scholarly journals Innovating to enhance clinical data management using non-commercial and open source solutions across a multi-center network supporting inpatient pediatric care and research in Kenya

2015 ◽  
Vol 23 (1) ◽  
pp. 184-192 ◽  
Author(s):  
Timothy Tuti ◽  
Michael Bitok ◽  
Chris Paton ◽  
Boniface Makone ◽  
Lucas Malla ◽  
...  
Keyword(s):  
Data Quality ◽  
Data Management ◽  
Open Source ◽  
Clinical Data ◽  
Data Capture ◽  
Quality Data ◽  
Pediatric Care ◽  
Electronic Data Capture ◽  
Electronic Data ◽  
Report Generation

Abstract Objective To share approaches and innovations adopted to deliver a relatively inexpensive clinical data management (CDM) framework within a low-income setting that aims to deliver quality pediatric data useful for supporting research, strengthening the information culture and informing improvement efforts in local clinical practice. Materials and methods The authors implemented a CDM framework to support a Clinical Information Network (CIN) using Research Electronic Data Capture (REDCap), a noncommercial software solution designed for rapid development and deployment of electronic data capture tools. It was used for collection of standardized data from case records of multiple hospitals’ pediatric wards. R, an open-source statistical language, was used for data quality enhancement, analysis, and report generation for the hospitals. Results In the first year of CIN, the authors have developed innovative solutions to support the implementation of a secure, rapid pediatric data collection system spanning 14 hospital sites with stringent data quality checks. Data have been collated on over 37 000 admission episodes, with considerable improvement in clinical documentation of admissions observed. Using meta-programming techniques in R, coupled with branching logic, randomization, data lookup, and Application Programming Interface (API) features offered by REDCap, CDM tasks were configured and automated to ensure quality data was delivered for clinical improvement and research use. Conclusion A low-cost clinically focused but geographically dispersed quality CDM (Clinical Data Management) in a long-term, multi-site, and real world context can be achieved and sustained and challenges can be overcome through thoughtful design and implementation of open-source tools for handling data and supporting research.

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.

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.

Validation of the Oral Survey-B System for Electronic Data Capture in National Oral Health Surveys

2016 ◽  
Vol 50 (3) ◽  
pp. 288-294 ◽  
Author(s):  
J.C. Carvalho ◽  
D. Declerck ◽  
E. De Vos ◽  
J. Kellen ◽  
J.P. Van Nieuwenhuysen ◽  
...  
Keyword(s):  
Oral Health ◽  
Clinical Data ◽  
Health Surveys ◽  
Interrater Reliability ◽  
Data Capture ◽  
Electronic Data Capture ◽  
Validation Process ◽  
Electronic Data ◽  
Kappa Value ◽  
Time Savings

The aims of the present study were to incorporate and to validate the electronic capture of participant-related outcomes into the Oral Survey-B System, which was originally developed for the electronic capture of clinical data. The validation process compared the performances of electronic and handwritten data captures. The hypothesis of noninferiority would be established if participants performed electronic data capture of the questionnaire survey with an effectiveness of at least 95% of that of handwritten data capture. In this multicenter, randomized, one-period crossover study design, participants (n = 261) were allocated to start with either electronic or handwritten data capture. The incorporation of the electronic self-completed questionnaire into the Oral Survey-B System was successful. The validation of the electronic questionnaire was performed by participants aged from 18 to 75 years. The interrater reliability of participants performing electronic and handwritten data capture of nonclinical assessments per questionnaire and per entry showed a kappa value of 0.72 (95% CI: 0.53-0.94). The noninferiority of electronic data capture in relation to that of the handwritten data capture and transfer was shown (p < 0.0001; 95% CI: 1.47-2.99). In conclusion, the electronic capture of participant-related outcomes with the Oral Survey-B System, originally designed for capture of clinical data, was validated. The electronic data capture was accurate and limited the number of errors. The participants were able to perform electronic data capture effectively, supporting its implementation in further National Oral Health Surveys. With the consideration of participant preference and time savings, this could lead to the implementation of electronic data capture worldwide in National Oral Health Surveys.

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.

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

scholarly journals Electronic Data Capture for Registries and Clinical Trials in Orthopaedic Surgery: Open Source versus Commercial Systems

2010 ◽  
Vol 468 (10) ◽  
pp. 2664-2671 ◽  
Author(s):  
Jatin Shah ◽  
Dimple Rajgor ◽  
Shreyasee Pradhan ◽  
Mariana McCready ◽  
Amrapali Zaveri ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Open Source ◽  
Orthopaedic Surgery ◽  
Data Capture ◽  
Electronic Data Capture ◽  
Electronic Data
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