scholarly journals OpenEDC: an open-source, standard-compliant, and mobile electronic data capture system for medical research (Preprint)

10.2196/29176 ◽  
2021 ◽  
Author(s):  
Leonard Greulich ◽  
Stefan Hegselmann ◽  
Martin Dugas
Keyword(s):  
Medical Research ◽  
Open Source ◽  
Data Capture ◽  
Electronic Data Capture ◽  
Electronic Data ◽  
Electronic Data Capture System

scholarly journals Open-source electronic data capture system offered increased accuracy and cost-effectiveness compared with paper methods in Africa

2014 ◽  
Vol 67 (12) ◽  
pp. 1358-1363 ◽  
Author(s):  
David G. Dillon ◽  
Fraser Pirie ◽  
Stephen Rice ◽  
Cristina Pomilla ◽  
Manjinder S. Sandhu ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Open Source ◽  
Data Capture ◽  
Electronic Data Capture ◽  
Electronic Data ◽  
Electronic Data Capture System

OpenEDC: an open-source, standard-compliant, and mobile electronic data capture system for medical research (Preprint)

2021 ◽  
Author(s):  
Leonard Greulich ◽  
Stefan Hegselmann ◽  
Martin Dugas
Keyword(s):  
Data Collection ◽  
Medical Research ◽  
Open Source ◽  
Clinical Data ◽  
Data Exchange ◽  
Data Capture ◽  
Digital Data ◽  
Quality Data ◽  
Electronic Data Capture ◽  
Electronic Data

BACKGROUND Medical research and machine learning for healthcare depend on high-quality data. Electronic data capture (EDC) systems are widely adopted for metadata-driven digital data collection. However, many systems use proprietary and incompatible formats that inhibit clinical data exchange and metadata reuse. In addition, configuration and financial requirements of typical EDC systems frequently prevent small-scale studies to profit from their eminent benefits. OBJECTIVE The goal was to develop and publish an open-source EDC system that addresses the aforementioned issues. We planned applicability of the system in a wide range of research projects. METHODS We conducted a literature-based requirements analysis to identify academic and regulatory demands towards digital data collection. After designing and implementing OpenEDC, we performed a usability evaluation to obtain feedback from users. RESULTS We identified 20 frequently stated requirements towards EDC. According to the ISO/IEC 25010 norm, we categorized the requirements into functional suitability, availability, compatibility, usability, and security. We developed OpenEDC based on the regulatory-compliant Clinical Data Interchange Standards Consortium Operational Data Model standard. Mobile device support enables the collection of patient-reported outcomes. OpenEDC is publicly available and released under the MIT open-source license. CONCLUSIONS Adopting an established standard without modifications supports metadata reuse and clinical data exchange but it limits item layouts. OpenEDC is a standalone web application that can be used without setup or configuration. This should foster compatibility of medical research and open science. OpenEDC is targeted at observational and translational research studies by clinician scientists.

OS 26-03 MOBILE DEVICE BASED ELECTRONIC DATA CAPTURE SYSTEM IN PHARMACEUTICAL CLINICAL TRIAL

2016 ◽  
Vol 34 (Supplement 1) ◽  
pp. e247
Author(s):  
Jing Zhang ◽  
Lei Sun ◽  
Yu Liu ◽  
Hongyi Wang ◽  
Ningling Sun ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Mobile Device ◽  
Data Capture ◽  
Electronic Data Capture ◽  
Electronic Data ◽  
Electronic Data Capture System

Possible Combinations of Electronic Data Capture and Randomization Systems

2014 ◽  
Vol 53 (03) ◽  
pp. 202-207 ◽  
Author(s):  
M. Haag ◽  
L. R. Pilz ◽  
D. Schrimpf
Keyword(s):  
Open Source ◽  
Data Storage ◽  
Data Entry ◽  
Data Capture ◽  
Electronic Systems ◽  
Electronic Data Capture ◽  
Electronic Data ◽  
Training Costs ◽  
Pros And Cons ◽  
General Data

SummaryBackground: Clinical trials (CT) are in a wider sense experiments to prove and establish clinical benefit of treatments. Nowadays electronic data capture systems (EDCS) are used more often bringing a better data management and higher data quality into clinical practice. Also electronic systems for the randomization are used to assign the patients to the treatments.Objectives: If the mentioned randomization system (RS) and EDCS are used, possibly identical data are collected in both, especially by stratified randomization. This separated data storage may lead to data inconsistency and in general data samples have to be aligned. The article discusses solutions to combine RS and EDCS. In detail one approach is realized and introduced.Methods: Different possible settings of combination of EDCS and RS are determined and the pros and cons for each solution are worked out. For the combination of two independent applications the necessary interfaces for the communication are defined. Thereby, existing standards are considered. An example realization is implemented with the help of open-source applications and state-of-the-art software development procedures.Results: Three possibilities of separate usage or combination of EDCS and RS are pre -sented and assessed: i) the complete independent usage of both systems; ii) realization of one system with both functions; and iii) two separate systems, which communicate via defined interfaces. In addition a realization of our preferred approach, the combination of both systems, is introduced using the open source tools RANDI2 and Open-Clinica.Conclusion: The advantage of a flexible independent development of EDCS and RS is shown based on the fact that these tool are very different featured. In our opinion the combination of both systems via defined interfaces fulfills the requirements of randomization and electronic data capture and is feasible in practice. In addition, the use of such a setting can reduce the training costs and the error-prone duplicated data entry.

Selecting an Electronic Data Capture System

2016 ◽  
Vol 3 (3) ◽  
pp. 236-241 ◽  
Author(s):  
Cameron B. Alavi ◽  
John D. Massman
Keyword(s):  
Data Capture ◽  
Electronic Data Capture ◽  
Electronic Data ◽  
Electronic Data Capture System

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

2007 ◽  
Vol 23 (8) ◽  
pp. 1967-1979 ◽  
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

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

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

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

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.

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