A Shovel‐Ready Solution to Fill the Nursing Data Gap in the Interdisciplinary Clinical Picture. Issue 1 (16th January 2017)

• Record Type: Journal Article
• Authors: Keenan, Gail M.; Lopez, Karen Dunn; Sousa, Vanessa E. C.; Stifter, Janet; Macieira, Tamara G. R.; Boyd, Andrew D.; Yao, Yingwei; Herdman, T. Heather; Moorhead, Sue; McDaniel, Anna; Wilkie, Diana J.
• Is Part Of: International Journal of Nursing Knowledge. Volume 29:Issue 1(2018:Jan.)
• Page Start: 49
• Page End: 58
• Publication Date: 2017-01-16
• Subjects: Big data science -- patient care planning -- standardized nursing terminology; Nursing diagnosis -- Periodicals; Nursing -- Terminology -- Periodicals; Nursing -- Practice -- Periodicals; 616.075
• DOI: 10.1111/2047-3095.12168
• Languages: English
• ISSNs: 2047-3087

Abstract

Abstract : PURPOSE: To critically evaluate 2014 American Academy of Nursing (AAN) call‐to‐action plan for generating interoperable nursing data. DATA SOURCES: Healthcare literature. DATA SYNTHESIS: AAN's plan will not generate the nursing data needed to participate in big data science initiatives in the short term because Logical Observation Identifiers Names and Codes and Systematized Nomenclature of Medicine – Clinical Terms are not yet ripe for generating interoperable data. Well‐tested viable alternatives exist. CONCLUSIONS: Authors present recommendations for revisions to AAN's plan and an evidence‐based alternative to generating interoperable nursing data in the near term. These revisions can ultimately lead to the proposed terminology goals of the AAN's plan in the long term.