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Related Concept Videos

Nursing Clinical Information System01:27

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Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
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Trends in nursing are multifactorial and associated with changes in society, within the nursing profession, and in other professions. Notably, telehealth and remote nursing contribute to successful healthcare delivery for numerous patients and help reduce stress for nurses due to nursing shortages. Nurses can reach patients, monitor their conditions, and interact with them using computers, audio, visual accessories, and telephones—for example, remote patient monitoring systems. Likewise,...
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Quality documentation and reporting share essential characteristics that ensure they are practical and valuable resources for those who use them. These characteristics are:
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Creating and executing a nursing diagnosis helps nurses plan care and guide patient, family, and community interventions. They are developed based on a patient's physical evaluation and support measuring the outcomes. It is not recommended to select random interventions throughout the planning process. Instead, consider the following six essential factors when choosing interventions:
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Related Experiment Video

Updated: Jun 11, 2025

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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Natural language processing in the intensive care unit: A scoping review.

Julia K Pilowsky1,2,3, Jae-Won Choi1,4, Aldo Saavedra1,2

  • 1Agency for Clinical Innovation, NSW Health, Australia.

Critical Care and Resuscitation : Journal of the Australasian Academy of Critical Care Medicine
|October 2, 2024
PubMed
Summary

Natural Language Processing (NLP) is increasingly used in intensive care for tasks like predicting outcomes and identifying conditions. Wider adoption of these AI techniques could enhance clinical research and quality improvement in critical care.

Keywords:
Artificial intelligenceIntensive care medicineNatural language processingScoping review

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Area of Science:

  • Artificial Intelligence
  • Clinical Informatics
  • Natural Language Processing

Background:

  • Intensive care units (ICUs) generate vast amounts of text data.
  • Natural Language Processing (NLP) applications are underutilized in critical care research and quality improvement.
  • NLP offers potential for analyzing clinical text data.

Purpose of the Study:

  • To review the current applications of NLP in the intensive care specialty.
  • To promote understanding of NLP's future clinical potential in critical care.
  • To synthesize findings from recent NLP research in intensive care.

Main Methods:

  • A scoping review methodology was employed.
  • A systematic search of the PubMed database was conducted for articles from the last 10 years.
  • Data extraction and narrative synthesis were performed by independent reviewers.

Main Results:

  • Eighty-seven articles were included in the review.
  • The most common NLP applications involved predicting clinical outcomes (e.g., mortality) and identifying specific clinical concepts (e.g., sepsis).
  • Most studies focused on algorithm development and internal validation, with limited clinical implementation.

Conclusions:

  • NLP has diverse applications within the ICU, including outcome prediction and concept identification.
  • Increased clinician awareness of NLP techniques can foster the development of clinically relevant algorithms.
  • Further implementation of NLP tools in clinical settings is warranted to realize their full potential.