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Related Concept Videos

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:
Patient-centered Care01:13

Patient-centered Care

Patient-centered care involves delivering care beyond inpatient hospitalization. Reflective practice can enhance a patient-centered approach. Reflective practice is a process of reasoning that considers all aspects of the present situation, including practicalities, learning from personal practice, and consideration of patient needs. Patients appreciate care decisions made while considering their input. Involving the patient in their care provides the patient with a sense of contribution rather...
Critical Thinking II01:25

Critical Thinking II

Critical thinking is a cognitive process with several attributes. The attributes of critical thinking include the following:
Critical Thinking I01:24

Critical Thinking I

Critical thinking helps decision-making and allows nurses to recognize barriers to success and find solutions to possible issues. It helps to brainstorm and implement ideas to achieve goals. Critical thinking helps acknowledge and state workflow inefficiencies while improving management techniques. Nurses understand the value of critical thinking and look for fellow nurses with critical thinking skills to upgrade their professional standards. Critical thinking can advance a nurse's career with...
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 Process for Patient and Caregiver Teaching I: Assessment and Diagnosis01:24

Nursing Process for Patient and Caregiver Teaching I: Assessment and Diagnosis

The nursing process provides a clinical decision-making framework for patients and families to establish and implement a personalized care plan. Since part of the nurse's duties is to teach patients, the steps of the nursing process are the most effective way to approach instruction. The nursing process and the teaching-learning process are inextricably linked.
It is critical to determine the patient's learning needs during the assessment. Determination of learning needs compounds data from the...

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Related Experiment Video

Updated: Jun 21, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

What can natural language processing do for clinical decision support?

Dina Demner-Fushman1, Wendy W Chapman, Clement J McDonald

  • 1U.S. National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. ddemner@mail.nih.gov

Journal of Biomedical Informatics
|August 18, 2009
PubMed
Summary
This summary is machine-generated.

Computerized clinical decision support (CDS) uses natural language processing (NLP) to leverage clinical narrative for better healthcare decisions. This review highlights recent NLP advancements for CDS, addressing unique challenges in clinical language and user needs.

Related Experiment Videos

Last Updated: Jun 21, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Area of Science:

  • Health Informatics
  • Artificial Intelligence
  • Computational Linguistics

Background:

  • Computerized clinical decision support (CDS) systems provide crucial health information at the point of care.
  • Natural language processing (NLP) is essential for extracting and utilizing information from clinical free-text data.
  • The field has seen a resurgence in fundamental NLP research specifically for CDS applications.

Purpose of the Study:

  • To review recent advancements in NLP methods and systems tailored for clinical decision support.
  • To discuss the challenges and current solutions related to distinct clinical sublanguages, user groups, and support objectives within NLP for CDS.

Main Methods:

  • Literature review focusing on recent developments in NLP for CDS.
  • Analysis of NLP techniques applied to clinical narrative and knowledge representation.
  • Discussion of strategies for addressing linguistic diversity and varied goals in CDS.

Main Results:

  • Renewed interest in fundamental NLP methods for CDS.
  • Advances in NLP systems enabling better utilization of clinical narrative.
  • Identification of solutions for challenges posed by specialized clinical language and diverse user needs.

Conclusions:

  • NLP is pivotal for enhancing CDS by unlocking insights from clinical text.
  • Ongoing research in NLP is crucial for developing more effective and adaptable CDS tools.
  • Addressing linguistic nuances and user-specific requirements is key to successful NLP-driven CDS implementation.