Journal article
The metrics behind high performing study startups: two-phase statistical analysis identifies the key performance drivers in clinical trial startup
Applied clinical trials, Vol.23(6-7), pp.20-28
01 Jun 2014
Abstract
Study startup underperformance and inefficiency has been a problem for executives who manage clinical research trials for decades. Study startup is the most challenging and important stage of any clinical trial. At the same time, startup also has the lowest performance scores and the greatest variation in performance of any of the other stages of clinical trials.1 For clinical study managers, the key to high performing studies is appropriate governance.23 That is, they should be able to track performance as the study progresses in order to appropriately manage performance.4 But of the hundreds of activities involved in starting a clinical trial, what are the key indicators that they should watch to know if the study startup is going well? This issue is important because busy clinical study managers worry about their "blind spots" or the innocuous issues that come back to undermine the trial. When a trial is outsourced, governance issues are magnified as clinical trial managers try to assess performance across organizational boundaries.
In order to identify the key drivers of study startup, we took a two-phase research approach. In the first phase, we sought to identify all of the important drivers of study startup performance by asking a broad variety of experienced clinical trial managers to identify the performance drivers. This approach reduces subjectivity bias because the identified drivers will not be our opinion, but that of a broad group of experts. In the second phase, we compared all of these drivers in a statistical model to see which of the drivers from phase one had the most substantial and significant impact on study startup performance. This research is part of the Clinical Trials Outsourcing Performance (C-TOP) study, an ongoing collaboration between Drexel University and CRO Analytics examining all of the phases of clinical trial performance. The research was conducted under Drexel University institutional review board (1RB) approval.
The operational timelines assess the ability of the clinical study team to meet the planned milestones in a timely fashion. Examples of operational timelines in study startup include activities such as the creation of the project and operations plans, study-specific convention (i.e., the definitions for terms in the study, such as, for instance, what "high cholesterol" means), forms and documents (e.g., case report forms, informed consent forms, or patient enrollment forms). Study startup operational timelines also includes activities such as IT system setup and submitting the appropriate documents to regulatory agencies (IRB forms, FDA forms, or clinicaltrials. gov registration). We recognize that the recruiting timelines are a subset of the operational timelines, but our subjects thought that the recruiting timelines were important enough to justify being assessed separately.
Several statistical indicators suggest that the model performed well. A substantial number of the paths were significant and the model explained high levels of variance in the important variables (project manager R2 = 81%; operational timelines R2 = 71%; study startup performance R2 = 73%). The two project-manager variables (i.e., knowledge and interpersonal skills) requiring detailed indicators demonstrated discriminant and convergent validity. It was originally thought that the investigator-related variables (ability to identify qualified investigators, timeline for recruiting investigators, and investigator meetings) would constitute a single "investigator" latent variable. This measurement structure didn't work well, so the variables were broken out as individual contributors to study startup performance.
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Details
- Title
- The metrics behind high performing study startups: two-phase statistical analysis identifies the key performance drivers in clinical trial startup
- Creators
- Michael J Howley Jr - Drexel University, MarketingPeter Malamis
- Publication Details
- Applied clinical trials, Vol.23(6-7), pp.20-28
- Publisher
- MJH Life Sciences Media
- Number of pages
- 6
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Marketing
- Identifiers
- 991021899413704721