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

Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

1.2K
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...
1.2K
Nursing Clinical Information System01:27

Nursing Clinical Information System

760
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:
760
Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

564
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.
For example, a patient with a chronic...
564
Assessment of the Gastrointestinal System II: Health Perception Pattern01:29

Assessment of the Gastrointestinal System II: Health Perception Pattern

87
Assessing the gastrointestinal (GI) system is a complex process that begins with collecting subjective data. This data, collected through patient interviews, provides crucial insights into the patient's health history, perception patterns, and lifestyle habits, all contributing significantly to GI health.
Health Perception Patterns
Health perception patterns offer valuable insights into a patient's lifestyle habits and how they may impact their GI health. These patterns include:
87
Data Validation01:03

Data Validation

5.0K
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...
5.0K
Methods of Documentation III: PIE01:21

Methods of Documentation III: PIE

1.4K
Problem-intervention-evaluation (PIE) is a systematic approach to documentation used in healthcare settings for clinical decision-making and patient care planning. It is a structured approach to organizing patient data based on problems, interventions, and evaluations. Here's a breakdown of its key features and considerations:
1.4K

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

Towards Data Quality Assessment and Standardized Representability of German Healthcare Claims Data for Secondary Use.

Studies in health technology and informatics·2026
Same author

Evaluating Prompt Strategies for LLM-Based De-Identification of German Discharge Letters: A Feasibility Study Using GraSCCo.

Studies in health technology and informatics·2026
Same author

Meet NUM-ENRICH: A Collaborative National Effort to Extend and Harmonize Research Infrastructures Within the German Network University Medicine.

Studies in health technology and informatics·2026
Same author

From Data Holder to Intermediary Entity: An Approach for the Evolving Role of Data Integration Centers in the European Health Data Space.

Studies in health technology and informatics·2026
Same author

Health research requires the linking of healthcare-related data.

Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany))·2026
Same author

New and Rare Taxa of <i>Lepidoziaceae</i> (<i>Marchantiophyta</i>) in East Indochina (Southeast Asia).

Plants (Basel, Switzerland)·2026
Same journal

A GenAI Pipeline for Violinist Kinematic Data Management.

Studies in health technology and informatics·2026
Same journal

AMAL-For-Qatar: A Comprehensive AI Ecosystem for Fetal Ultrasound Analysis - Project Overview and Achievements.

Studies in health technology and informatics·2026
Same journal

Longitudinal Treatment-Aware Multimodal AI for Dermatology: A Scoping Review.

Studies in health technology and informatics·2026
Same journal

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026
Same journal

Validation of Deep-Learning Models for Autosegmentation of Brain Metastases.

Studies in health technology and informatics·2026
Same journal

Delay-Dependent Gating in Modular RNNs.

Studies in health technology and informatics·2026
查看所有相关文章

相关实验视频

Updated: Jun 14, 2025

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
09:00

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

Published on: April 13, 2021

4.4K

在临床系统中从通用数据结构中检索模式的挑战 - - 技术案例报告

Richard Gebler1, Hung Manh Nguyen1, Luise Donat1

  • 1Institute for Medical Informatics and Biometry, Faculty of Medicine and University Hospital Carl Gustav Carus, Dresden University of Technology, Dresden, Germany.

Studies in health technology and informatics
|September 5, 2024
PubMed
概括
此摘要是机器生成的。

本研究提出了一种方法,将复杂的实体属性值 (EAV) 临床数据转换为可用于研究的格式. 该方法简化了数据分析,并提高了医疗研究中二次使用的数据完整性.

关键词:
数据整合数据集成数据管理数据管理实体属性值数据库 实体属性值数据库健康信息的互操作性 互操作性信息存储和检索 信息存储和检索

更多相关视频

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

15.9K
Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

6.2K

相关实验视频

Last Updated: Jun 14, 2025

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
09:00

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

Published on: April 13, 2021

4.4K
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

15.9K
Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

6.2K

科学领域:

  • 临床信息学 临床信息学
  • 健康数据管理 管理健康数据
  • 医学研究方法学 医学研究方法学

背景情况:

  • 在临床环境中二次数据的使用提供了研究潜力,但在实体-属性-值 (EAV) 等通用数据结构方面面临挑战.
  • 由于EAV模型在临床信息系统中的适应性,由于其垂直结构和动态图表,复杂化了用于研究的数据检索.
  • 为研究提取和分析EAV数据需要专门的方法来克服固有的复杂性.

研究的目的:

  • 在临床环境中开发一种处理通用数据结构的方法方法,特别是实体-属性-值 (EAV) 模型.
  • 将基于EAV的临床数据转换为适合增强医学研究和实践的格式.
  • 为了应对与EAV数据结构相关的数据检索和分析的挑战.

主要方法:

  • 开发了一种五步方法方法,涉及了解临床过程,分析数据源结构和元数据,逆转用例特定的数据结构,分析医疗信息的内容,以及管理模式变化.
  • 该方法侧重于将前端数据输入映射到其存储格式,并在数据中建立连接.
  • 在整个转换过程中,重点是保持数据完整性.

主要成果:

  • 将该方法应用于医院信息系统,成功将基于EAV的数据转换为结构化,适合研究的格式.
  • 转换过程减少了数据稀疏性,并提高了模式更改的可管理性.
  • 在EAV数据转换过程中,其他数据类别的完整性没有受到影响.

结论:

  • 开发的方法提供了一个系统的框架,用于管理复杂的数据关系,并确保使用EAV模型的临床系统中的数据完整性.
  • 这种方法促进了临床数据的二次使用,从而增加了其对医学研究和临床实践的价值.
  • 该方法为克服EAV结构化临床数据数据提取和分析障碍提供了可行的解决方案.