Software to Automate Source Data Verification in Clinical Trials

Project Abstract Source data verificationSDVis one of the most expensivelabor intensiveand error ridden steps in monitoring clinical trialsDuring the SDV processhuman monitors manually compare information in two or more databases for completenessconsistencyand adherence to the trial protocolBecause SDV is performed manuallyit incurs high labor costs and is prone to human borne errorsOur overall objective with this PhaseSBIR grant is to develop a prototype software application that can automate the SDV processThis tool would also incorporate a rules based engine to compare information in the database to study specific protocol parametersOur specific aims are as followsdevelop exogenous source data interfacesdevelop exogenous configuration data interfacesdesign and implement an efficient comparison engine capable of detecting protocol rule violations in the records extracted from multiple exogenous data sourcesandperformad hocStudy Simulations and Measure the effectiveness of the Swift SDV system Project Narrative Source data verification in clinical trialsthe manual task of verifying information between a participant s health record and a clinical trial databaseis a costly and error prone processWe are proposing a software tool that will automate source data verification by cross referencing information from the two aforementioned sources in a temporaryde identified databaseThis tool will allow clinical researchers to quickly identify incongruent data and will improve the speedcost efficiencyand accuracy of clinical trial monitoring