An Open-Source, Standard-Compliant, and Mobile Electronic Data Capture System for Medical Research (OpenEDC): Design and Evaluation Study

Abstract

Background Medical research and machine learning for health care depend on high-quality data. Electronic data capture (EDC) systems have been 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, the configuration and financial requirements of typical EDC systems frequently prevent small-scale studies from benefiting from their inherent advantages. Objective The aim of this study is to develop and publish an open-source EDC system that addresses these issues. We aim to plan a system that is applicable to a wide range of research projects. Methods We conducted a literature-based requirements analysis to identify the academic and regulatory demands for 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 for EDC. According to the International Organization for Standardization/International Electrotechnical Commission (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 (CDISC ODM) 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 stand-alone web app that can be used without a setup or configuration. This should foster compatibility between medical research and open science. OpenEDC is targeted at observational and translational research studies by clinicians.

Portal of Medical Data Models: Application in Federated Data Capture

“…For a proof of concept, MDM is now equipped with a REST interface. As a first consumer application of the interface we enhanced the electronic data capture (EDC) software openEDC [5] with a REST client interface. By entering the MDM identification number of a data model in openEDC, the corresponding form is automatically download via REST and made available as CRF.…”

Diagnose- und Aufnahmezentrum

“…Aktuelle KIS bieten größtenteils noch nicht die in anderen Kontexten gewohnte Benutzerfreundlichkeit, Flexibilität und den Funktionsumfang, um eine auch longitudinale Datenerfassung innerhalb einer Systemumgebung zu ermöglichen. Zwar bieten zahlreiche kommerzielle und nichtkommerzielle Anbieter moderne Electronic-Data-Capture-Systeme mit teils beeindruckendem Funktionsumfang an, deren wechselseitige Integration in die jeweilige KIS-Umgebung kann derzeit allerdings nicht realisiert werden [ 3 , 6 ]. Erfreulicherweise wurde mit dem KHZG ein Impuls gesetzt, den Funktionsumfang der KIS deutlich zu erweitern, um eine integrierte und benutzerfreundliche Datenerfassung für Patienten und weitere Beteiligte künftig zu ermöglichen.…”