Research Integrated Network of Systems (RINS): a virtual data warehouse for the acceleration of translational research

• Published in: Journal of the American Medical Informatics Association : JAMIA Vol. 28; no. 7; pp. 1440 - 1450
• Main Authors: He, Wenjun, Kirchoff, Katie G, Sampson, Royce R, McGhee, Kimberly K, Cates, Andrew M, Obeid, Jihad S, Lenert, Leslie A
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 14.07.2021
• Subjects: Acceleration; Data Warehousing; Electronic Health Records; Humans; Research and Applications; Systems Integration; Translational Research, Biomedical; learning health system; clinical data warehouse; application programming interfaces; health information interoperability
• ISSN: 1527-974X; 1067-5027; 1527-974X
• DOI: 10.1093/jamia/ocab023

Abstract Objective Integrated, real-time data are crucial to evaluate translational efforts to accelerate innovation into care. Too often, however, needed data are fragmented in disparate systems. The South Carolina Clinical & Translational Research Institute at the Medical University of South Carolina (MUSC) developed and implemented a universal study identifier—the Research Master Identifier (RMID)—for tracking research studies across disparate systems and a data warehouse-inspired model—the Research Integrated Network of Systems (RINS)—for integrating data from those systems. Materials and Methods In 2017, MUSC began requiring the use of RMIDs in informatics systems that support human subject studies. We developed a web-based tool to create RMIDs and application programming interfaces to synchronize research records and visualize linkages to protocols across systems. Selected data from these disparate systems were extracted and merged nightly into an enterprise data mart, and performance dashboards were created to monitor key translational processes. Results Within 4 years, 5513 RMIDs were created. Among these were 726 (13%) bridged systems needed to evaluate research study performance, and 982 (18%) linked to the electronic health records, enabling patient-level reporting. Discussion Barriers posed by data fragmentation to assessment of program impact have largely been eliminated at MUSC through the requirement for an RMID, its distribution via RINS to disparate systems, and mapping of system-level data to a single integrated data mart. Conclusion By applying data warehousing principles to federate data at the “study” level, the RINS project reduced data fragmentation and promoted research systems integration.