Conducting clinical trials more efficiently and ultimately more successfully would significantly improve patient care. However, the fragmentation of the relevant data required to implement improvements in translation studies is a significant obstacle.
While some bioinformatics tools have attempted to address this problem, they have often lacked the ability to assess the effectiveness of translational science. Researchers at the South Carolina Medical University of South Carolina Clinical & Translational Research Institute (MUSC) have developed a novel bioinformatic tool called RINS, the Research Integrated Network of Systems, that can be used to assess whether improvements in the clinical trial process make a difference. Their results, published in the Journal of the American Medical Informatics Associationshowed that RINS can integrate clinical trial data across disparate systems and provide metrics on the efficiency and effectiveness of MUSC’s clinical trials.
“You could call it metadata – it’s data about how we produce data in studies or how we get studies up and running,” said Dr. Leslie A. Lenert, Chief Research Information Officer at MUSC and Director of the Biomedicine Computer Center. “These were all in a different place, in a different format, and used numbers for which there was no agreed definition. But we have summarized everything at a glance to get a comprehensive overview of the scientific processes. And we’ve never had that because the data lived in different systems. “
In order to make informed decisions about how best to improve and streamline translational research practices, detailed data is required. In order to collect this data, the institutes need meaningful assessment tools. To this end, MUSC developed and deployed the Research Transaction Management System SPARCRequest, which offers a powerful tool that allows researchers to determine budgets for grant applications, manage the regulatory process, recruit various study participants and conduct clinical studies. While SPARCRequest was instrumental in streamlining clinical research, it wasn’t originally set up to track metrics across systems. Lenert’s planned new, decentralized RINS research data market took SPARCRequest’s research metrics tracking activities to the next level and enabled cross-disciplinary tracking and communication of groups.
“It’s a simple concept, but difficult to implement,” said Lenert, who also acts as an assistant for data science and computer science. “Nobody had the opportunity to bring these different systems together to tell us how long it would take for an institutional review body [IRB] Protocol to be approved, or whether that funding led to this outcome – these are difficult things to do. “
In order to store and access the data in the warehouse, the RINS team needed a way to clearly identify each study and to link the different systems together. To solve the problem of identifying each study, the team created a Research Master Identifier (RMID).
Using RMIDs and application programming interfaces, RINS integrates SPARCRequest with other electronic databases, including MUSC’s electronic medical record. electronic IRB; and systems for grant management, expense tracking, and clinical trial management. RINS was flexible enough to accommodate new programs while maintaining historical data.
Edited by Gary Cramer