Towards implementing SNOMED CT in nursing practice: A scoping review

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Abstract

Background: Currently, it is rare for nursing data to be available in data repositories due to the quality of nursing data collected in clinical practice. To improve the quality of nursing data, the American Nurses Association recommends the use of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) for coding nursing problems, interventions, and observations in electronic health records. Objective: To determine “what is known about the use of SNOMED terminology (Pre-SNOMED CT and SNOMED CT) in nursing”. Methods: We searched four databases and two search engines. We identified 29 articles for review. A modified version of System Development Life Cycle (SDLC), and Mapping Evaluation Assessment (MEA), created by the authors were used for quality assessment. Results: All 29 studies mapped standardized (n = 19) or local nursing terms (n = 10) to the SNOMED terminology. MEA scores ranged from 2-8 (range 0-11) with 25 receiving scores from 5-8. On the modified SDLC (range 0–5), all studies exhibited activities of stage 0 (pre-application integration), with two studies describing integration and preliminary testing of SNOMED CT coded nursing content in applications (stage 2). Conclusion: Though efforts are underway to ensure adequate coverage of nursing in SNOMED CT, there were no studies indicating use in nursing practice. The authors offer recommendations for achieving the widespread collection of interoperable SNOMED CT coded nursing data in clinical applications to evaluate nursing's impact on patient outcomes. These include creating a clear professional vision and path to our data goals that builds on sound rationale and evidence, abundant stakeholder engagement, and sufficient resources.

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Kim, J., Macieira, T. G. R., Meyer, S. L., Ansell (Maggie), M., Bjarnadottir (Raga), R. I., Smith, M. B., … Keenan, G. M. (2020, February 1). Towards implementing SNOMED CT in nursing practice: A scoping review. International Journal of Medical Informatics. Elsevier Ireland Ltd. https://doi.org/10.1016/j.ijmedinf.2019.104035

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