Site Metrics for Study Start-Up
Study start-up (SSU) for randomized controlled trials (RCTs) is usually a long and costly process that can cause significant delays. CTTI engaged in an effort to identify benchmarks in the SSU process in order to help optimize the operation aspects of multicenter trials. At the Site Metrics expert meeting, it became apparent that definitions of SSU processes and collection of SSU data vary widely among sponsors. Using CTTI-developed proposed definitions for SSU benchmarks, CTTI obtained data from research coordinating entities and identified factors that were significantly associated with reduced cycle times. These included the use of central IRBs as opposed to local IRBs and status as a private practice or independent research site.
Standard measures of SSU efficiency are needed to improve study initiation processes at US research sites. Meeting this goal may require considerable time, effort, and infrastructure changes; however, continued collaboration across stakeholder groups can facilitate progress in measuring and improving the SSU process.
Project Status: Closed
Christine Pierre, Co-Leader of CTTI’s Site Metrics Project President of Society for Clinical Research Sites
“CTTI’s Site Metrics Project reported on specific metrics and benchmarks related to study start-up and recommended greater standardization within the industry. Both of these findings reinforced the Society for Clinical Research Sites’ (SCRS) work with industry stakeholders to address issues related to streamlining study start-up. Additionally, SCRS will use the early benchmarks for study start-up activities to work with the site communities to gain greater operational efficiencies.”
Prolonging the time between 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 pose 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.
Three workstreams with distinct roles were defined to gather evidence:
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, postcontract-to-patient cycle) was, in part, dependent upon organization type. Of the 7 time cycles measured, 6 were significantly associated with IRB type. Factors that were significantly associated with reduced cycle times included the use of central 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 meaningful prospective collection of data. Future development of standard measures of SSU efficiency will be critical to analyzing and improving study initiation processes at US research sites; however, this may also require large-scale changes to infrastructure.
|Team Member||Diana Abbott||Duke University|
|Team Member||Swati Chakraborty||Duke University|
|Team Leader||Robert Califf||Duke University|
|Team Leader||Briggs Morrison||Pfizer Inc|
|Team Leader||Christine Pierre||Society for Clinical Research Sites|
|Project Manager||Sara Calvert||Clinical Trials Transformation Initiative|