A Combined Patient Registry and Biobank Laboratory Information System for Prospective Multisite Chronic Rheumatic Disease Research Using REDCap

Background/Purpose: As we enter the big data revolution, comprehensive informatics solutions are essential to realising precision medicine for rheumatic and other chronic disease patients, especially for curating high-quality, large-scale and longitudinal biospecimen and linked data collections. In establishing the Australian Arthritis and Autoimmune Biobank Collaborative (A3BC), we sought to develop a low-cost, nation-scale data management system capable of managing our multi-site longitudinal biobank-registry and its complex biobank and data requirements. This included broad life-course data from adults and children across clinical/phenotypic, biological, patient-reported and administrative health data domains, collected to enable holistic multidisciplinary research towards improved outcomes for people living with arthritis and autoimmune conditions.

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 meeting 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 external modules that 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” for non-profit REDCap Consortium members. REDCap is highly configurable and customisable to a variety of biobank and registry needs and can be developed/ maintained by end-users with modest IT skill, time and cost. We created a secure, comprehensive participant-centric biobank-registry database that includes best practice data security measures (incl login for multi-site access using academic and government user credentials), permission-to-contact and dynamic itemised e-consent, a complete chain of custody from consent to biospecimen/data collection to publication, complex longitudinal patient-reported surveys, a fully integrated biobanking workflow, disease-specific case report forms, integration of record-level extracted/ linked participant data, significant form auto-population for streamlined data capture, and native dashboards for operational visualisations. The system has the capacity to enrol participants with a range of diagnoses as well as healthy or at-risk controls (e.g. first degree relatives).

Conclusion: We utilised REDCap to develop an economical, easily-adaptable and sustainable model and recommend it for prospective chronic disease biobanks or biobank-registry projects supporting research into disease prediction, targeted treatments and prevention strategies.