Our prototype system designed for clinical data acquisition and recording of studies is a novel electronic data capture (EDC) software for simple and lightweight data capture in clinical research. Existing software tools are either costly or suffer from very limited features. To overcome these shortcomings, we designed an EDC software together with a mobile client. We aimed at making it easy to set-up, modifiable, scalable and thereby facilitating research. We wrote the software in R using a modular approach and implemented existing data standards along with a meta data driven interface and database structure. The prototype is an adaptable open-source software, which can be installed locally or in the cloud without advanced IT-knowledge. A mobile web interface and progressive web app for mobile use and desktop computers is added. We show the software's capability, by demonstrating four clinical studies with over 1600 participants and 679 variables per participant. We delineate a simple deployment approach for a server-installation and indicate further use-cases. The software is available under the MIT open-source license. Conclusively the software is versatile, easily deployable, highly modifiable, and extremely scalable for clinical studies. As an open-source R-software it is accessible, open to community-driven development and improvement in the future.
Biomedical studies rely on methodical data acquisition and processing. EDC software is essential to biomedical research since it greatly facilitates systematic data acquisition and processing enabling meaningful analysis and relevant insights. Furthermore, high-quality data acquisition and handling is the key to reliable research results. Modern EDC software must serve vastly diverse needs of biomedical studies while protecting data integrity and promoting transparent, reproducible, and reliable research. The process of data recording, using the electronic Case Report Form (eCRF) integrated into the EDC software needs to be as easy as possible, facilitating data acquisition both by study personal and by patients when filling out patient related outcome forms. In general, use of an EDC software in contrast to spread sheet solutions improves data quality whilst reducing time consumption. The quality and comprehensiveness of data is ensured by detection of missing fields or inability to complete the submission form, a central aspect of the eCRF. An important feature of EDC software, especially with interventional studies, is the possibility of real data analysis and review, whilst monitoring the study outcome thus being able to interfere whenever a group of patients might be harmed by the intervention studied.
Most current EDC programs are published under proprietary licenses. These include some of the most widely used EDC software in academic research, such as REDCap. Their usage and distribution are subject to fees or specific conditions and their source code is not publicly available. Customizations and deployment of proprietary software is costly and/or bound to strict limitations. When customizations are not easily available to third parties, scientific reproducibility is impaired. Especially, data exchange and compatibility are of major importance in medical research but are often impaired by vendor-specific data architecture.
Many research groups have published innumerous studies using the REDCap software, but a head-to-head analysis against other proprietary software is not available. The most frequent burdens in the application especially involve the setup of the system since advanced computing skills are needed to run in on the local computer which often includes extra local setup fees. Yet another popular eCRF software published under a proprietary license is soscisurvey, which is mostly used for simple online surveys. It is difficult to use when more than one time point is assessed.
Important and frequent limitations of many available EDC systems are restrictions in creating versions of the database in an active study. Modifying the meta data (e.g. adding variables or visits) to a study protocol after an amendment requires archiving the existing database and a complete reset of the database.
Other commonly issues include the lack of auditability and security-concerns of the EDC software owing to many solutions being programmed rather long ago with constantly changing standards.
An important alternative to proprietary programs is open-source software. Its source code is available to the public domain under a variety of open-source licenses. Generally, open-source licenses allow the use, study, adaptation, and distribution of the source code and the software itself to everybody and for any use. Some of the most widely used programming languages, software packages and operating systems such as C#, R, Ubuntu or Android are published under open-source licenses. In the scientific context, open source-software has important advantages: publicly available source code makes open-source software transparent. Adaption and scientific analyses of open-source software are viable and not limited to license constraints. Publicly funded software development stays available to the public. Developer communities can maintain and improve the software as needed. Unfortunately, open-source EDC programs like OpenClinica often suffer from limited features in the open-source branch. Customizations and deployment of these programs require advanced software engineering skills, due to advanced programming languages and complex software architectures. Furthermore, more recent advances such as federated learning or artificial intelligence can't be deployed.
Getting started with a clinical study might require substantial resources and time for customizing and setting up current proprietary and open-source EDC systems. For many small research projects, these resources are not affordable. In consequence, such projects do not use EDC software but rather rely on spreadsheet-programs and paper-based forms for patient questionnaires. This jeopardizes data quality and impairs collaborative multicenter research for small projects or in low-budget settings.
To address these problems, we designed a new prototype for an open-source EDC software and an accompanying mobile client.
