As more and more sponsors elect to collect vendor data and hire companies to perform vendor tasks on trials, CROs and the like must train and adapt their needs to ensure the data is as clean as possible. This includes introduction of novel collection pathways that must be reconciled. These novel pathways include wearable devices, Artificial Intelligence (AI) and mobile technology. As the use of technological developments have changed the collection of data, we as reviewers must adapt our methods to be more efficient and decide the most cost-effective ways for reconciliation. This session will explore the types of data and an efficient way, the Puzzle Method, for reconciling vendor data, as well as novel pathways for data collection.
Learning Objective : Define the most common data points to be reconciled between clinical databases and external vendor records; Describe how to apply the Puzzle Method to any vendor reconciliation task on a clinical trial where external vendor reconciliation is required; Identify novel external data sources and discuss the necessity of reconciliation and the key variables to reconcile novel data against the clinical database.
Streamlining the Process of Vendor Reconciliation: The Puzzle Method
Kelley Chrisman, MBA, MPH
Lead Data Manager
PRA Health Sciences, United States
Reconciling Novel External Data Sources (Wearable Devices and Mobile Technology) with Clinical Databases
Associate Director, Data Management
Otsuka Pharmaceutical Development & Commercialization, Inc, United States