Mobile Device–Based Electronic Data Capture System Used in a Clinical Randomized Controlled Trial: Advantages and Challenges

Abstract Background Randomized controlled trials (RCT) are considered the ideal design for evaluating the efficacy of interventions. However, conducting a successful RCT has technological and logistical challenges. Defects in randomization processes (e.g., allocation sequence concealment) and flawed masking could bias an RCT’s findings. Moreover, investigators need to address other logistics common to all study designs, such as study invitations, eligibility screening, consenting procedure, and data confidentiality protocols. Research Electronic Data Capture (REDCap) is a secure, browser-based web application widely used by researchers for survey data collection. REDCap offers unique features that can be used to conduct rigorous RCTs. Methods In September and November 2020, we conducted a parallel group RCT among Indiana University Bloomington (IUB) undergraduate students to understand if receiving the results of a SARS-CoV-2 antibody test changed the students’ self-reported protective behavior against coronavirus disease 2019 (COVID-19). In the current report, we discuss how we used REDCap to conduct the different components of this RCT. We further share our REDCap project XML file and instructional videos that investigators can use when designing and conducting their RCTs. Results We reported on the different features that REDCap offers to complete various parts of a large RCT, including sending study invitations and recruitment, eligibility screening, consenting procedures, lab visit appointment and reminders, data collection and confidentiality, randomization, blinding of treatment arm assignment, returning test results, and follow-up surveys. Conclusions REDCap offers powerful tools for longitudinal data collection and conduct of rigorous and successful RCTs. Investigators can make use of this electronic data capturing system to successfully complete their RCTs. Trial registration The RCT was prospectively (before completing data collection) registered at ClinicalTrials.gov; registration number: NCT04620798, date of registration: November 9, 2020.

Download Full-text

Use of Research Electronic Data Capture (REDCap) in different phases of a COVID-19 randomized controlled trial: A practical example

10.21203/rs.3.rs-382860/v1 ◽

2021 ◽

Author(s):

Sina Kianersi ◽

Maya Luetke ◽

Christina Ludema ◽

Alexander Valenzuela ◽

Molly Rosenberg

Keyword(s):

Data Collection ◽

Undergraduate Students ◽

Web Application ◽

Controlled Trial ◽

Data Capture ◽

Electronic Data Capture ◽

Electronic Data ◽

Instructional Videos ◽

Randomized Controlled ◽

Longitudinal Data Collection

Abstract Background: Randomized controlled trials (RCT) are considered the ideal design for evaluating the efficacy of interventions. However, conducting a successful RCT has technological and logistical challenges. Defects in randomization processes (e.g., allocation sequence concealment) and flawed masking could bias an RCT’s findings. Moreover, investigators need to address other logistics common to all study designs, such as study invitations, eligibility screening, consenting procedure, and data confidentiality protocols. Research Electronic Data Capture (REDCap) is a secure, browser-based web application widely used by researchers for survey data collection. REDCap offers unique features that can be used to conduct rigorous RCTs.Methods: In September and November 2020, we conducted a parallel group RCT among Indiana University Bloomington (IUB) undergraduate students regarding their seropositivity for Coronavirus Disease 2019 (COVID-19) antibodies. In the current report, we discuss how we used REDCap to conduct the different components of this RCT. We further share XML REDCap files and instructional videos that investigators can use when designing and conducting their RCTs.Results and Conclusions: We report on the different features that REDCap offers to complete various parts of a large RCT, including sending study invitations and recruitment, eligibility screening, consenting procedures, lab visit appointment and reminders, data collection and confidentiality, randomization, blinding of treatment arm assignment, returning test results, and follow-up surveys. REDCap offers powerful tools for longitudinal data collection and conduct of rigorous and successful RCTs.

Download Full-text

Discussion on developing a data management plan and its key factors in clinical study based on electronic data capture system

Journal of Chinese Integrative Medicine ◽

10.3736/jcim20120802 ◽

2012 ◽

pp. 841-846 ◽

Cited By ~ 1

Author(s):

QN Li

Keyword(s):

Clinical Study ◽

Data Management ◽

Management Plan ◽

Data Capture ◽

Electronic Data Capture ◽

Key Factors ◽

Electronic Data ◽

Electronic Data Capture System

Download Full-text

FACILITATING REAL WORLD CARDIOLOGY STUDIES THROUGH VALIDATION OF THE APOLLO ELECTRONIC DATA CAPTURE SYSTEM IN A COMMUNITY CARDIOLOGY ELECTRONIC HEALTH RECORD DATABASE

