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 ◽  
...  

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.

2016 ◽  
Vol 34 (Supplement 1) ◽  
pp. e247
Author(s):  
Jing Zhang ◽  
Lei Sun ◽  
Yu Liu ◽  
Hongyi Wang ◽  
Ningling Sun ◽  
...  

2014 ◽  
Vol 53 (03) ◽  
pp. 202-207 ◽  
Author(s):  
M. Haag ◽  
L. R. Pilz ◽  
D. Schrimpf

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.


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

2007 ◽  
Vol 23 (8) ◽  
pp. 1967-1979 ◽  
Author(s):  
Joseph Huffstutter ◽  
W. David Craig ◽  
Gregory Schimizzi ◽  
John Harshbarger ◽  
Jeffrey Lisse ◽  
...  

Author(s):  
Akiyoshi KAWAI ◽  
Tomoaki KUWANO ◽  
Hisao NAKAJIMA ◽  
Kiyofumi MIZUNO ◽  
Hiroyuki NISHIMOTO ◽  
...  

10.2196/18580 ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. e18580 ◽  
Author(s):  
Caleb J Ruth ◽  
Samantha Lee Huey ◽  
Jesse T Krisher ◽  
Amy Fothergill ◽  
Bryan M Gannon ◽  
...  

Background When we were unable to identify an electronic data capture (EDC) package that supported our requirements for clinical research in resource-limited regions, we set out to build our own reusable EDC framework. We needed to capture data when offline, synchronize data on demand, and enforce strict eligibility requirements and complex longitudinal protocols. Based on previous experience, the geographical areas in which we conduct our research often have unreliable, slow internet access that would make web-based EDC platforms impractical. We were unwilling to fall back on paper-based data capture as we wanted other benefits of EDC. Therefore, we decided to build our own reusable software platform. In this paper, we describe our customizable EDC framework and highlight how we have used it in our ongoing surveillance programs, clinic-based cross-sectional studies, and randomized controlled trials (RCTs) in various settings in India and Ecuador. Objective This paper describes the creation of a mobile framework to support complex clinical research protocols in a variety of settings including clinical, surveillance, and RCTs. Methods We developed ConnEDCt, a mobile EDC framework for iOS devices and personal computers, using Claris FileMaker software for electronic data capture and data storage. Results ConnEDCt was tested in the field in our clinical, surveillance, and clinical trial research contexts in India and Ecuador and continuously refined for ease of use and optimization, including specific user roles; simultaneous synchronization across multiple locations; complex randomization schemes and informed consent processes; and collecting diverse types of data (laboratory, growth measurements, sociodemographic, health history, dietary recall and feeding practices, environmental exposures, and biological specimen collection). Conclusions ConnEDCt is customizable, with regulatory-compliant security, data synchronization, and other useful features for data collection in a variety of settings and study designs. Furthermore, ConnEDCt is user friendly and lowers the risks for errors in data entry because of real time error checking and protocol enforcement.


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