with summary results
Many ways of collecting similar data, e.g. depression
Increasing granularity in outcome measurement reporting
Each ClinicalTrials.gov record presents summary information about a study protocol and includes the following:
Disease or condition
Intervention (for example, the medical product, behavior, or procedure being studied)
Title, description, and design of the study
Requirements for participation (eligibility criteria)
Locations where the study is being conducted
Contact information for the study locations

5. A Common Data Element (CDE) is a data element common to multiple sets across different studies
Fixed representation of a variable to be collected within a particular analytic of clinical domain Consists of a precisely defined question and a specified format or set of permissible values for responses (answers) Defined unambiguously in human and machine-computable terms Sets of CDEs can be combined into more complex questionnaires, survey instruments, and case report forms
A “common data element” is a data element that is common to multiple sets of data across different studies. This can be thought of a fixed representation of a variable that contains a question and a specified format or set of permissible values. So an example of this might be something like “how often do you consume alcohol” and the responses “not at all, some days, or every day”. Another example might be “how many drinks do you have in a month” and the response is any number. CDEs are defined to be both human and machine readable. In my first question, there were a specified set of responses, so a list of values. In the second question, any numeric response was valid. Sets of CDEs can be combined into more complex questionnaires, survey instruments and case report forms.

6. Examples of Common Data Element Initiatives at NIH
Some collections are across disciplines and domains, such as NIH Toolbox, PhenX Toolkit, PROMIS and Neuro-Qol (click)
Some are domain or disease focused, such as the NINDS Common Data Elements (Neurology), Genetic and Rare Diseases, NIDA CTN (substance abuse) and eyeGENE (eyes). (click).
And while CDEs may be new to some, several collections have been established for years in their communities, one example being NCI, who has been in the CDE business for 20 plus years.

7. NIH CDE Repository https://cde.nlm.nih.gov/
Promote the use of standards-based data elements and forms in support of electronic data capture and exchange for clinical research
Centralized library of data elements and standardized instruments recommended or required by NIH Institutes and Centers, and others
Facilitate use of machine-readable definitions through standards-based export capabilities
AMIA | amia.org

8. Origins of NIH CDE Repository
AMIA | amia.org

9. NLM and Data Science Variable Measurement Variable1 + Variable2
Libraries do information science and data management really well
How can we apply methods to manage clinical research metadata?
Facilitate reuse and reproducibility
Speed study start up
Improve data quality and data validation for data repositories
Make standardized administrative and clinical measurements easier to access/reuse while promoting transparency and scientific creativity
Collect
Store
Classify
Retrieve
Disseminate
Measurement
Variable
Variable1 + Variable2
AMIA | amia.org

10. Key functionalities of the NIH Common Data Element Repository
Develop new CDE and Form collections for clinical research Identify/discover CDEs and Forms recommended or required by NIH Institutes and Centers, and others Facilitate harmonization of data elements and forms, as well as specification using EHR-relevant health data standards Provide a platform for management and maintenance of CDE and Form collections Export authoritative versions of requested CDEs and Forms
AMIA | amia.org

11. NIH CDE Repository features
Today’s Use Case Demos:
NINR Symptom Science P20 Centers
Find and reuse elements
Collaborate with peers
Draft and publish recommendations
LASIK Quality of Life Collaboration Project (FDA, NEI, and DOD)
Create electronic form
Export
Today’s Highlighted Capabilities:
Search recommended or required measures; Browse by domain
Data elements and groupings
Standardized assessment instruments, surveys, Case Report Forms
Create and Collaborate
Export for use in electronic data capture systems
JSON, XML/ODM, XML/SDC, REDCAP
Published form
AMIA | amia.org

12. NINR Symptom Science
NINR first developed a set of CDEs commonly collected in all symptom studies -- Sleep, Fatigue, Pain, and Cognitive/Affect -- regardless of diagnosis. Along with symptoms, also included are demographic information (e.g., date of birth/ age, race, ethnicity); on participants throughout a study Required in specific P20 FOAs (NINR)
Search
Create a Board
Compare two data elements, forms
Add comment and reviewer
NINR Common Data Element Portal

13. LASIK Quality of Life Collaboration Project
FDA, NEI and DOD project to better understand potential risk of severe problems that can result from LASIK.
Patient-Reported Outcomes with LASIK (PROWL)
Pre-Op and Post-Op Questionnaires
NLM asked to create CDEs and electronic form
More information on scales used in PROWL Questionnaires
Create a CDE
Create a Form
Add a Section
LASIK Quality of Life Collaboration Project (FDA site)

14. Standards Terminology Export and Exchange JSON – NIH/CDE Schema
LOINC – pull panels from LOINC as they are requested for collection
Newborn Screening
Social, psychological and behavioral observations Edition Health IT Certification Criteria set
eyeGENE® (NEI)
PhenX (hybrid LOINC/RTI curated)
SNOMED CT – annotation of data elements
MeSH – NLM indexers evaluating use of MeSH to aid discoverability
Export and Exchange
JSON – NIH/CDE Schema
Structured Data Capture - XML with XSL transform
CDISC Operational Data Model – XML
Lister Hill National Center for Biomedical Communications (LHNCBC) Forms Widget
REDCAP zipped CSV
AMIA | amia.org

15. Challenges, Opportunities and Future Directions
Curation, duplication, quality assurance and harmonization
Siloed development/initial curation of metadata
Proliferation of many standards
Copyright analysis and display
Environmental scan of standardized assessment instruments to determine copyright status/terms of use
Development of workflow for contacting copyright holder, with intention to represent in Repository
Continued development of service model to support various use cases and stakeholders with limited resources
Annotation(s) of data elements and forms to support discoverability
SNOMED CT (Poster Session 5pm)
MeSH (collaboration with NLM Index Section)
Move to Amazon Web Services
AMIA | amia.org

16. Challenges, Opportunities and Future Directions (Continued)
Enhanced collaboration with other public repositories (both data and data element/form)
Enhanced discovery and authoring capabilities to support measure and registry authoring projects, including enhanced coordination with the NLM Value Set Authority Center (VSAC), particularly for authoring using EHR- relevant health data standards
FHIR (SMART on FHIR)
AMIA | amia.org

17. Thank you!
cde.nlm.nih.gov