ArticleInternational journal of medical informatics2024
Standardizing nursing data extracted from electronic health records for integration into a statewide clinical data research network.
Article in International journal of medical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Trajectories of Nursing Care During the Critical and Intensive Phases After Coronary Artery Bypass Graft Surgery: A Retrospective Observational Study.Journal of advanced nursing · 2026Observational
- Standardized nursing terminologies in primary care: a qualitative approach to the experience of nursing professionals.BMC nursing · 2026Article
- Exploring common data model coverage of nursing flowsheet data: a pilot study using SNOMED CT and LOINC mapping.JAMIA open · 2025Article
- Standardized Nursing Terminologies and Electronic Health Records: A Secondary Analysis of a Systematic Review.Healthcare (Basel, Switzerland) · 2025Review
- Deciphering the Link Between Diagnosis-Related Group Weight and Nursing Care Complexity in Hospitalized Children: An Observational Study.Children (Basel, Switzerland) · 2025Article
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Authors and funding
11 authors.
Funding
Abstract
backgroundCare plans documented by nurses in electronic health records (EHR) are a rich source of data to generate knowledge and measure the impact of nursing care. Unfortunately, there is a lack of integration of these data in clinical data research networks (CDRN) data trusts, due in large part to nursing care being documented with local vocabulary, resulting in non-standardized data. The absence of high-quality nursing care plan data in data trusts limits the investigation of interdisciplinary care aimed at improving patient outcomes.
objectiveTo map local nursing care plan terms for patients' problems and goals in the EHR of one large health system to the standardized nursing terminologies (SNTs), NANDA International (NANDA-I), and Nursing Outcomes Classification (NOC).
methodsWe extracted local problems and goals used by nurses to document care plans from two hospitals. After removing duplicates, the terms were independently mapped to NANDA-I and NOC by five mappers. Four nurses who regularly use the local vocabulary validated the mapping.
results83% of local problem terms were mapped to NANDA-I labels and 93% of local goal terms were mapped to NOC labels. The nurses agreed with 95% of the mapping. Local terms not mapped to labels were mapped to the domains or classes of the respective terminologies.
conclusionMapping local vocabularies used by nurses in EHRs to SNTs is a foundational step to making interoperable nursing data available for research and other secondary purposes in large data trusts. This study is the first phase of a larger project building, for the first time, a pipeline to standardize, harmonize, and integrate nursing care plan data from multiple Florida hospitals into the statewide CDRN OneFlorida+ Clinical Research Network data trust.
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Registered trials
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