70% of ClinOps Teams Take Too Long To Identify Study Issues. Here’s Why.

In our second blog, we shared survey results that indicated only 2% of ClinOps teams were able to complete all of their tasks on time. Today, we’ll look at how the respondents identified operational issues and initiated change. 

Because they are bogged down and overwhelmed with tasks, many ClinOps teams lack enough time to get work done and/or work efficiently. This was confirmed when respondents were asked to rate their organization’s ability to identify clinical trial issues. Just 28% characterized their organization as being quickly able to identify issues in clinical trials -- such as enrollment, data quality, and site performance -- while only 7% judged their company as excellent in this regard. And 65% of respondents saw their organization operating below a best practice level.

Respondents who said their organizations were less effective in identifying issues chalked it up to reasons such as:

• lack of proactivity
• no process in place to identify issues
• software limitations
• organizational bureaucracy
• increased workloads and
• limited resources 

Why? ClinOps teams are operating in tighter timeframes with fewer resources, smaller budgets and more responsibilities, such as handling data from many sources and dealing with multiple vendors. Nearly 20% of respondents said that aggressive timelines pose the biggest challenges when it comes to identifying operational issues more quickly. 

At the same time, the amount and types of data captured and managed in trials has increased exponentially driven by more complex study protocols and corresponding endpoints, as well as the use of wearable sensors by patients. Effective trial management is nearly impossible given staffing shortages, inadequate reporting and analytics, disparate systems, and data silos. 

“We have no process for issue deviation management and no metrics to follow up on performance and quality. Recruitment is the only metric that is followed closely” one respondent commented, an indication of a lack of proactivity. Clinical trials aren’t always set up to proactively manage issues beyond patient recruitment. 

“Software development is slow” and “poor investment in technology” were voiced by two other participants. Existing software many teams use isn’t optimized to support issue identification, and it may take too long to set up to accommodate the unique demands of each clinical trial.

The reality is that the combination of fewer resources, disparate systems and software that doesn’t properly support ClinOps teams necessitates the need for a robust CTMS. Because Medidata’s Rave CTMS runs on the Rave Clinical Cloud, it dramatically streamlines, accelerates and improves trial management, while ensuring regulatory compliance and inspection readiness. Study teams realize the intelligent oversight needed for not only efficient -- but more importantly, effective -- trial management.

In our next blog, we’ll dive into obstacles in effectively using trial data and collaborating across functions in trials.