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

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques13:44

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

4.2K
Here, we present a protocol for the behavioral analysis of a project-based learning methodology for health sciences students (20-56 years old). The protocol facilitates the comparison of the participants' performance in e-Learning versus blended-Learning (b-Learning) through a monitoring tool. The results are analyzed using Educational Data Mining and qualitative...
4.2K
Secondary Data Collection Methods01:29

Secondary Data Collection Methods

2.5K
Secondary data collection offers significant advantages, making it essential in research. It is cost-effective, saving time and resources compared to primary data collection. Researchers can access extensive datasets from government databases, academic publications, and industry reports, providing comprehensive insights and enabling longitudinal analysis. Evaluating the reliability and validity of sources is crucial to ensure that data is credible, current, and relevant, providing a solid...
2.5K
CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data07:11

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

3.3K
We present CorrelationCalculator and Filigree, two tools for data-driven network construction and analysis of metabolomics data. CorrelationCalculator supports building a single interaction network of metabolites based on expression data, while Filigree allows building a differential network, followed by network clustering and enrichment analysis.
3.3K
Data Reporting and Recording01:24

Data Reporting and Recording

5.3K
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...
5.3K
Workflow and Framework for Collecting and Implementing Point-of-Care Ultrasound Data in the Management of Heart Failure Patients03:47

Workflow and Framework for Collecting and Implementing Point-of-Care Ultrasound Data in the Management of Heart Failure Patients

1.1K
This protocol presents a scalable workflow for the use of point-of-care ultrasound in the management of hospitalized and outpatient heart failure...
1.1K
Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI10:35

Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI

33.3K
Simultaneous electroencephalography (EEG) and functional Magnetic Resonance imaging (fMRI) is a powerful neuroimaging tool. However, the inside of an MRI scanner forms a difficult environment for EEG data recording and safety must be considered whenever operating EEG equipment inside a scanner. Here, we present an optimised EEG-fMRI data acquisition...
33.3K

You might also read

Related Articles

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

Sort by
Same author

Evaluating the Fitness for Purpose of Primary Care Data from Electronic Health Records for Automated Antimicrobial Prescribing Audits.

Applied clinical informatics·2026
Same author

A culturally-safe primary care intervention for migrant/refugee women suffering domestic violence and abuse: HARMONY-a pragmatic cluster randomised controlled trial.

BMC medicine·2026
Same author

EngageEMR: Codesigning resources to promote patient and carer engagement with their hospital electronic medical record.

Patient education and counseling·2026
Same author

Strengthening Care for Children Using a Virtual Integrated General Practitioner-Pediatrician Model of Primary Care (SUSTAIN): Protocol for a Stepped Wedge Cluster Randomized Controlled Trial.

JMIR research protocols·2026
Same author

Clinician perspectives on linked electronic health records for preventing type 2 diabetes after gestational diabetes in primary care-an Australian qualitative study.

BMJ open·2025
Same author

Developing and validating a risk prediction model for conversion to type 2 diabetes mellitus in women with a history of gestational diabetes mellitus: protocol for a population-based, data-linkage study.

BMJ open·2025
Same journal

Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry.

EGEMS (Washington, DC)·2019
Same journal

A Spatial Analysis of Health Disparities Associated with Antibiotic Resistant Infections in Children Living in Atlanta (2002-2010).

EGEMS (Washington, DC)·2019
Same journal

Predicting the Incidence of Pressure Ulcers in the Intensive Care Unit Using Machine Learning.

EGEMS (Washington, DC)·2019
Same journal

Cardiovascular Health Trends in Electronic Health Record Data (2012-2015): A Cross-Sectional Analysis of The Guideline Advantageâ„¢.

EGEMS (Washington, DC)·2019
Same journal

Understanding U.S. Health Systems: Using Mixed Methods to Unpack Organizational Complexity.

EGEMS (Washington, DC)·2019
Same journal

Colonoscopy Indication Algorithm Performance Across Diverse Health Care Systems in the PROSPR Consortium.

EGEMS (Washington, DC)·2019
See all related articles

Related Experiment Video

Updated: Jan 19, 2026

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
13:44

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

4.2K

Improving a Secondary Use Health Data Warehouse: Proposing a Multi-Level Data Quality Framework.

Sandra Henley-Smith1, Douglas Boyle1, Kathleen Gray1

  • 1University of Melbourne, AU.

EGEMS (Washington, DC)
|September 19, 2019
PubMed
Summary
This summary is machine-generated.

Existing data quality frameworks lack contextual understanding for secondary data use. This study introduces a two-level framework to ensure data quality and relevance for specific health research questions.

Keywords:
data qualitydata warehouseelectronic health records

More Related Videos

Secondary Data Collection Methods
01:29

Secondary Data Collection Methods

2.5K
Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

3.3K

Related Experiment Videos

Last Updated: Jan 19, 2026

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
13:44

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

4.2K
Secondary Data Collection Methods
01:29

Secondary Data Collection Methods

2.5K
Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

3.3K

Area of Science:

  • Health Informatics
  • Data Management
  • Information Science

Background:

  • Data quality frameworks have evolved significantly in IT and healthcare.
  • Current frameworks inadequately address the context of data use for secondary purposes.

Purpose of the Study:

  • To refine and expand existing data quality frameworks.
  • To incorporate contextual requirements for data assessment.
  • To ensure data quality for secondary health data use.

Main Methods:

  • Literature review to identify relevant research.
  • Refinement and expansion of an existing data quality framework.
  • Application of synthesized concepts to a health data warehouse.

Main Results:

  • A novel two-level data quality framework was developed.
  • The framework maintains intrinsic data value.
  • The framework indicates data suitability for specific research questions.

Conclusions:

  • Existing frameworks are often one-dimensional and inflexible.
  • This work systematically addresses framework shortcomings.
  • Contextualized data quality management is crucial for secondary health data use.