Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Statistical Software for Data Analysis and Clinical Trials

Statistical Software for Data Analysis and Clinical Trials

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...

Archival Research

Archival Research

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...

Methods of Documentation VII: EMR

Methods of Documentation VII: EMR

Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare settings,...

You might also read

Related Articles

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

Sort by

Same authorSame Topic

Using a translational data platform to create clinical-grade genome-informed risk assessments.

JAMIA open·2026

Same author

First endogenous case of <i>Blastomyces dermatitidis</i> ARDS in an immunocompetent man in Newfoundland and Labrador: Case report and mini-review.

Journal of the Association of Medical Microbiology and Infectious Disease Canada = Journal officiel de l'Association pour la microbiologie medicale et l'infectiologie Canada·2026

Same author

Generative artificial intelligence implementation in REDCap.

JAMIA open·2026

Same author

Palliative Dialysis: Putting the Person First in Dialysis Care.

American journal of kidney diseases : the official journal of the National Kidney Foundation·2026

Same author

Lonafarnib for chronic hepatitis delta: Clinical mechanism of action, development, and evolving role in combination therapy.

Antiviral research·2026

Same author

Multisite evaluation of automated electronic case report form data entry from electronic health records.

Journal of biomedical informatics·2026

Search research articles

Related Experiment Video

Updated: Jun 28, 2026

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

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

Published on: September 20, 2018

Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing

Paul A Harris¹, Robert Taylor, Robert Thielke

¹Department of Biomedical Informatics, Vanderbilt University, 2525 West End Avenue, Suite 674, Nashville, TN 37212, USA. paul.harris@vanderbilt.edu

Journal of Biomedical Informatics

|October 22, 2008

Summary

Research Electronic Data Capture (REDCap) offers a rapid solution for clinical and translational research data management. This metadata-driven system supports numerous projects across a global consortium, enhancing research efficiency and collaboration.

More Related Videos

Biobanking of Human Aqueous and Vitreous Liquid Biopsies for Molecular Analyses

Biobanking of Human Aqueous and Vitreous Liquid Biopsies for Molecular Analyses

Published on: September 11, 2023

Related Experiment Videos

Last Updated: Jun 28, 2026

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

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

Published on: September 20, 2018

Biobanking of Human Aqueous and Vitreous Liquid Biopsies for Molecular Analyses

Biobanking of Human Aqueous and Vitreous Liquid Biopsies for Molecular Analyses

Published on: September 11, 2023

Area of Science:

Clinical Research
Translational Science
Health Informatics

Background:

Clinical and translational research requires efficient data capture tools.
Developing custom electronic data capture (EDC) solutions can be time-consuming and resource-intensive.
A standardized, adaptable platform is needed to streamline research workflows.

Purpose of the Study:

To describe the Research Electronic Data Capture (REDCap) software and methodology.
To detail the utilization of study-related metadata within REDCap.
To present the impact, collaborative network, and system characteristics of REDCap.

Main Methods:

Description of the REDCap metadata-driven software toolset.
Explanation of metadata capture and utilization from research teams.
Analysis of REDCap's impact, consortium network, and system strengths/limitations.

Main Results:

REDCap facilitates the rapid development and deployment of EDC tools.
The system effectively captures and utilizes study-related metadata.
REDCap supports 286 translational research projects within a network of 27 institutions.

Conclusions:

REDCap is a robust, metadata-driven system enhancing clinical and translational research.
The collaborative consortium model fosters widespread adoption and impact.
REDCap offers a scalable solution for diverse research data management needs.