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相关概念视频

Role of Communication in the Nursing Process III: Evaluation and Documentation01:08

Role of Communication in the Nursing Process III: Evaluation and Documentation

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A successful patient outcome depends mainly on the evaluation stage of the nursing process. Evaluation determines effectiveness by reviewing what was done previously after the completion of nursing interventions. Every time a healthcare professional steps in or administers treatment, they must reassess or evaluate the action to ensure the intended result. During the evaluation phase, there are three probable patient outcomes:
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Guidelines for Nursing Documentation I01:30

Guidelines for Nursing Documentation I

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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:
Factual:  
The following points emphasize the significance of upholding accurate and unbiased documentation in healthcare.
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Documentation in Long-Term and Home Healthcare Setting01:29

Documentation in Long-Term and Home Healthcare Setting

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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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Guidelines for Nursing Documentation II01:26

Guidelines for Nursing Documentation II

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Effective documentation is an integral part of nursing practice. Here are some essential guidelines to follow when documenting patient care:
Timely documentation is crucial to ensure continuity of care for patients. Any delays in recording or reporting medical information can result in medical errors and even adverse patient outcomes. From medication administration to diagnostic test results, every detail must be accurately and promptly documented to provide the best possible care for patients.
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Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

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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...
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Formats for Nursing Documentation01:28

Formats for Nursing Documentation

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Nursing documentation encompasses various formats designed to capture precise patient data, facilitate communication among healthcare team members, and ensure comprehensive and accurate patient records. Let's explore each of these formats in detail:
Nursing Assessment Form:
• A nursing assessment form is a foundational document that captures detailed patient data from physical assessments and nursing histories.
• It includes patient demographics, medical history,...
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相关实验视频

Updated: Jul 16, 2025

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
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基于机器学习的语音识别系统用于护理文档 - 一项试点研究

Tso-Ying Lee1, Chin-Ching Li2, Kuei-Ru Chou3

  • 1Director of Nursing Research Center, Nursing Department, Taipei Medical University Hospital, Taipei, Taiwan; Associate Professor, School of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan.

International journal of medical informatics
|September 10, 2023
PubMed
概括

一个基于机器学习的语音识别系统在减少护理文档工作量方面表现有前途. 该系统在四次会议中获得了更高的准确性,这表明在临床记录管理中提高效率的潜力.

关键词:
人工智能的人工智能话语编写 话语编写 话语编写自然语言处理自然语言处理.护理文档护理文档语音识别 语音识别 语言识别

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科学领域:

  • 临床信息学 临床信息学
  • 医疗保健中的人工智能
  • 护理技术的护理技术

背景情况:

  • 护理文档是工作负载的重要贡献者.
  • 有效的记录保存对于有效的患者护理和医院运营至关重要.
  • 现有的记录方法对护理人员来说可能是耗时的.

研究的目的:

  • 评估基于机器学习的语音识别 (SR) 系统的有效性.
  • 评估该系统对减少护士打字记录的临床工作量的影响.
  • 在现实世界精神病房设置中测试SR系统.

主要方法:

  • 基于深度学习的SR引擎使用医院护理数据进行训练.
  • 21名护士与传统键盘输入一起评估了SR系统.
  • 记录时间和识别错误率在四个会议中进行了比较.

主要成果:

  • 该SR系统处理了超过3万个单词,准确度越来越高.
  • 平均准确度从第一个会话中的87.06%提高到第四个会话中的95.07%.
  • 该系统的平均处理速度为每秒0.928个单词.

结论:

  • 基于机器学习的SR系统显示了可接受的准确性和减轻护士文档负担的潜力.
  • 需要持续改进以解决SR转录错误.
  • 需要进一步的研究,以使SR在跨专业的护理数字记录中得到最佳整合.