Health Data Standards: A Common Language to Support Research and Health Care

Guest post by Dianne Babski, Associate Director for Library Operations and Robin Taylor, MLIS, National Library of Medicine

Every day we benefit from data standards, and every day most of us don’t even notice it! Did you wear a seatbelt today? Take a precise dose of medicine? Send an email? Plug a laptop into an outlet? These are examples of activities that are made possible through data standards. At NLM, we think a lot about data standards, particularly health data standards.

NLM partners with organizations such as the Office of the National Coordinator for Health Information Technology (ONC) to promote health data standards for data captured in electronic health records (EHRs), clinical research, and other health information systems. With a focus on how health data are collected, stored, described, and retrieved, health data standards make up the backbone of interoperability. This provides the ability to connect and seamlessly share data between computerized systems and allows for the information exchange between other applications and databases.

Let’s look at a current example where health data standards, a common data language, have had a real impact. When SARS-CoV-2, and the disease it causes, COVID-19, emerged in late 2019, researchers around the world began planning studies to figure out how to combat this global pandemic. Research questions, such as, “What date did the patient first display COVID-19 symptoms?” arose continuously. It sounds like a simple question, but there are so many ways to ask the question, and even more possible responses. If researchers apply health data standards in their investigations — if they ask questions and collect responses in a standardized way — the data they collect can be combined and compared with data from other COVID-19 studies and EHRs. This enables reuse of data across multiple sources, which increases statistical power and accelerates our understanding of this disease.  

For more than 20 years, NLM has served as the central coordinating body for clinical terminology standards nationally. Our long-standing efforts to establish common health terminology supported the COVID-19 response by allowing access to near-real time clinical information to guide the diagnosis, treatment, and prevention of this disease.

NLM supports multiple vocabulary standards and mappings, like RxNorm, SNOMED CT, and the UMLS, as well as terminology tools like AccessGUDID, DailyMed, MedlinePlus Connect, MetaMap, the Value Set Authority Center (VSAC), and the NIH CDE Repository, a database that provides access to structured human and machine-readable definitions of common data elements, more commonly referred to as CDEs.

CDEs are one type of health data standard that can help researchers normalize data across studies. CDEs are standardized, precisely defined questions that are paired with a set of specific allowable responses, then used systematically across different sites, studies, or clinical trials to ensure consistent data collection.

CDEs are in use across NIH, to varying degrees. Some NIH institutes and Centers have had mature CDE programs for years; others are just beginning to develop. NLM has been involved with CDEs since 2012 and plays a key role in encouraging CDE adoption across NIH by:

• Hosting the NIH CDE Task Force (CDETF), a trans-NIH community of practice.
• Forming a CDE Governance Committee that reports to the CDETF. The committee’s primary charge is to decide whether common data elements submitted to them by NIH recognized bodies (NIH Institutes, offices, etc.) meet criteria that merit their recommendation for use in NIH-funded research.
• Maintaining the NIH CDE Repository, a central access point to data elements that have been recommended or required by NIH Institutes and Centers for use in research and for other purposes. In 2020, we completed a usability study of the NIH CDE Repository and have been implementing enhancements based on the recommendations.

This year, while continuing to enhance the usability of the NIH CDE Repository, we will also engage with users through a CDE awareness and training campaign.