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How To Best Manage Diverse Protocol And Investigator Needs?


Maximize Resource Allocation

Increase Competiveness

Best Leverage Investigators

 
 

Tiered Approach to Electronic Data Capture (EDC)

Study (e.g., design requirements, significance, safety risk, available resources) and investigator (e.g., resident, seasoned investigator) characteristics vary considerably from one study to the next. In addition, rapidly changing information technology and the increasingly competitive funding landscape demand that institutions remain flexible, leverage research informatics in a cost-effective manner, attract the best investigators, and maximize investigator productivity. A tiered approach to EDC offers a direct and compelling response to these challenges.

 

Three Tiers

Tier 1 (no license, limited support and functionality [e.g., REDCap]) and Tier 3 (e.g., costly license, flexible, high FTE overhead [e.g., Inform]) applications are used for the low and high-end range of study characteristics (e.g., importance-level, safety risk, design requirements) and investigator characteristics / preferences (e.g., student vs. senior investigator, support, importance of research career). Tier 2 (i.e., StudyTRAX) combines a cost-effective solution (i.e., easily scales, flexible licensing, top notch support) that dramatically increases investigator productivity. Indeed, as a group within an academic institution, investigators are the most highly paid, highly trained, and most influential of an institution’s reputation.

 

Tier 2 – Integrating Academic Output

Academic output (e.g., manuscripts, book chapters, posters, etc.) is a common, well recognized and accepted metric of investigator productivity. Despite this clear end-result aim of academic research, none of the available EDC systems are organized around the publication of results or offer tools specifically designed to capture the manuscript generation process. Indeed, StudyTRAX is the only EDC system to completely integrate study management (e.g., create forms, run a study, collect data) with the process of generating all types of academic output (e.g., grants, manuscripts, presentations, book chapters, posters), thereby dramatically improving investigator productivity.