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Related Concept Videos

Nursing Diagnosis01:22

Nursing Diagnosis

Following assessment, a nursing diagnosis is the next step in the nursing process. It begins after the nurse has collected and recorded the patient data. The purpose of diagnosing is to identify how the client responds to actual or potential health processes, identify factors that bestow or that cause health problems, the etiologies, and identify resources or strengths the individual, group, or community can draw on to prevent or resolve problems.
The nursing diagnosis focuses on evidence-based...
Formulating and Validating Nursing Diagnosis I01:26

Formulating and Validating Nursing Diagnosis I

A nursing diagnosis is written when the nurse recognizes a cluster of essential patient data indicating health problems treated with independent nursing interventions. The standardized terminologies of a nursing diagnosis help nurses identify and treat patients' problems. Every electronic health record that uses nursing diagnosis must employ standard diagnostic terminology. Developing an efficient, individualized care plan begins with accurate nursing diagnoses.
There are thirteen domains for...
Formulating and Validating Nursing Diagnosis II01:25

Formulating and Validating Nursing Diagnosis II

Nursing diagnoses represent a problem validated by major defining characteristics. There are four categories of nursing diagnoses: problem-focused, risk, health promotion or wellness, and syndrome. The anatomy of a nursing diagnosis includes three components: problem statement or diagnostic label, defining characteristics, and related factors.
Risk nursing diagnoses represent clinical judgments of an individual, family, or community more vulnerable to developing the health problem than others...
Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters assessment...
Nursing Interventions II: Selecting and Classifying the Nursing Interventions01:29

Nursing Interventions II: Selecting and Classifying the Nursing Interventions

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:
Nursing Clinical Information System01:27

Nursing Clinical Information System

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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Related Experiment Video

Updated: Jul 3, 2026

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

Optimizing ICU Care: Advancing Nursing Diagnoses with a Decision Support System.

Cynthia Abi Khalil1,2, Antoine Saab1,3, Akram Redjdal4

  • 1Sorbonne Université, INSERM, Université Sorbonne Paris Nord, Limics 75006 Paris, France.

Studies in Health Technology and Informatics
|May 17, 2025
PubMed
Summary

VIGIL Care, a clinical decision support system, enhances the Nursing Process (NP) in ICUs by identifying key nursing diagnoses (NDs). It shows promise in improving accuracy and efficiency in critical care settings.

Keywords:
Clinical Decision Support SystemsIntensive Care UnitsNursing DiagnosisNursing Process

Related Experiment Videos

Last Updated: Jul 3, 2026

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

Area of Science:

  • Nursing Informatics
  • Clinical Decision Support Systems
  • Critical Care Nursing

Background:

  • The Nursing Process (NP) is crucial for evidence-based patient care, with Nursing Diagnoses (NDs) forming a foundational step.
  • Optimizing NP in high-acuity environments like Intensive Care Units (ICUs) presents unique challenges.
  • Existing methods for ND identification can be time-consuming and may not always capture the complexity of ICU patient needs.

Purpose of the Study:

  • To develop and evaluate VIGIL Care, a clinical decision support system (CDSS) aimed at improving the accuracy and efficiency of NP in ICUs.
  • To refine a curated list of relevant nursing diagnoses and their indicators for ICU settings.
  • To assess the system's performance in proposing patient-specific NDs and supporting nursing autonomy.

Main Methods:

  • A Delphi method was employed with 13 experts to select 32 high-criticality/prevalence NDs from the NANDA-I taxonomy (2024-2026) for ICU care.
  • A panel refined diagnostic indicators for the selected NDs, identifying highly or moderately relevant ones.
  • VIGIL Care was developed, integrating patient data with logical rules to suggest NDs, featuring an explainable user interface.

Main Results:

  • VIGIL Care demonstrated 86% sensitivity and 78% specificity in assessing 10 NDs across 20 patient cases.
  • The system outperformed traditional nursing assessments, particularly under time constraints.
  • The developed system supports nursing decisional autonomy through its explainable interface.

Conclusions:

  • VIGIL Care represents a promising advancement in CDSS for enhancing NP in ICUs.
  • The system's ability to identify relevant NDs efficiently suggests potential for improved patient outcomes.
  • Further validation with larger sample sizes is recommended to confirm the system's effectiveness and generalizability in critical care settings.