Assessing the Proficiency of Emergency and Critical Care Nurses in Electrocardiogram Interpretation and the Integration of Computerized Electrocardiogram Analysis--Benefits and Limitations: A Systematic Review.

Purpose: This systematic review aimed to evaluate electrocardiogram interpretation competency among emergency and critical care nurses and to examine the diagnostic performance, benefits, and limitations of computerized and artificial intelligence--based electrocardiogram interpretation systems. Met...

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Publicado en:Korean Journal of Adult Nursing Vol. 38; no. 2; pp. 139 - 155
Autores principales: Alwahsh, Amer Hussein, Hasanien, Amer A.
Formato: research systematic review tables/charts Journal Article
Publicado: Korean Society of Adult Nursing May2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2026
      vid: 38
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      pub: Korean Society of Adult Nursing
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        10.7475/kjan.2025.1125
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        atl: Assessing the Proficiency of Emergency and Critical Care Nurses in Electrocardiogram Interpretation and the Integration of Computerized Electrocardiogram Analysis--Benefits and Limitations: A Systematic Review.
      aug:
        au:
          Alwahsh, Amer Hussein
          Hasanien, Amer A.
        affil: Graduate Student PhD Candidate, Department of Clinical Nursing, The University of Jordan School of Nursing, Amman, Jordan
      sug:
        subj:
          Emergency Nurses Psychosocial Factors
          Critical Care Nurses Psychosocial Factors
          Clinical Competence Evaluation
          Electrocardiography
          Artificial Intelligence
          Diagnosis, Computer Assisted
          Human
          Female
          Male
          Systematic Review
          Descriptive Statistics
          Checklists
          Heart Arrest Diagnosis
          Arrhythmia
          Myocardial Ischemia
          Decision Support Systems, Clinical
          Critical Care Nursing
          Emergency Nursing
          Professional Competence
          Medline
          Embase
          CINAHL Database
          Cochrane Library
          Gray Literature
          Female
          Male
      ab: Purpose: This systematic review aimed to evaluate electrocardiogram interpretation competency among emergency and critical care nurses and to examine the diagnostic performance, benefits, and limitations of computerized and artificial intelligence--based electrocardiogram interpretation systems. Methods: This systematic review was conducted in accordance with PRISMA 2020 guidelines and registered in the International Prospective Register of Systematic Reviews under registration number CRD420251169307. Six electronic databases and additional sources were searched for studies published between January 2020 and October 2025, with the final search conducted in October 2025. Studies were included if they involved registered nurses interpreting electrocardiograms in acute care settings or evaluated computerized electrocardiogram interpretation systems using adult datasets. Methodological quality was assessed using validated tools appropriate to study design, including the Joanna Briggs Institute critical appraisal tools, ROBINS-I, and QUADAS-2. Results: Mean electrocardiogram interpretation scores among nurses ranged from 43% to 68%, with fewer than 40% of participants meeting predefined competency thresholds. Performance was strongest for asystole recognition and weakest for tachyarrhythmias, myocardial ischemia, and conduction abnormalities. Artificial intelligence--based systems demonstrated high diagnostic accuracy, with area under the curve values ranging from 0.91 to 0.97 and sensitivity exceeding 94% across major diagnostic tasks. Conclusion: Emergency and critical care nurses demonstrated insufficient electrocardiogram interpretation competency in several safety-critical domains. Computerized and artificial intelligence--based systems showed high diagnostic accuracy and may serve as effective complementary tools when integrated with ongoing nurse education and appropriate clinical oversight.
      pubtype: Academic Journal
      doctype:
        research
        systematic review
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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