REDCap: A Tool for the Electronic Capture of Research Data

Wright, Andrea

doi:10.1080/15424065.2016.1259026

Cited by 64 publications

(52 citation statements)

References 5 publications

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“…The study will use a password-protected offline Research electronic data capture (REDCap) database (Vanderbilt University, Nashville, TN, USA) [97] to enter data and store entered data in an encrypted drive. The Principal Investigator will keep the source data in a locked cabinet at the study's central office.…”

Section: Data Collection and Managementmentioning

confidence: 99%

Electronic pillbox-enabled self-administered therapy versus standard directly observed therapy for tuberculosis medication adherence and treatment outcomes in Ethiopia (SELFTB): protocol for a multicenter randomized controlled trial

Manyazewal

Woldeamanuel

Holland

et al. 2020

Trials

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Background: To address the multifaceted challenges associated with tuberculosis (TB) in-person directly observed therapy (DOT), the World Health Organization recently recommended that countries maximize the use of digital adherence technologies. Sub-Saharan Africa needs to investigate the effectiveness of such technologies in local contexts and proactively contribute to global decisions around patient-centered TB care. This study aims to evaluate the effectiveness of pillbox-enabled self-administered therapy (SAT) compared to standard DOT on adherence to TB medication and treatment outcomes in Ethiopia. It also aims to assess the usability, acceptability, and cost-effectiveness of the intervention from the patient and provider perspectives.

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Section: Data Collection and Managementmentioning

confidence: 99%

Electronic pillbox-enabled self-administered therapy versus standard directly observed therapy for tuberculosis medication adherence and treatment outcomes in Ethiopia (SELFTB): protocol for a multicenter randomized controlled trial

Manyazewal

Woldeamanuel

Holland

et al. 2020

Trials

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“…Block randomization of participants to the two treatment conditions will be completed using the Research Electronic Data Capture (REDCap) Randomization Model [24][25][26]. A randomized allocation table will be created in Microsoft Excel stratifying by gender (male and female), disease severity as determined using the Modified Hoehn & Yahr scoring (<= 2 and > =2.5) [21], and site (BU and WU).…”

Section: Randomization and Blindingmentioning

confidence: 99%

“…To promote data quality, we will be using a REDCap database hosted at Boston University. REDCap is a secure, web-based software platform designed to support data capture for research studies [24][25][26]. A data entry assistant initially will enter data collected on paper into REDCap and each questionnaire will be marked as "unverified".…”

Section: Data Collection and Managementmentioning

confidence: 99%

Design of the WHIP-PD study: a phase II, twelve-month, dual-site, randomized controlled trial evaluating the effects of a cognitive-behavioral approach for promoting enhanced walking activity using mobile health technology in people with Parkinson-disease

et al. 2020

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Background: Parkinson disease (PD) is a debilitating and chronic neurodegenerative disease resulting in ambulation difficulties. Natural walking activity often declines early in disease progression despite the relative stability of motor impairments. In this study, we propose a paradigm shift with a "connected behavioral approach" that targets real-world walking using cognitive-behavioral training and mobile health (mHealth) technology.

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“…REDCap is an electronic data capture software that allows the easy building of research instruments while providing collaboration capabilities, metadata workflow, security, auditing, and export to common statistical packages. Medical librarians have used REDCap for both research data capture as well as operational databases [27]. These examples are more than just platforms, being fully-fledged architectures that can be installed in more than one site.…”

Section: Summary Of the Studiesmentioning

confidence: 99%

“…The objective of this systematic review was to identify projects and software solutions that promote patient electronic health data discovery, as enablers for data reuse and advancement of biomedical and translational research.We have identified 20 such platforms [16,17,18,19,20,21,22,23,24,3,7,25,26,27,28,29,30,31,32,33,34], following a semi-automatic search strategy that we present in the following section. We are interested in understanding how these systems address interoperability, how they impact clinical research and ultimately what the outcomes are in terms of scientific results and contributions to better general healthcare.…”

Section: Introductionmentioning

confidence: 99%

Patient data discovery platforms as enablers of biomedical and translational research: A systematic review

Trifan

Oliveira

2019

Journal of Biomedical Informatics

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Background The global shift from paper health records to electronic ones has led to an impressive growth of biomedical digital data along the past two decades. Exploring and extracting knowledge from these data has the potential to enhance translational research and lead to positive outcomes for the population's health and healthcare. Objective The aim of this study was to conduct a systematic review to identify software platforms that enable discovery, secondary use and interoperability of biomedical data. Additionally, we aim evaluating the identified solutions in terms of clinical interest and main healthcare-related outcomes. Methods A systematic search of the scientific literature published and indexed in Pubmed between January 2014 and September 2018 was performed. Inclusion criteria were as follows: relevance for the topic of biomedical data discovery, English language, and free full text. To increase the recall, we developed a semi-automatic and incremental methodology to retrieve articles that cite one or more of the previous set. Results A total number of 500 candidate papers were retrieved through this methodology. Of these, 85 were eligible for abstract assessment. Finally, 37 studies qualified for a full-text review, and 20 provided enough information for the study objectives. Conclusions This study revealed that biomedical discovery platforms are both a current necessity and a significantly innovative agent in the area of healthcare. The outcomes that were identified, in terms of scientific publica

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REDCap: A Tool for the Electronic Capture of Research Data

Cited by 64 publications

References 5 publications

Electronic pillbox-enabled self-administered therapy versus standard directly observed therapy for tuberculosis medication adherence and treatment outcomes in Ethiopia (SELFTB): protocol for a multicenter randomized controlled trial

Electronic pillbox-enabled self-administered therapy versus standard directly observed therapy for tuberculosis medication adherence and treatment outcomes in Ethiopia (SELFTB): protocol for a multicenter randomized controlled trial

Design of the WHIP-PD study: a phase II, twelve-month, dual-site, randomized controlled trial evaluating the effects of a cognitive-behavioral approach for promoting enhanced walking activity using mobile health technology in people with Parkinson-disease

Patient data discovery platforms as enablers of biomedical and translational research: A systematic review

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