2017 CDISC Europe InterchangeApril 24 - 28, 2017 - London, England
Join Biorasi at the 2017 CDISC Europe Interchange
April 24 – 28, 2017
Connect with Biorasi at the 2017 CDISC Europe Interchange in London, England. Our team will be attending the event held at the Grange Tower Bridge Hotel and would love the opportunity to meet with partners, sponsors, and friends to discuss today’s data standards in clinical research.
Don’t miss the presentation from Biorasi’s own VP of Data Sciences, Jon Roth, MBA, at the conference! Here is sneak preview of what to expect on “Big Data’ Analytic Methods to Simplify Risk-Based-Monitoring and Fraud Detection in Clinical Trials”:
Risk based methods have been employed for a number of years in clinical studies as a way to improve the quality of clinical data, the accuracy of conclusions and to reduce the significant costs of clinical study oversight. Risk Based Monitoring (RBM) techniques derive their advantage through powerful statistical analytics that can guide monitor focus and activity over the life of the study to identify and verify key data and to correct site misunderstandings and issues before they evolve into serious problems. Although rarely implemented, the same statistical analytics can be used to identify fraudulent sites and patients participating in a study – an important topic that is now gaining critical visibility.
Traditional methods for implementing RBM stress the need for early assessment, planning and development work to ensure that risks are aligned with study needs. Conversely, a Big Data approach de-prioritizes much of this early work in favor of allowing the data itself to guide the analysis and risk profile for the study. This brings a number of advantages including a faster implementation time and a lower dependence on pre-identifying and programming for the key risk elements of the study. As an added benefit, common Fraud Detection analyses can be performed at the same time to highlight suspect sites or patients that should call for immediate monitoring attention.
This presentation shows how clinical data automatically flows from EDC platform into a well-known clinical analytics system for risk assessment, data visualization and fraud detection. Genuine examples are given from multi-venue studies which indicate a high risk of non-compliance and a significant probability of fraud at several sites. All of this is done without the need for extensive custom programming or for transforming data into a proprietary data mart or warehouse.