Common Data Elements (CDEs) are a type of health data standard that is commonly used and reused in both clinical and research settings. CDEs provide a way to standardize data collection—ensuring that data are collected consistently, and otherwise-avoidable variability is minimized.
To fully benefit from the exponentially growing body of biomedical data, we need cutting-edge approaches that foster data access, analysis, sharing, and collaboration so novel scientific questions can be pursued. But the sheer volume, sometimes siloed nature, along with the costs and time associated with analyzing large datasets, can be difficult for some researchers. Recognizing these concerns, NIH is helping by hosting large data sets and bringing together computational tools and cloud technologies in ways that support open access, interoperability, and collaborative analyses. We encourage you to explore how these resources may help accelerate your research in ways not possible before. Read on for more…
Common Data Elements foster rigor, facilitate data sharing, and allow multiple datasets to be integrated. They also help make data more FAIR (Findable, Accessible, Interoperable, and Reusable). Many different CDEs are currently in use and can vary across research disciplines, so we would encourage researchers check out databases like the NIH CDE Repository for examples, tools, and other related resources. Through a recently released Request for Information (NOT-LM-21-005), we seek your thoughts on how you use CDEs, potential challenges to their adoption, and how NIH might facilitate and incentivize their use to help us plan future CDE-related efforts.
Today, nearly twenty years after the publication of the Final NIH Statement on Sharing Research Data in 2003, we have released a Final NIH Policy for Data Management and Sharing. This represents the agency’s continued commitment to share and make broadly available the results of publicly funded biomedical research. We hope it will be a critical step in moving towards a culture change, in which data management and sharing is seen as integral to the conduct of research. Responsible data management and sharing is good for science; it maximizes availability of data to the best and brightest minds, underlies reproducibility, honors the participation of human participants by ensuring their data is both protected and fully utilized, and provides an element of transparency to ensure public trust and accountability.
In this post, we would like to remind you of some of the important cybersecurity policies that apply to your NIH-supported research. These policies are designed to protect not only the NIH, but also you, your coworkers, your study participants, your institution, and your research. As healthcare and research institutions continue to face mounting threats from cyberattacks, it’s important that we all not only know how to protect sensitive information, but also make a personal commitment to keeping data safe.
Opportunity knocks for NIH researchers, who will be able to leverage clinical data from electronic health record (EHR) systems with increased frequency and consistency. The recently published final rule, which went into effect on June 30, 2020, and requires electronic health record (EHR) systems to provide the clinical data necessary for nationwide, interoperable health information exchange through the adoption of the U.S. Core Data for Interoperability (USCDI) standard.
Ever figured out a clever solution to a vexing challenge that affected the rigor of your work with laboratory animals, and then thought that those solutions could improve the quality and transparency of animal research supported across NIH? Recently found yourself at virtual lab meetings brainstorming ways to facilitate translating the findings from your animal study to human biology and disease? Questioned the status quo on how the research culture drives the choice of animal models and the design of experiments? Well, we want to know more.
NIH has released for public comment a Draft NIH Policy for Data Management and Sharing along with supplemental draft guidance. Let the NIH know what you think works and what doesn’t in the proposed policy by submitting your comments through the web-portal no later than January 10, 2020.
NIH is currently accepting public comments on the use of standards for capturing, integrating, and exchanging clinical data for research purposes (NOT-OD-19-150). This is a great opportunity to hear more from the community on ways to strengthen approaches that find, share, and access high-quality patient data, while also making it more interoperable and reusable. Such goals align with long-standing NIH data sharing policies and what was also called for in a related NIH strategic plan on data science.
On May 22, I had the privilege of participating in a terrific national conference that focused on what institutions can do to foster a culture of research integrity. I was also given the opportunity to present my thoughts on promoting research integrity, something I have written about before. My talk dealt with approaches institutions may take to foster a culture of research integrity, and I wanted to share it here as a resource for others.
