A national action plan for sharable and comparable nursing data to support practice and translational research for transforming health care

Bonnie L. Westra, Gail E. Latimer, Susan A. Matney, Jung I n Park, Joyce Sensmeier, Roy L. Simpson, Mary J o Swanson, Judith J. Warren, Connie W. Delaney

Research output: Contribution to journalArticlepeer-review

57 Scopus citations


Background There is wide recognition that, with the rapid implementation of electronic health records (EHRs), large data sets are available for research. However, essential standardized nursing data are seldom integrated into EHRs and clinical data repositories. There are many diverse activities that exist to implement standardized nursing languages in EHRs; however, these activities are not coordinated, resulting in duplicate efforts rather than building a shared learning environment and resources. Objective The purpose of this paper is to describe the historical context of nursing terminologies, challenges to the use of nursing data for purposes other than documentation of care, and a national action plan for implementing and using sharable and comparable nursing data for quality reporting and translational research. Methods In 2013 and 2014, the University of Minnesota School of Nursing hosted a diverse group of nurses to participate in the Nursing Knowledge: Big Data and Science to Transform Health Care consensus conferences. This consensus conference was held to develop a national action plan and harmonize existing and new efforts of multiple individuals and organizations to expedite integration of standardized nursing data within EHRs and ensure their availability in clinical data repositories for secondary use. This harmonization will address the implementation of standardized nursing terminologies and subsequent access to and use of clinical nursing data. Conclusion Foundational to integrating nursing data into clinical data repositories for big data and science, is the implementation of standardized nursing terminologies, common data models, and information structures within EHRs. The 2014 National Action Plan for Sharable and Comparable Nursing Data for Transforming Health and Healthcare builds on and leverages existing, but separate long standing efforts of many individuals and organizations. The plan is action focused, with accountability for coordinating and tracking progress designated.

Original languageEnglish (US)
Pages (from-to)600-607
Number of pages8
JournalJournal of the American Medical Informatics Association
Issue number3
StatePublished - May 1 2015

Bibliographical note

Funding Information:
In August 2013, the University of Minnesota School of Nursing and its Center for Nursing Informatics hosted a group of 40 leaders/organization stakeholders at the inaugural Nursing Knowledge: Big Data Research to Transform Health Care consensus conference. Participants were invited based on their expertise and to represent a diverse range of organizations: practice settings (health systems, community-based settings), education (both university educators and nurses from the American Association of Colleges of Nursing and the National League for Nursing), informatics organizations (American Medical Informatics Association (AMIA), Health Information Management Systems Society (HIMSS) Alliance for Nursing Informatics, American Academy of Nursing Informatics Expert Panel), research (NINR), standards organizations (LOINC, HL7, IHE, and the ONC Standards and Interoperability Framework), federal and state organizations (National Quality Forum, Minnesota e-Health Initiative), national nursing specialty organizations, EHR and other informatics vendors, and potential funding organizations (NINR, Agency for Healthcare Research and Quality, Robert Wood Johnson Foundation).

Publisher Copyright:
© The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved.


  • Consensus development conference
  • Electro health records
  • National health policy
  • Nursing informatics
  • Terminology


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