Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Nursing Clinical Information System01:27

Nursing Clinical Information System

1.2K
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:
1.2K
Data Validation01:03

Data Validation

6.3K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
6.3K
Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

3.3K
Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
3.3K
Quality Assurance01:19

Quality Assurance

956
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
956
Nursing Interventions II: Selecting and Classifying the Nursing Interventions01:29

Nursing Interventions II: Selecting and Classifying the Nursing Interventions

3.1K
Creating and executing a nursing diagnosis helps nurses plan care and guide patient, family, and community interventions. They are developed based on a patient's physical evaluation and support measuring the outcomes. It is not recommended to select random interventions throughout the planning process. Instead, consider the following six essential factors when choosing interventions:
3.1K
Guidelines For Measuring Vital Signs01:19

Guidelines For Measuring Vital Signs

2.7K
Following these guidelines can help nurses accurately measure vital signs, assess changes in patient conditions, and provide timely treatment when necessary. Adhering closely to the guidelines ensures the accuracy and reliability of the results.
Before taking a patient's vital signs, a nurse would consider and assess the patient's comfort level and ensure appropriate equipment is available.
2.7K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Digital biomarkers in non-communicable diseases.

Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals·2026
Same author

[Post-Intensive Care Syndrome - The Potential of Digital Aftercare for Integrated Cross-Sectoral Care].

Deutsche medizinische Wochenschrift (1946)·2026
Same author

AI-Supported, Integrative Prediction of Postoperative Delirium: Protocol for the CONFUSED Study.

JMIR research protocols·2026
Same author

Organizational Tensions in the Implementation of Modifiable Off-the-Shelf Technologies in a University Hospital: Qualitative Multimethod Study.

JMIR human factors·2026
Same author

The predicted body weight equation overestimates lung sizes of female, critically ill patients: an analysis of randomized, controlled trials and real-world clinical data.

Intensive care medicine·2026
Same author

The Patient Monitoring Roundtable as Catalyst for Health Care Innovation: Case Study.

Journal of participatory medicine·2026
Same journal

Correction: Call for Decision Support for Electrocardiographic Alarm Administration Among Neonatal Intensive Care Unit Staff: Multicenter, Cross-Sectional Survey.

Journal of medical Internet research·2026
Same journal

A Futures Framework for Clinical AI Governance: Anticipating Emerging Risks, Shifting Roles, and Regulatory Challenges.

Journal of medical Internet research·2026
Same journal

Using a Large Language Model to Support Thematic Analysis of Patient Experiences in Chronic Illness Management: Comparative Qualitative Study.

Journal of medical Internet research·2026
Same journal

Combined Internet-Based Cognitive Behavioral Therapy and Face-to-Face Physiotherapy in Primary Health Care for Chronic Widespread Pain: Randomized Controlled Trial.

Journal of medical Internet research·2026
Same journal

Operationalizing Digital Health Equity in Artificial Intelligence-Enabled Patient Decision Aids for Older Adults: Mixed Methods Study.

Journal of medical Internet research·2026
Same journal

Automated Prediction of Glasgow Coma Scale Scores From Unstructured Electronic Health Records Using Natural Language Processing: Development and Validation Study.

Journal of medical Internet research·2026
查看所有相关文章

相关实验视频

Updated: Jan 16, 2026

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies
10:38

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies

Published on: January 16, 2019

20.8K

密集护理医学的计算机可解释的质量指标:开发和验证研究研究

Falk von Dincklage1, Viktor Karl Bublitz1, Oliver Kumpf2

  • 1Department of Anesthesia, Intensive Care, Emergency and Pain Medicine, University Medicine Greifswald, Greifswald, Germany.

Journal of medical Internet research
|September 26, 2025
PubMed
概括
此摘要是机器生成的。

这项研究将德国重症监护质量指标 (QI) 标准化为计算机可解释的快速医疗互操作资源 (FHIR) 格式. 这使得自动化质量管理和在各医疗机构进行可比评估成为可能.

关键词:
菲希尔 (FHIR) 是一个人.快速医疗互操作性资源 互操作性资源临床质量评估临床质量评估可以通过计算机解释的规则.电子质量测量 电子质量测量重症监护医学的重症监护医学的医学.质量指标质量指标语义互操作性的语义互操作性标准化 标准化 标准化

更多相关视频

Monitoring Lung Function with Electrical Impedance Tomography in the Intensive Care Unit
05:56

Monitoring Lung Function with Electrical Impedance Tomography in the Intensive Care Unit

Published on: September 6, 2024

6.0K
Objective Nociceptive Assessment in Ventilated ICU Patients: A Feasibility Study Using Pupillometry and the Nociceptive Flexion Reflex
06:04

Objective Nociceptive Assessment in Ventilated ICU Patients: A Feasibility Study Using Pupillometry and the Nociceptive Flexion Reflex

Published on: July 4, 2018

9.2K

相关实验视频

Last Updated: Jan 16, 2026

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies
10:38

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies

Published on: January 16, 2019

20.8K
Monitoring Lung Function with Electrical Impedance Tomography in the Intensive Care Unit
05:56

Monitoring Lung Function with Electrical Impedance Tomography in the Intensive Care Unit

Published on: September 6, 2024

6.0K
Objective Nociceptive Assessment in Ventilated ICU Patients: A Feasibility Study Using Pupillometry and the Nociceptive Flexion Reflex
06:04

Objective Nociceptive Assessment in Ventilated ICU Patients: A Feasibility Study Using Pupillometry and the Nociceptive Flexion Reflex

Published on: July 4, 2018

9.2K

科学领域:

  • 医疗信息学 医疗信息学
  • 临床质量测量临床质量测量
  • 在医疗保健中的标准化.

背景情况:

  • 质量指标 (QI) 对于评估和改进重症监护医学至关重要.
  • 德国重症监护和急救医学跨学科协会 (DIVI) 开发了重症监护的QA.
  • 当前技术实施的变化阻碍了设施之间的可比质量评估.

研究的目的:

  • 使用快速医疗互操作资源 (FHIR) 开发 DIVI QI 的明确,计算机可解释的表示.
  • 建立一个可复制的流程,将叙事QA转化为标准化的数字格式.

主要方法:

  • 将DIVI QI分解为患者群体和护理方面的概念.
  • 将概念映射到国际词汇中,为缺失的术语创建一个补充代码系统.
  • 在FHIR中使用先前开发的实施指南实现了QA.
  • 通过反向翻译和专家临床审查验证了FHIR表示.

主要成果:

  • 成功将10个DIVI QI转化为31个可测量的指标 (9个结构指标,17个过程指标,5个结果指标).
  • 所有的过程和结果指标都在FHIR中表现出来,使用了58个独特的医疗概念 (90%与国际词汇进行了映射).
  • 标准的FHIR机制完全支持嵌套的布尔逻辑和时间条件,经过专家小组准确度的批准.

结论:

  • 一个结构化的流程可以为自动化质量管理提供明确的,计算机可解释的QI表示.
  • 标准化的数字QA可以提高医疗保健机构之间的质量评估可比性.
  • 开发的过程和FHIR表示可供重复使用,可以作为其他医学专业的蓝图.