ArticleJournal of the American Medical Informatics Association : JAMIA2023
Utilizing standardized nursing terminologies in implementing an AI-powered fall-prevention tool to improve patient outcomes: a multihospital study.
Article in Journal of the American Medical Informatics Association : JAMIA, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 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
- Enhancing multimodal inpatient fall prediction via nursing statement integration within the OMOP common data model.Scientific reports · 2026Article
- Implications for Virtual Nursing Role Development in Acute Nursing Care: 24-Hour Time-and-Motion Study.JMIR nursing · 2026Article
- Developing a Subset of ICNPHealthcare (Basel, Switzerland) · 2026Article
- Cognitive readiness of nurses regarding artificial intelligence predictions: understanding through the dual lens of verbatim and gist knowledge.JAMIA open · 2026Article
- Voices From the Frontline: A Qualitative Study of Nurses' Experiences With Documentation and Its Influence on Patient Safety.Journal of nursing management · 2026Article
- Exploring common data model coverage of nursing flowsheet data: a pilot study using SNOMED CT and LOINC mapping.JAMIA open · 2025Article
- Enhancing Adverse Event Reporting With Clinical Language Models: Inpatient Falls.Journal of advanced nursing · 2025Observational
- Standardized Nursing Terminologies and Electronic Health Records: A Secondary Analysis of a Systematic Review.Healthcare (Basel, Switzerland) · 2025Review
- An example of leveraging AI for documentation: ChatGPT-generated nursing care plan for an older adult with lung cancer.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Evaluating the validity of the nursing statements algorithmically generated based on the International Classifications of Nursing Practice for respiratory nursing care using large language models.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Nurses' perceptions, experience and knowledge regarding artificial intelligence: results from a cross-sectional online survey in Germany.BMC nursing · 2024Article
- Standardized nursing terminologies come of age: advancing quality of care, population health, and health equity across the care continuum.Journal of the American Medical Informatics Association : JAMIA · 2023Article
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Authors and funding
5 authors.
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Abstract
objectivesStandardized nursing terminologies (SNTs) are necessary to ensure consistent knowledge expression and compare the effectiveness of nursing practice across settings. This study investigated whether SNTs can support semantic interoperability and outcoming tracking over time by implementing an AI-powered CDS tool for fall prevention across multiple EMR systems. MATERIALS AND
methodsThe study involved 3 tertiary academic hospitals and 1 public hospital with different EMR systems and nursing terms, and employed an AI-powered CDS tool that determines the fall risk within the next hour (prediction model) and recommends tailored care plans (CDS functions; represented by SNTs). The prediction model was mapped to local data elements and optimized using local data sets. The local nursing statements in CDS functions were mapped using an ICNP-based inpatient fall-prevention catalog. Four implementation models were compared, and patient outcomes and nursing activities were observed longitudinally at one site.
resultsThe postimplementation approach was practical for disseminating the AI-powered CDS tool for nursing. The 4 hospitals successfully implemented prediction models with little performance variation; the AUROCs were 0.8051-0.9581. The nursing process data contributed markedly to fall-risk predictions. The local nursing statements on preventing falls covered 48.0%-86.7% of statements. There was no significant longitudinal decrease in the fall rate (P = .160, 95% CI = -1.21 to 0.21 per 1000 hospital days), but rates of interventions provided by nurses were notably increased.
conclusionSNTs contributed to achieving semantic interoperability among multiple EMR systems to disseminate AI-powered CDS tools and automatically track nursing and patient outcomes.
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