Guest post by NLM staff: David Anderson, UMLS Production Coordinator; Liz Amos, Special Assistant to the Chief Health Data Standards Officer; Anna Ripple, Information Research Specialist; and Patrick McLaughlin, Head, Terminology QA & User Services Unit.
Shortly after Donald A.B. Lindberg, MD was sworn in as NLM Director in 1984, he asked “What is NLM, as a government agency, uniquely positioned to do?” Through conversations with experts, Dr. Lindberg identified a looming question in the field of bioinformatics — How can machines act as if they understand biomedical meaning? At the time, the information necessary to answer this question was distributed across a variety of resources. Very few publicly available tools for processing biomedical text had been developed. NLM had experience with terminology development and maintenance (MeSH – Medical Subject Headings), coordinating distributed systems (DOCLINE), and distributing and providing access to large datasets (MEDLINE) in an era when this was a challenge.
As a national library, NLM was deeply interested in providing good answers to biomedical questions. For these reasons, NLM was uniquely positioned to develop a system — the Unified Medical Language System (UMLS) — that could lay the groundwork for machines to act as if they understand biomedical meaning. This year marks the 30th anniversary of the release of the first edition of the UMLS in November 1990.
Achieving the Unified Medical Language System
The result of a large-scale, NLM-led research and development project, the UMLS began with the audacious goal of helping computer systems behave as if they understand the meaning of the language of biomedicine and health. The UMLS was expected to facilitate the development of systems that could retrieve, integrate, and aggregate conceptually-related information from disparate electronic sources such as literature databases, clinical records, and databanks despite differences in the vocabularies and coding systems used within them, and in the terminology employed by users.
Under the direction of Dr. Donald Lindberg, then-Deputy Associate Director for Library Operations, Betsy Humphreys, and a multidisciplinary, international team from academia and the private sector, the UMLS evolved into an essential tool for enabling interoperability, natural language processing, information retrieval, machine learning, and other data science use cases.
UMLS Knowledge Sources
Central to the UMLS model is the grouping of synonymous names into UMLS concepts and the assignment of broad categories (semantic types) to all those concepts. Since its first release in 1990, NLM has continued to expand and update the UMLS Knowledge Sources based on feedback from testing and use.
The UMLS Metathesaurus was the first biomedical terminology resource organized by concept, and its development had a significant impact on subsequent medical informatics theory and practice. The broad terminology coverage, synonymy, and semantic categorization in the UMLS, in combination with its lexical tools, enable its primary use cases:
- identifying meaning in text,
- mapping between vocabularies, and
- improving information retrieval.
The growing increase in UMLS use over the past decade reflects broad developments in health policy, including the designation of SNOMED CT, LOINC, and RxNorm (three component vocabularies included in the UMLS Metathesaurus) as U.S. national standards for clinical data for quality improvement payment programs such as CMS’s Promoting Interoperability Programs (previously known as Meaningful Use). Many UMLS source vocabularies are also referenced in the United States Core Data for Interoperability (USCDI). Researchers continue to rely on the UMLS as a knowledge base for natural language processing and data mining. The UMLS community of users has developed several tools that enhance and expand the capabilities of the UMLS.
Celebrating 30 Years
Thirty years after the initial release of the UMLS Knowledge Sources, the UMLS resources continue to be of benefit to millions of people worldwide. The UMLS is used in NLM flagship applications such as PubMed and ClinicalTrials.gov. Additionally, some researchers and system developers use the UMLS to build or enhance electronic resources, clinical data warehouses, components of electronic health record systems, natural language processing pipelines, and test collections. UMLS resources are being used primarily as intended, to facilitate the interpretation of biomedical meaning in disparate electronic information and data in many different computer systems serving scientists, health professionals, and the public.
The Journal of the American Medical Informatics Association is commemorating the 30th UMLS anniversary with a special focus issue dedicated to the memory of Dr. Lindberg (1933–2019) that also includes information on current research and applications, broader impacts, and future directions of the UMLS.
Upon her retirement from NLM in 2017, Betsy Humphreys remarked that “systems that get used, get better.” As the UMLS enters its fourth decade, a review of UMLS production methods and priorities is underway with the same high standard goals with which it started – trailblazing into the future to improve biomedical information storage, processing and retrieval.
As we reflect on this important milestone, we want to thank stakeholders, like you, who have provided feedback over the years to help us make the UMLS leaner, stronger, and more useful.
Top row: David Anderson, UMLS Production Coordinator and Liz Amos, Special Assistant to the Chief Health Data Standards Officer
Bottom Row: Anna Ripple, Information Research Specialist and Patrick McLaughlin, Head, Terminology QA & User Services Unit