Canadian Journal of Cardiology ◽

10.1016/j.cjca.2021.07.125 ◽

2021 ◽

Vol 37 (10) ◽

pp. S61

Author(s):

M Heffernan ◽

M Birch ◽

T Bandukwala ◽

K Katebian

Keyword(s):

Electronic Health Record ◽

Real World ◽

Data Capture ◽

Health Record ◽

Electronic Data Capture ◽

Electronic Data ◽

Electronic Data Capture System ◽

Electronic Health

Download Full-text

Selecting an Electronic Data Capture System

Urology Practice ◽

10.1016/j.urpr.2015.06.007 ◽

2016 ◽

Vol 3 (3) ◽

pp. 236-241 ◽

Cited By ~ 1

Author(s):

Cameron B. Alavi ◽

John D. Massman

Keyword(s):

Data Capture ◽

Electronic Data Capture ◽

Electronic Data ◽

Electronic Data Capture System

Download Full-text

A multicenter, randomized, open study to evaluate the impact of an electronic data capture system on the care of patients with rheumatoid arthritis

Current Medical Research and Opinion ◽

10.1185/030079907x210624 ◽

2007 ◽

Vol 23 (8) ◽

pp. 1967-1979 ◽

Cited By ~ 8

Author(s):

Joseph Huffstutter ◽

W. David Craig ◽

Gregory Schimizzi ◽

John Harshbarger ◽

Jeffrey Lisse ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Open Study ◽

Data Capture ◽

Electronic Data Capture ◽

Electronic Data ◽

Electronic Data Capture System ◽

The Impact

Download Full-text

Application of Electronic Data Capture System to a Clinical Study in Japan

Rinsho yakuri/Japanese Journal of Clinical Pharmacology and Therapeutics ◽

10.3999/jscpt.34.4_193 ◽

2003 ◽

Vol 34 (4) ◽

pp. 193-198

Author(s):

Akiyoshi KAWAI ◽

Tomoaki KUWANO ◽

Hisao NAKAJIMA ◽

Kiyofumi MIZUNO ◽

Hiroyuki NISHIMOTO ◽

...

Keyword(s):

Clinical Study ◽

Data Capture ◽

Electronic Data Capture ◽

Electronic Data ◽

Electronic Data Capture System

Download Full-text

Assessment of the Chad guinea worm surveillance information system: A pivotal foundation for eradication

PLoS Neglected Tropical Diseases ◽

10.1371/journal.pntd.0009675 ◽

2021 ◽

Vol 15 (8) ◽

pp. e0009675

Author(s):

Saugat Karki ◽

Adam Weiss ◽

Jina Dcruz ◽

Dorothy Hunt ◽

Brandon Haigood ◽

...

Keyword(s):

Information System ◽

Data Management ◽

Data Storage ◽

Management Practices ◽

Information Value ◽

Data Capture ◽

Electronic Data Capture ◽

Electronic Data ◽

Guinea Worm ◽

Electronic Data Capture System

Background In the absence of a vaccine or pharmacological treatment, prevention and control of Guinea worm disease is dependent on timely identification and containment of cases to interrupt transmission. The Chad Guinea Worm Eradication Program (CGWEP) surveillance system detects and monitors Guinea worm disease in both humans and animals. Although Guinea worm cases in humans has declined, the discovery of canine infections in dogs in Chad has posed a significant challenge to eradication efforts. A foundational information system that supports the surveillance activities with modern data management practices is needed to support continued program efficacy. Methods We sought to assess the current CGWEP surveillance and information system to identify gaps and redundancies and propose system improvements. We reviewed documentation, consulted with subject matter experts and stakeholders, inventoried datasets to map data elements and information flow, and mapped data management processes. We used the Information Value Cycle (IVC) and Data-Information System-Context (DISC) frameworks to help understand the information generated and identify gaps. Results Findings from this study identified areas for improvement, including the need for consolidation of forms that capture the same demographic variables, which could be accomplished with an electronic data capture system. Further, the mental models (conceptual frameworks) IVC and DISC highlighted the need for more detailed, standardized workflows specifically related to information management. Conclusions Based on these findings, we proposed a four-phased roadmap for centralizing data systems and transitioning to an electronic data capture system. These included: development of a data governance plan, transition to electronic data entry and centralized data storage, transition to a relational database, and cloud-based integration. The method and outcome of this assessment could be used by other neglected tropical disease programs looking to transition to modern electronic data capture systems.

Download Full-text