Request for Information (RFI) on Next Directions for the National Library of Medicine’s Unified Medical Language System®

Notice Number: NOT-LM-20-001

Key Dates
Release Date: October 23, 2019

Related Announcements

Issued by
National Library of Medicine (NLM)



Created in 1986, the National Library of Medicine’s (NLM) Unified Medical Language System (UMLS) integrates and distributes key terminology, classification and coding standards, and associated resources to promote creation of effective and interoperable biomedical information systems and services, including electronic health records. It is a set of files and software that brings together many health and biomedical vocabularies and standards to enable interoperability between computer systems. For the past 30 years, researchers, health care providers, industry/vendors, and others have utilized the terminological resources of the UMLS in various applications of natural language processing, text processing, search retrieval, data extraction, and other applications. With recent advancements and improvements (e.g., artificial intelligence, AI) in computer processing, NLM is reviewing the computational infrastructure of the UMLS to consider how to improve its efficiency and utility, and to support modern use cases.

Through this RFI, NLM seeks stakeholder input on how to improve the UMLS. Additionally, NLM will conduct at least one public informational webinar that presents proposed ideas for improving UMLS. The input received from these efforts will be considered by NLM in the development of future versions of the UMLS.

Information Requested

In support of the NLM Strategic Plan, 2017-2027, and NIH Strategic Plan for Data Science, the goal of this effort is to make the UMLS leaner, stronger, and more useful. As such, NLM is requesting public comment on the considerations listed in the bullets that follow. Response to this Notice is voluntary, and respondents are free to address any or all of the topics listed or other topics not listed:

  • Considerations of focusing the UMLS Metathesaurus primarily on concept synonyms, inter-concept relationships and mappings between concepts, including:
    • Attributes that could be removed
    • Vocabularies that may be removed
    • Ways of customizing presentation for specific use cases
    • Customization processes (e.g., sub setting through MetamorphoSys) that could be removed
    • Whether UMLS should retain the capability to reconstruct native versions of the source terminologies from its contained vocabularies when they can be obtained from those sources directly
  • Considerations for enhancing the UMLS Metathesaurus content, including:
    • Vocabularies that might be added, especially those that would improve alignment with the work of other NIH Institutes and Centers and other stakeholders
    • Structure of the content that would facilitate use in health data science and analytics
    • Better support for access to retired codes to facilitate longitudinal data analysis
  • Considerations for enhancing the UMLS Metathesaurus distribution, including:
    • Integration of the UMLS into Fast Healthcare Interoperability Resources (FHIR) vocabulary services
    • Enhancing the application programming interface (API) to support mapping
    • Consideration of the use of cloud computing such that independent developers/users can implement their own processing technology against a cloud version of UMLS
  • Consideration for the use of machine learning/AI to support and enhance the UMLS Metathesaurus creation process
  • Considerations for modifying/simplifying the UMLS license for supporting open science
  • Any other topic which may be relevant for NLM to consider in modernizing UMLS

Submitting a Response

Comments should be submitted electronically to the following webpage: by January 11, 2020.

This Notice is for planning purposes only and should not be construed as a policy, solicitation for applications, or as an obligation on the part of the Government to provide support for any ideas identified in response to it. Please note that the Government will not pay for the preparation of any information submitted or for its use of that information.

Please do not include any proprietary, classified, confidential, or sensitive information in your response. The Government reserves the right to use any non-proprietary technical information in summaries of the state of the science, and any resultant solicitation(s). The NIH may use information gathered by this Notice to inform development of future funding opportunity announcements and policy development.


Please direct all inquiries to:

Liz Amos
Office of the Director, National Library of Medicine
Telephone: 301-287-4291