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Engagement with other research networks

(Andrew Williams) #1

Please use this thread to announce, link to, and discuss activities in other research networks or organizations that present interesting opportunities for engagement by the OHDSI community.

(Andrew Williams) #2

The national Center for Data to Health (CD2H) and the related iDTF (Domain Task Force) workgroups are driving development of key research consortium capacities across NIH-sponsored CTSA (Clinical and Translational Science Awards) hubs at academic health centers in the US. While I and other OHDSI community members (e.g. @karthik, @Christophe_Lambert) are involved in some parts of these efforts, they encompass many projects and my impression is that OHDSI participation is relatively light given the potential value and relevance of the work. Some of these projects are likely to be valuable enough to warrant high-level broad engagement by OHDSI to accelerate their progress and promote alignment with related OHDSI efforts.

It is worth noting that many CTSAs have an OMOP instance and many researchers at those institutions may be unaware of them or of the benefits of OHDSI tools and OHDSI community participation. Others may undervalue these resources because of partial or incorrect understanding of them. More robust engagement with these CTSA consortium efforts by OHDSI would likely promote greater mind share in this researcher rich community and result in more network studies among other good things. We are also likely to learn a lot from other smart people coming at similar objectives from different angles.

Finally, I think it is also likely that we will discover new tools and practices that will advance OHDSI’s mission: E.g. the data discover engine for making data findable and enhancing interoperability, menRva to record and disseminate digital works across the translational community to enhance their visibility, promote people and support attribution of their work, DQe-c for evaluation of data completeness and visualization of data quality test results, the clinical adaptor for line level STDM data submission to FDA, and ehr2HPO for conversion of EHR data (such as LOINC) to HPO codes.

This site lists and describes the three community workgroups in CD2H. Each group encompasses several projects. CTSA members can engage with project prototypes during development at the CD2H labs site and access the dedicated Slack channel for support. And many of the projects have a public Github repo.

For convenience and reference in this thread, I’ve listed, with minimal paraphrasing, the three workgroups, their leads, goals, and component projects below with links to relevant web pages and documents.

  1. Workgroup Name: Data Workgroup
    Leads: Chunlei Wu, Christopher Chute:
    Goals: Advance CTSA’s capacity to operate as a federated network with clinical data experience that can be leveraged for data discovery and translational research at scale. Its products will foster collaboration on shared data models, data licensing, informative metadata, and informatics maturity criteria.
  1. Workgroup Name: Software, Tools & Algorithms Workgroup
    Leads: Sean Mooney, Philip Payne, David Eichmann
    Goals: Promoting and supporting the collaborative development and sharing of software, tools, and algorithms that advance clinical and translational research.
  • Project: Secure cloud-based infrastructure for CTSA hub data sharing.
    Lead: Kari Stephens
    Description: There is incredible wealth and computational potential in CTSA program data assets, but effective utilization requires effective secure data sharing. This project leverages new, cloud based infrastructure that includes elasticity, scalability, state-of-the-art cybersecurity capabilities, and economies of scale.

  • Project: Open Source Clinical Enterprise Data Warehouse (EDW) Data Browser (Leaf).
    Lead: Nic Dobbins
    Description: Leaf is a data-model agnostic, cloud based user interface for cohort discovery and research analytics; this next phase of development focuses on implementation at additional CTSAs and explores support for queries via FHIR.

  • Project: Leaf Cloud Pilot.
    Lead: Kari Stephens
    Description: The demonstration project will provide opportunities for CD2H to discover a pathway to: 1) data sharing governance structures that could be a model for the CTSA Program, 2) cloud infrastructure that could be adapted for use by multiple CTSAs, operating multiple data models, and 3) cloud vendor partnerships. It will scale an existing front end tool for self-service against an OMOP repository that can be co-opted by other CTSA institutes in the near term. This project will create groundwork for building scalable solutions that allow more nimble data sharing within and across CTSAs (i.e., API solutions for multiple self-service tools to operate against multiple shared data models like OMOP, i2b2, and FHIR).

  • Project: SPARC in the Cloud for CTSA Hubs.
    Lead: Robert Schuff
    Description: This project puts SPARC on the NCATS cloud in collaboration and partnership with MUSC to support CTSA services management.

  • Project: Data Quality Methods and Tools to Support CTSA Hub Data Sharing
    Lead: Kari Stephens
    Description: EHR data must be tested for data quality when being shared for research; this project will launch a publically available data quality testing tool. This tool is designed to run against OMOP.

  • Project: CTSA Data Sharing Governance Pathways Project.
    Lead: Kari Stephens
    Description: Clear governance pathways within and between CTSAs are needed to expediently allow safe sharing of electronic health data for research. This project provides examples and templates of standardized Data Use Agreements (DUAs) to promote collaborative and flexible data sharing for CTSA hubs.

  1. Workgroup Name: People, Expertise & Attribution Workgroup.
    Leads: Melissa Haendel, Kristi Holmes, David Eichmann
    Goals: Support discovery of the rich expertise available within the CTSAs and beyond, and to provide innovative infrastructure for supporting attribution of the diverse contributions required for effective translational team science.
  • Project: A computable representation of contributions.
    Lead: Kristi Holmes
    Description: Representing individual contributions to translational science is important for providing credit, as well as understanding the expertise of our workforce.

  • Project: Personas for Clinical and Translational Science.
    Lead: Sara Gonzales
    Description: This project will profile the translational workforce: specific roles, expertise, training, needs regarding data access and use, software tools, and workflows; the resulting library of community driven collection of personas will help scope and drive forward translational software and program projects.

  • Project: Science of translational science research platform.
    Lead: David Eichmann
    Description: Data aggregation platform for the CTSA Program, including educational resources, datasets, software tools, etc., providing the ability to discover not only resources and expertise, but also support new analytics on the science of translational science, such as scholar tracking and impact analysis.

  • Project: Competitions tool for CTSA community peer review.
    Lead: Firas Wehbe
    Description: Competitions is an open source tool to run NIH-style peer review of competitions, pilot projects, and research proposals in a cloud-based consortium-wide single sign-on platform.

  • Project: menRva: an interdisciplinary open research repository.
    Lead: Matt Carson
    Description: Infrastructure to preserve and disseminate translational research more easily. The portal enhances visibility and access, promotes people and the attribution of their work, and supports open and FAIR-TLC science with good data practice workflows, powerful search and indexing, and privacy standards required for translational research.