Cited by 51,384Research Data Management PracticesElectronic Health Records SystemsScientific Computing and Data Management

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index; none of the 6 sources its claims cite is checked for support yet.

Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support

Open access
Harris, Paul A., Taylor, Robert, Thielke, Robert, Payne, Jonathon, Gonzalez, Nathaniel, Conde, Jose G.·2009·Journal of Biomedical Informatics

Abstract

Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.

Overview

Integrity signals

Registry

Crossref · 10.1016/j.jbi.2008.08.010

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

16 Own interpretation · 10 No basis given · 8 Own result · 4 Not checked yet

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  • It may state two separate claims as one. 16
  • Probably not a substantial claim. 16
27 of 27
  • The paper relies on this without support.

    The need to collect and share data securely with numerous collaborators across academic departments or institutions is a formidable challenge.

    “However, the need to collect and share data in a secure manner with numerous collaborators across academic departments or even institutions is a formidable challenge.”
  • The paper relies on this without support.

    The need for researcher-controlled data services and secure data collection, storage, and export is universal for any single- or multi-center research study.

    “Most important, the need for researcher-controlled data services and secure data collection, storage and export is a universal need for any single- or multi-center research study.”
  • The paper relies on this without support.

    The academic research environment typically has many preclinical investigator-initiated research studies requiring fewer subjects than larger trials.

    “Although costs can be justified in large organizations running multiple sponsored clinical trials, the academic research environment is typically home to many preclinical investigator-initiated research studies requiring a fraction of the subjects needed for larger trials.”
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Metadata

Authors
Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G.
Affiliations
  • Vanderbilt University (US)
  • Medical College of Wisconsin (US)
  • University of Puerto Rico System (PR)
Corresponding author
Harris, Paul A.
Venue
Journal of Biomedical Informatics
Publisher
Elsevier BV
Published
2009-04
Volume
42
Issue
2
Pages
377-381
ISSN
1532-0464 (ISSN-L)
OpenAlex
W2093274439
Cited by
51,384
References
5
Citations by year
2026: 5202 · 2025: 6530 · 2024: 6650 · 2023: 5897 · 2022: 6019 · 2021: 5548 · 2020: 4337 · 2019: 3000 · 2018: 2318 · 2017: 1841 · 2016: 1426 · 2015: 1083 · 2014: 703 · 2013: 414 · 2012: 227
FWCI
116.65
Type
journal article
Language
en
Open access
Locations
  • Journal of Biomedical Informatics (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Center for Research Resources (G12-RR-03051, 5 M01 RR 00095, M01RR000095, M01RR000058, KL2RR024977, TL1RR024978, UL1RR024975, G12RR003051)
  • National Institute on Minority Health and Health Disparities (G12MD007600)
Topics
  • Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
Keywords
REDCap, clinical research data management
MeSH terms
Clinical Trials as Topic, Data Collection, Humans, Medical Informatics, Software, Internet, Biomedical Research

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

A language model drew the claims from the paper on 2026-09-28, under version 3 of the claim definition (prompt extract-v3).

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