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Methods of Documentation VI: Case Management Model01:15

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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.
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Current trends in nursing include:
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Planning Nursing Care I01:21

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The planning phase of the nursing process helps nurses set priorities, outline patient-centered goals and expected outcomes, and tailor nursing interventions to align with the aligned care plan. Through the planning phase, the nurse applies critical thinking skills to align and develop interventions according to the patient's needs. It provides continuity of care allowing patients to receive the maximum benefit from treatment. It serves as a pilot plan for allocating individual staff to a...
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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: Jun 16, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
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使用病床管理数据预测未来重症监护病床的可用性.

John Palmer1, Areti Manataki2, Laura Moss3,4

  • 1Center for Medical Informatics, The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK.

BMJ health & care informatics
|August 19, 2024
PubMed
概括

仅使用医院病床管理数据来预测重症监护病床的可用性是可行的. 这种数据驱动的方法可以预测容量,而不需要敏感的患者信息,从而增强资源规划.

关键词:
计算方法的计算方法.数据科学数据科学数据科学决策支持系统,管理管理系统.机器学习 机器学习

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科学领域:

  • 医疗信息学 医疗信息学
  • 计算机建模 计算建模
  • 数据科学数据科学数据科学

背景情况:

  • 准确预测重症监护病床的可用性对于有效的医院资源管理至关重要.
  • 现有的方法可能需要复杂的患者级数据,这带来隐私和后勤挑战.

研究的目的:

  • 用数据驱动的计算预测建模来评估预测重症监护病床容量的可行性.
  • 确定是否常规收集的医院病床管理数据足以进行预测.

主要方法:

  • 一个概念验证,单一中心可行性研究,利用前性收集数据的回顾性分析.
  • 将基于回归和分类的数据科学技术应用于全医院的病床管理数据.
  • 预测重症监护病床在1,7和14天的时间内可用.

主要成果:

  • 仅使用医院病床管理数据和可解释模型,证明了预测重症监护病床容量的可行性.
  • 与14天预测 (AUC 0.73) 相比,在1天预测 (AUC 0.78) 中获得了更好的预测性能.
  • 功能重要性分析表明依赖于重症监护和时间数据,而不是来自其他病房的数据.

结论:

  • 仅使用医院病床管理数据的数据驱动预测工具可以预测重症监护病床的可用性.
  • 这种新的方法消除了在预测建模中对患者敏感数据的需求.
  • 需要进一步的研究来完善这种方法,以便在其他医院环境中得到更广泛的应用.