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Related Concept Videos

Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

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The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic...
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Documentation in Long-Term and Home Healthcare Setting01:29

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Documentation in long-term care facilities and home healthcare settings is crucial for ensuring continuous, coordinated, and comprehensive care for patients. Each setting has its specific documentation processes and tools:
Long-Term Care Facilities
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Introduction to Documentation and Reporting01:20

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Documentation is the systematic process of formally recording, maintaining, and communicating information.
Nursing documentation records essential information and details regarding a patient's care and treatment in written or electronic form. It is a critical aspect of nursing practice that involves documenting assessments, interventions, outcomes, and other relevant details about a patient's health status.
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Methods of Documentation III: PIE01:21

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Problem-intervention-evaluation (PIE) is a systematic approach to documentation used in healthcare settings for clinical decision-making and patient care planning. It is a structured approach to organizing patient data based on problems, interventions, and evaluations. Here's a breakdown of its key features and considerations:
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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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Nursing Clinical Information System01:27

Nursing Clinical Information System

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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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Updated: May 20, 2025

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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Improving Clinical Documentation with Artificial Intelligence: A Systematic Review.

Scott W Perkins, Justin C Muste, Taseen A Alam

    Perspectives in Health Information Management
    |March 26, 2025
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    Summary
    This summary is machine-generated.

    Artificial Intelligence (AI) tools can enhance clinical documentation by structuring data and identifying errors, potentially reducing clinician opportunity costs. However, fully automated AI documentation assistants are not yet available in published research.

    Keywords:
    Artificial intelligenceautomationclinical guidelinesdocumentationelectronic health recordsinformatics

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    Area of Science:

    • Medical Informatics
    • Clinical Documentation Improvement
    • Artificial Intelligence in Healthcare

    Background:

    • Clinicians spend substantial time on clinical documentation, leading to significant opportunity costs.
    • Artificial Intelligence (AI) presents a potential solution for enhancing documentation quality and efficiency.

    Purpose of the Study:

    • To systematically review peer-reviewed AI tools designed to improve clinical documentation.
    • To understand how AI applications can mitigate the opportunity costs associated with documentation.

    Main Methods:

    • A systematic review of PubMed, Embase, Scopus, and Web of Science databases.
    • Inclusion of original, English-language studies published up to July 2024 focusing on AI tool development, application, and validation for clinical documentation.
    • Extraction and analysis of 129 studies from 673 initial candidates.

    Main Results:

    • AI tools enhance documentation through data structuring, note annotation, quality evaluation, trend identification, and error detection.
    • Real-time AI assistance during patient visits shows moderate accuracy, limiting widespread adoption.
    • No end-to-end AI documentation assistant with high accuracy has been reported in peer-reviewed literature.

    Conclusions:

    • Current AI techniques, particularly data structuring, offer targeted improvements to clinical documentation workflows.
    • Further research and development are needed to achieve highly accurate, comprehensive AI solutions for clinical documentation.
    • AI holds promise for reducing clinician burden and opportunity costs in healthcare documentation.