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相关概念视频

Methods of Documentation VII: EMR01:30

Methods of Documentation VII: EMR

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Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
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Healthcare Agencies I01:18

Healthcare Agencies I

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Healthcare agencies provide healthcare services to people. In the United States, voluntary agencies are often non-profit centers sponsored by donations, grants, or fundraisers. One such organization is Meals on Wheels, which provides meals to the elderly and homebound. The American Heart Association and the American Lung Association are other non-profit community organizations. Doctors and nurses are frequently active members of these organizations, which offer health checks and educational...
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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
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Ethical standards are the backbone of nursing practice, guiding nurses as they interact with patients, families, and colleagues. These standards are crucial for providing safe, empathetic care centered on the patient's needs.
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Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
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The nursing history captures and records the patient's health status, so that a care plan evolves to meet the patient's individual needs. The nursing health history is a part of the initial assessment. A comprehensive history covers all health dimensions and plays a significant role in the assessment process. A comprehensive history includes the patient's biographical information, reasons for seeking health care, expectations, present and past health history, medications, and...
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在使用无监督表示学习的顺序电子医疗数据中发现患者组.

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来自电子健康记录 (EHR) 的无监督学习创建了患者特定的功能. 这些特征揭示了儿科重症监护中的患者个人资料和治疗方法的显著差异,证明了临床实用性.

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科学领域:

  • 计算生物学是一种计算生物学.
  • 医疗信息学医学信息学

背景情况:

  • 自然语言处理 (NLP) 启发的无监督特征学习方法可以从纵向电子健康记录 (EHR) 中获得患者特征.
  • 这些方法为分析复杂的患者数据提供了一种新的方法.

研究的目的:

  • 将文档嵌入算法应用于儿科重症监护室 (PICU) EHR数据.
  • 从1853名患者的ICU行程中提取患者特定的特征.
  • 通过K-means集群评估这些特征的临床实用性.

主要方法:

  • 文档嵌入算法应用于包括实验室测试和药物事件在内的EHR数据.
  • 训练了一种文档嵌入模型,并用于生成潜在的患者特征向量.
  • 在患者载体上进行了K-means聚类以进行下游分析.

主要成果:

  • 在所有1853名患者中成功生成了潜在患者特征向量.
  • 无监督集群确定了5个不同的患者集群.
  • 跨集群观察到患者特征,手术干预和诊断资料的显著变化 (p<0.0001).

结论:

  • K-means集群证实了从嵌入算法中获得的患者特征的临床实用性.
  • 学习的潜在患者特征直接适用于其他机器学习算法.
  • 未来的研究将纳入时间EHR信息,并扩展嵌入算法,用于个性化患者旅程预测.