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相关概念视频

Guidelines and Strategies for Safe Computer Charting01:18

Guidelines and Strategies for Safe Computer Charting

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The guidelines and strategies provided by the American Nurses Association (ANA) and the Canadian Nurses Association (CNA) offer essential principles for ensuring safe and secure computer charting systems in healthcare settings. Let's break down each recommendation:
Maintain Confidentiality and Security:
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Heart Failure VII: Nursing Interventions01:30

Heart Failure VII: Nursing Interventions

422
The first step in nursing management of a patient with heart failure involves thoroughly assessing the patient's medical history.Subjective Data: Obtain the patient's medical history of coronary artery disease, hypertension, myocardial infarction, and symptoms like dyspnea, orthopnea, and paroxysmal nocturnal dyspnea.Objective Data: Conduct a physical examination to identify findings such as jugular vein distention, pulmonary crackles, tachycardia, murmurs, peripheral edema, and vital signs,...
422
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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Rheumatic Heart Disease IV: Nursing Management01:20

Rheumatic Heart Disease IV: Nursing Management

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AssessmentA comprehensive assessment is essential in managing a patient with rheumatic heart disease (RHD). Begin with obtaining a detailed medical history, including recent streptococcal infections, a history of rheumatic fever, or previously diagnosed rheumatic heart disease. Assess the patient for symptoms such as fever, chest pain, widespread joint pain (arthralgia), tachycardia, pericardial friction rub, muffled heart sounds, heart murmurs, peripheral edema, subcutaneous nodules, and...
276
Dysrhythmias VII: Nursing Management of Dysrhythmias01:25

Dysrhythmias VII: Nursing Management of Dysrhythmias

370
Nursing management of dysrhythmias involves the following:AssessmentSubjective Assessment:The initial step involves gathering patient-reported symptoms such as dizziness, palpitations, and chest discomfort. It is crucial to collect a detailed history, including previous heart conditions, current medication use, and lifestyle factors like caffeine and alcohol consumption.Objective Assessment:This involves observing clinical signs such as jugular venous distention, cool and pale skin, and...
370
Current Trends in Nursing II01:30

Current Trends in Nursing II

3.3K
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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相关实验视频

Updated: Jan 17, 2026

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
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预测还是预防? 护士与电子早期预警系统的互动,以防跌倒风险.

Meriel McCollum, Yimei Wu, LeeAnna Spiva

    Joint Commission journal on quality and patient safety
    |September 13, 2025
    PubMed
    概括

    机器学习在医院中的跌倒警报是常见的,但护士经常忽视. 大多数患者跌倒发生在初级护士没有看到警报的情况下,这表明需要优化工作流程.

    科学领域:

    • 护理信息学 在护理信息学.
    • 临床决策支持系统临床决策支持系统
    • 机器学习在医疗保健中的应用

    背景情况:

    • 机器学习 (ML) 模型越来越多地被整合到电子健康记录中,用于风险评估和不良结果预测.
    • 关于ML技术如何影响护理工作流程,护士行为和患者结果的研究有限.

    研究的目的:

    • 探索护士与ML生成的跌倒警报的互动.
    • 检查警报和患者在护理工作流程中的关系.

    主要方法:

    • 追溯分析了四个医疗/外科单位的数据.
    • 从预测性跌倒模型中检查护士与中断警报的互动.
    • 警报与实际患者跌倒的时间相关性.

    主要成果:

    • 87.0%的入院产生了至少一个下降警报;1.5%导致了下降.
    • 大多数警报 (57.3%) 都是被偷偷看的;22.0%的警报是由非初级护士看到的.
    • 89.3%的跌倒是任何工作人员看到警报之前,但只有38.7%的初级护士.

    结论:

    • 主要护士往往没有接触到患者跌倒之前的警报.

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  • 通过"Snooze to Review"来驳回警报是常见的.
  • 需要进一步的研究来优化用于护理工作流程和患者安全的ML技术.