Investigative sites are becoming saturated and overburdened, asked to tap into their investigator and patient resources for more studies (in addition to their already busy clinical and patient care workload). As a result, many sites end up underperforming, resulting in wasted start-up costs, extended study timelines and, in many cases, poor quality trial data.
A site’s ability to enroll and retain patients can significantly affect trial costs. However, it can often be difficult and time-consuming to determine which sites are most likely to successfully enroll patients and provide timely, quality data.
Many sponsors make enrollment decisions based only on how a site previously performed on their studies. However, sponsors can now use an investigative site’s historical performance across all studies from numerous sponsors to make these important clinical trial site selection decisions.
Centralized, Cloud-based Site Performance Databases
Today’s centralized, cloud-based site performance databases use algorithms to score a site’s historical performance relative to other sites using criteria integral to each study. Sponsors can gain a complete picture of a site’s performance by adding in historical data from other industry sources. These data include:
- Patient enrollment scores
- Site quality scores
- Site operational efficiency scores
- Site overall scores with indication and phase specificity
Site-specific study data across all sponsors are stored in a centralized, cloud-based database that can be accessed with proper credentials from anywhere, at any time. And, sponsors can gain a complete picture of a site’s performance by adding in historical data from other industry sources.
Centralized, cloud-based site performance databases are just one example of the technological advancements that help sponsors get the most out of their investigative sites during clinical development. By leveraging this tool in clinical trial site selection, sponsors recognize significant cost, time and data quality benefits with minimal investment and disruption to current operations.
Be on the lookout for the next installment in our series, which looks at how to standardize and improve clinical trial data quality through effective rater training.
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- Treweek, S. ‘Meeting the challenges of recruitment to multicentre, community-based, lifestyle-change trials: a case study of the BeWEL trial,’ Trials. 2013; 14: 436. Published online 2013 Dec 18. doi: 10.1186/1745-6215-14-436
- 2. Outlook Report: Tufts Center for the Study of Drug Development, Phase II & III Enrollment Performance on a multi-center study, Tufts University, 2014