Prolonging the time from protocol finalization to participant enrollment can have detrimental effects on the overall success of a given trial; this is especially true in large, multisite trials. While reducing the time required for study start-up (SSU) activities will lead to considerable benefits to trial conduct and drug development overall, the lack of standardized, industry-wide metrics poses a challenge to implementing wide-reaching change. At the time of this project’s initiation, little information was available on the variability of site performance and the factors that contributed the most to delaying SSU.

Site Metrics for Study Start-Up (2010-2013)

Identify and quantify components of SSU activities to enhance SSU and trial enrollment.

Resolution of the issues identified by CTTI can inform an enterprise-wide effort to define standard, universal SSU metrics/definitions.

Two workstreams with distinct roles were defined to gather evidence:

• Workstream 1: Data Collection
  • Developed a preliminary list of proposed data elements from which to generate standard metrics for SSU activities
  • Tested the workability of this list by retrospectively collecting these data elements from multiple organizations conducting clinical trials and by calculating metrics from these data elements
• Workstream 2: Define Metrics
  • Expert meeting

During the early phase of this project, CTTI developed proposed definitions for SSU benchmarks and obtained data from research coordinating entities. Cycle time for different metrics (e.g., site cycle, site-to-IRB cycle, site-to-contract cycle, site-to-patient cycle, IRB cycle variables, post-contract-to-patient cycle) was, in part, dependent upon organization type. Of the seven-time cycles measured, six were significantly associated with IRB type. Factors that were significantly associated with reduced cycle times included the use of single IRBs.

A retrospective data collection effort and discussion during the expert meeting revealed substantial inconsistencies in the collection and definition of SSU data that was tracked by different organizations and even within the same organization. In addition, there was often decentralization of these data and storage in multiple databases within organizations. The decentralization of data and lack of consistent, standard SSU definitions pose a significant challenge to gathering quality data on SSU metrics and inciting change in this area. Additionally, data governance policies of many organizations may also impede standardized definitions.

Findings of CTTI’s evidence-gathering activities were published in January 2013, detailing the wide variation in how data is collected, defined, stored, and governed across organizations and how this will impact attempts at a meaningful prospective collection of data. Future development of standard measures of SSU efficiency will be critical to analyzing and improving study initiation processes at U.S. research sites; however, this may also require large-scale changes to infrastructure.

Organization affiliations are listed as active affiliations during the project.