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

Data Validation01:03

Data Validation

7.2K
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...
7.2K
Clinical Trials01:16

Clinical Trials

11.1K
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
11.1K
Clinical Trials: Overview01:11

Clinical Trials: Overview

5.3K
Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
5.3K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.8K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.8K
Reliability and Validity01:29

Reliability and Validity

14.3K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
14.3K

You might also read

Related Articles

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

Sort by
Same author

Increasing age is associated with elevated circulating interleukin-6 and enhanced temporal summation of mechanical pain in people living with HIV and chronic pain.

Pain reports·2026
Same author

Factors Associated with Diet Quality in Middle-Aged and Older Adults with HIV: Insights from the PROSPER-HIV study.

medRxiv : the preprint server for health sciences·2026
Same author

Longitudinal Effects of Adolescent Digital Media Use on Mental Health in Young Adulthood.

Children (Basel, Switzerland)·2026
Same author

Influence of the low-frequency extension filter on accelerometer-based activity measurements in people with HIV: a comparative analysis.

AIDS (London, England)·2026
Same author

A Theory Informed Multi-Component Intervention to Promote Family Medicine Provider PrEP Prescription to Adolescent Girls and Young Women in the U.S. Southeast: Pilot Trial Results.

Journal of primary care & community health·2025
Same author

Opportunities for Low-Barrier HIV Testing in the U.S. Deep South: Findings from a Survey in Alabama.

AIDS and behavior·2025
Same journal

Medical students' use of large language models: a national survey.

International journal of medical informatics·2026
Same journal

BlockFedMed: A blockchain-federated learning framework for privacy-preserving mortality prediction across heterogeneous intensive care units.

International journal of medical informatics·2026
Same journal

Integrating clinical decision support systems in pediatric oncology: A scoping review of applications, implementation gaps, and management Implications.

International journal of medical informatics·2026
Same journal

Understanding digital health capability of allied health professionals - a mixed-methods study with content validity analysis.

International journal of medical informatics·2026
Same journal

On-premises open-source large language models for privacy-preserving multimodal depression screening.

International journal of medical informatics·2026
Same journal

Data mining methods, tasks, and algorithms for adverse drug reaction analysis in pharmacovigilance: A scoping review.

International journal of medical informatics·2026
See all related articles

Related Experiment Video

Updated: Mar 16, 2026

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

5.5K

Validating the extract, transform, load process used to populate a large clinical research database.

Michael J Denney1, Dustin M Long2, Matthew G Armistead1

  • 1Biomedical Informatics, West Virginia Clinical and Translational Science Institute, Morgantown, WV, USA.

International Journal of Medical Informatics
|August 11, 2016
PubMed
Summary
This summary is machine-generated.

Validating the extract, load, and transform (ETL) process for clinical data warehouses ensures data integrity. This study confirmed 100% accuracy in data extraction from electronic health records (EHRs) into a data repository.

Keywords:
Clinical data warehouseCorrectnessElectronic health recordExtract transform loadInformatics

More Related Videos

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
11:18

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research

Published on: January 22, 2011

16.5K
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

6.9K

Related Experiment Videos

Last Updated: Mar 16, 2026

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

5.5K
Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
11:18

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research

Published on: January 22, 2011

16.5K
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

6.9K

Area of Science:

  • Health Informatics
  • Clinical Data Management
  • Translational Science

Background:

  • Clinical research infrastructure relies on populating research databases from operational systems like electronic health records (EHRs).
  • Data extraction, transformation, and loading (ETL) processes are critical for maintaining data integrity during this transfer.
  • The West Virginia Clinical and Translational Science Institute developed an Integrated Data Repository (IDR) using data from two EHR systems.

Purpose of the Study:

  • To validate the correctness of the ETL process used for extracting data into the Integrated Data Repository (IDR).
  • To ensure the accuracy and integrity of clinical data transferred from EHR systems to a central data warehouse.

Main Methods:

  • Randomly selected 498 observations from the Integrated Data Repository (IDR).
  • Compared these observations against the two source electronic health record (EHR) systems.
  • Categorized and analyzed discordant observations to identify sources of discrepancies.

Main Results:

  • Out of 498 observations, 479 were concordant, and 19 were discordant between the IDR and source EHRs.
  • Discordances were attributed to design differences, timing issues, and user interface settings.
  • After resolving discrepancies, the IDR achieved 100% accuracy relative to its source EHR systems.

Conclusions:

  • The validation of the ETL process is crucial for ensuring the accuracy of data used in clinical research.
  • As secondary use of EHR data expands, rigorous validation of data extraction processes is essential.
  • Institutions developing clinical data warehouses must prioritize the validation of their ETL procedures.