Common Data Elements Questions with Dr. Kibbe

Common Data Elements Questions with Dr. Kibbe

Jan. 29, 2021

As projects take steps to implement  National Institutes of Health (NIH) Common Data Elements (CDEs) into your research studies, we sat down with Dr. Warren Kibbe to address your most pressing questions and concerns. Along with Drs. Keith Marsolo and Lisa Wruck, Dr. Kibbe leads the RADx-UP Coordination and Data Collection Center’s Data Science and Biostatistics Core. He has had a direct role in selecting and finalizing the NIH CDEs with NIH and project team input in mind. Hear what he has to say in the podcast series “CDE Questions with Dr. Kibbe.” The first seven segments of the series explore the below questions:

Key points

What are the benefits of NIH RADx-UP CDEs?

  • Many of the CDEs have originated from NIH-funded projects over the course of many, many years and have been well vetted and validated.
  • The CDEs will help us consistently ask questions of our participants, and compare results in a uniform way.
  • In addition, we’ll be able to compare RADx-UP research to other types of research taking place across the country and around the world asking similar questions.

What was the process for selection?

  • NIH provided the RADx-UP Data Harmonization Guidance document, which included a large collection of 752 required CDEs.
  • Thanks to input from all RADx-UP projects we were able to provide justification to NIH to reduce the required CDEs to 66 in order to minimize participant and coordinator burden.
  • In the process of reviewing input from all of your projects we identified and incorporated novel CDEs that further your science. These will be used across the entire consortium to answer important questions to identify and alleviate testing disparities in underserved populations.
  • The NIH CDEs were finalized in January and they are now ready for your implementation.

What are the final NIH RADx-UP CDEs?

  • Tier 1 CDEs are required from all testing Projects (optional for Pilot Projects).
  • Tier 2 CDEs are recommended additions.
  • For more information on the CDEs, please see the below graphic, or visit the Data Toolkit tab on the Toolkit page.

Why should projects collect personal identifiers?

  • While some personal identifiers are Tier 1 CDEs, there is an exception process (read more here.)  These personal identifier CDEs are strongly encouraged for collection because they allow us to put our research into the context of the individual and the community, and re-contact participants for future research.
  • With location identifiers, like address and zip code, we can link data at an area level using geospatial data linkage. This enables us to look at social determinants of health and understand risk and protective mechanisms for community health.
  • We can also link data at an individual level. For example, personal identifiers can help us link to Centers for Medicare & Medicaid Services (CMS) claims data to understand the bigger context of individual health for each of our participants without increasing interview burden.

What is the timeline for implementation?

  • We’re under enormous pressure to understand and alleviate the impact of the pandemic on underserved communities.
  • The CDEs are an important way that we have consistent measurement across the RADx-UP consortium.
  • Because the pandemic is evolving so rapidly, we need to start that measurement as quickly as possible.
  • Implementing the CDEs is critical for projects to generate consistent and meaningful results for the consortium, the communities that you serve, and our country.

What is the NIH RADx-UP CDE exception process?

  • There is an expectation that everyone collects Tier 1 CDEs, as stated in the terms and conditions of all RADx-UP award.
  • The CDCC tracks the NIH CDEs collected by each project for the purposes of data quality (data missingness) and reporting to the NIH. This tracking is done via project completion of the NIH CDE Tracking form sent to you via REDCap.
  • If your project has identified a CDE that you cannot capture, you must also submit a prior approval request to the NIH for a waiver to the terms and conditions of your award. Waivers are only approved due to study design reasons or for Tribal Nations Projects.
  • If you would like to request a variance in wording or value sets that you are capturing, those requests can be submitted in the NIH CDE Tracking Form and your project informaticist will review and work with you to ensure changed CDEs are still able to be harmonized across data sets.
  • We want to be respectful and mindful of the communities you are partnering with and the science each of you are doing, while balancing the goals of the consortium.

What is the expectation for projects already under way?

  • We recognize that some projects are already in the field collecting data. Those projects will need to compare the data already being collected with the NIH CDEs. If there's a need to integrate CDEs into your collection form, you will need to file the necessary IRB amendments.
  • We recognize there may be items that you aren't able to add, in which case, you'll need to ensure those items are documented in your NIH CDE Tracking Form and submit a Prior Approval Request to the NIH.

How do NIH RADx-UP common data elements support vaccine research?

  • The current CDEs released on January 4, 2021 are already poised to enable vaccine research.
  • The CDEs contain two questions about flu, and up to five questions about the COVID-19 vaccine. Our working hypothesis is that participants who are willing to receive the flu vaccine will be more open to receiving the COVID-19 vaccine. For COVID-19, specifically, we ask whether participants have already received the vaccine and completed their vaccination course. We also query why participants would or would not receive the COVID-19 vaccine to explore factors for vaccine acceptance.
  • We do not currently have a question about COVID-19 vaccination date. This will be important to capture in order to explore how long immune response holds and if there are differences between the vaccines and immune response in different populations.

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