A Versatile, Secure and Sustainable All-In-One Biobank-Registry Data Solution: The A3BC REDCap Model

Abstract

Introduction: A key element in the big data revolution is large-scale biobanking and the associated development of high-quality data collections and supporting informatics solutions. As such, in establishing the Australian Arthritis and Autoimmune Biobank Collaborative (A3BC), we sought to establish a low-cost, nation-scale data management system capable of managing a multi-site biobank-registry with complex longitudinal sample and data requirements. Materials and Methods: We assessed several international commercial and non-profit software platforms using standardised system requirement criteria and follow-up interviews. Vendor compliance scoring was prioritised to meet our project-critical requirements. Consumer / end-user co-design was integral to refining our system requirements for optimised adoption. Customisation of the selected software solution was performed to optimise field auto-population between participant timepoints and forms, using modules that are transferable and do not impact core code. Institutional and independent testing was used to ensure data security. Results: We selected the widely used research web application Research Electronic Data Capture (REDCap) which is “free” (under non-profit license agreement terms), highly configurable and customisable to a variety of biobank and registry needs, and can be developed/ maintained by biobank users with modest IT skill, time and cost. We created a secure, comprehensive participant-centric biobank-registry database that includes: (a) best practice data security measures (incl. multi-site access login using institutional user credentials), (b) permission-to-contact and dynamic itemised e-consent, (c) a complete chain of custody from consent to longitudinal biospecimen-data collection to publication, (d) complex longitudinal patient-reported surveys, (e) integration of record-level extracted/ linked participant data, (f) significant form auto-population for streamlined data capture, and (g) native dashboards for operational visualisations. Conclusion: We recommend the versatile, reusable and sustainable informatics model we have developed in REDCap for prospective chronic disease biobanks or registry-biobanks (of local to national complexity) supporting holistic research into disease prediction, precision medicine and prevention strategies.