Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Purpose of Health Records I01:11

Purpose of Health Records I

1.2K
The vital purpose of health records is to provide a complete and accurate account of a patient's medical history, including communication, diagnostic and therapeutic orders, care planning, research, and quality review.
Here's a breakdown of how health records serve these purposes:
1.2K
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
Data Reporting and Recording01:24

Data Reporting and Recording

4.7K
Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
4.7K
Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

573
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...
573
Guidelines for Nursing Documentation I01:30

Guidelines for Nursing Documentation I

1.1K
Quality documentation and reporting share essential characteristics that ensure they are practical and valuable resources for those who use them. These characteristics are:
Factual:  
The following points emphasize the significance of upholding accurate and unbiased documentation in healthcare.
1.1K
Introduction to Documentation and Reporting01:20

Introduction to Documentation and Reporting

2.0K
Documentation is the systematic process of formally recording, maintaining, and communicating information.
Nursing documentation records essential information and details regarding a patient's care and treatment in written or electronic form. It is a critical aspect of nursing practice that involves documenting assessments, interventions, outcomes, and other relevant details about a patient's health status.
Documentation maps the patient's health journey by creating a comprehensive...
2.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Data Management in Forensic Medicine: A Proposal for a Layered Architecture Model.

Studies in health technology and informatics·2026
Same author

Proposal of a procedure to stratify the reidentification risk of medical data: RIMEDA.

BMC medical informatics and decision making·2026
Same author

Proposal for Using AI to Assess Clinical Data Integrity and Generate Metadata: Algorithm Development and Validation.

JMIR medical informatics·2025
Same author

Transferring Structured Medical Data from Hospital to Rehabilitation Facilities Using HL7 FHIR and openEHR.

Studies in health technology and informatics·2025
Same author

Non-invasive infrared thermography for screening, diagnosis and monitoring of skin cancer.

Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG·2024
Same author

Interoperable Integration of Automatic ECG Processing Using DICOMweb and the AcuWave Software Suite.

Studies in health technology and informatics·2024

Related Experiment Video

Updated: Jul 5, 2025

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

FAIR+R: Making Clinical Data Reliable Through Qualitative Metadata.

Caroline Bönisch1, Dorothea Kesztyüs1, Tibor Kesztyüs1

  • 1Medical Data Integration Center, Department of Medical Informatics, University Medical Center Göttingen, Robert-Koch-Str. 40, 37075 Göttingen, Germany.

Studies in Health Technology and Informatics
|January 25, 2024
PubMed
Summary
This summary is machine-generated.

Metadata quality is crucial for reliable data sharing in clinical repositories. This study proposes nine measures and adds a fifth "Reliability" block to the FAIR Guiding Principles for better data assessment.

Keywords:
FAIRdata qualitymetadatareliable data

More Related Videos

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
11:02

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

539
The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
06:05

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

Published on: February 19, 2021

1.3K

Related Experiment Videos

Last Updated: Jul 5, 2025

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
Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
11:02

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

539
The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
06:05

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

Published on: February 19, 2021

1.3K

Area of Science:

  • Data Science
  • Information Science
  • Clinical Informatics

Background:

  • Metadata is essential for researchers accessing data repositories for secondary use.
  • The volume of metadata is increasing due to automatic generation and harvesting.
  • Current metadata quality in repositories often falls short of its potential, impacting data reliability.

Purpose of the Study:

  • To identify measures for assessing metadata quality in clinical care repositories.
  • To propose an extension to the FAIR Guiding Principles to include data reliability.
  • To lay the groundwork for assessing metadata quality in Medical Data Integration Centers (MeDICs).

Main Methods:

  • Conducted an extensive literature review to identify metadata assessment measures.
  • Synthesized findings to propose nine measures for metadata assessment.
  • Developed three new principles for data reliability, forming a fifth block for the FAIR Guiding Principles.

Main Results:

  • Identified nine key measures for assessing metadata quality in clinical repositories.
  • Proposed an enhanced FAIR Guiding Principles framework with an added block for Reliability.
  • Established a foundation for future metadata quality assessments in MeDICs.

Conclusions:

  • Metadata quality is a critical component for ensuring reliable data in secondary use.
  • The proposed reliability principles enhance the FAIR framework, promoting more trustworthy data.
  • This work provides a basis for improving metadata quality and data accessibility in clinical research settings.