Late last year, we asked 300 global leaders in clinical operations (ClinOps) to participate in a survey that focused on identifying their biggest barriers to delivering trials on-time and within budget. We received responses across the globe, and they came in so quickly that we had to shut down the survey earlier than anticipated.
When the dust settled, the survey results were clear: data quality is ClinOps’ biggest challenge. This probably isn’t news to most of you. What surprised us, however, is that there is considerable alignment on the solution for this data quality problem—and its potential to make an impact on the efficiency of clinical trials. That is, data quality is both the biggest challenge and opportunity facing ClinOps leaders today.
Milestone Achievement is a Top Priority, Yet Tough to Accomplish
It should come as no surprise that achieving milestones is considered a critically important objective. Our survey suggests that 83 percent of ClinOps leaders consider milestone achievement a top priority.
Although an important objective, meeting milestones is tough to achieve. In the survey, eight in 10 report that they regularly miss milestones. As a result, every ClinOps leader reports that they have initiatives in place to improve milestone achievement.
ClinOps leader agree that the following five initiatives are critical for improving success in focus areas and reducing the incidence of missed milestones:
- Study quality metrics
- Continuous quality
- Risk-based monitoring
- Centralized monitoring
- CRO oversight
If everyone is aware of the initiatives necessary for improvement, then why are milestones regularly missed? We asked survey respondents to provide additional context on their focus areas within these initiatives. In short, we wanted to learn what processes were most important for them and get additional context on how they were performing.
There is a Gap Between the Importance and Success of Key Processes
To reduce the likelihood of missed milestones, ClinOps leaders focus on three critical processes:
- Enrollment
- Site productivity
- Subject compliance
For enrollment, they are largely focused on how quickly sites are able to recruit patients, why patients fall out of the recruitment funnel, and how to correct underperforming sites and studies. Once sites are activated, it is important to ensure that they are being properly monitored, that data is being accurately captured, and that issues are proactively resolved. And for patients in the study, it is critical to track compliance with protocols, including monitoring of endpoint data, protocol deviations, and adverse events.
When we surveyed ClinOps leaders, the vast majority consider enrollment (95 percent), site productivity (75 percent), and subject compliance (65 percent) to be “very important”—suggesting they are actively dedicating considerable resources to address these areas.
Although they consider these areas important, the majority of ClinOps leaders are not finding much success in addressing them. In fact, only 47 percent consider their enrollment process to be successful, 22 percent consider their site productivity processes to be successful, and 25 percent consider their subject compliances processes to be successful.
Significant gap between importance and success of milestone-driving processes.
Bridging this gap between importance and success in addressing each area is critical to reduce missed milestones and trial delays. These delays cause a drag on productivity and lead to significant operational cost overruns. In the survey, 80 percent of respondents report that a three-month CRO change order costs over $100,000, and 23 percent reported that it cost them over $250,000. This data shows broad alignment on the challenges facing ClinOps leaders today.
Existing Solutions Are Insufficient
Fewer than 10 percent report having access to the software tools that enable automation of these initiatives. In addition, almost two out of three ClinOps leaders report they use manually compiled spreadsheets for their operations. Reflecting the lack of appropriate tools for managing their clinical trials, these leaders described a number of limitations as the key barriers to improving the success of key processes:
- Inability to investigate issues in real-time
- Lack of visibility into data and actions being taken to address issues
- Data across too many disparate data sources makes it tough to identify issues
Without capabilities that provide accurate and timely clinical data quality, it is no surprise that the majority of these leaders describe their decision making process as reactive. Without accurate and timely data to guide answers to these questions, ClinOps leaders must make decisions with uncertainty. This uncertainty can lead to delays in diagnosing or responding to issues, which in turn, leads to missed milestones.
Automating Manual Processes is the Path to Success
Fortunately, ClinOps leaders are also aligned on the right path forward. The majority agree that automation—in lieu of manual processes—for data collection, analysis, and management is critical for improving milestone achievement. In this survey, most respondents identify real-time data aggregation across systems and studies as the most important attribute of any solution. Below is a full list of the top five system requirements to improve clinical data certainty.
This list of requirements describes the critical elements of an automated approach to clinical trial management. When empowered with automation, ClinOps leaders have access to accurate and timely data. Armed with this data, these leaders are able to make smarter, proactive decisions that keep the study on time.
Conclusion: Data Quality is the Biggest Challenge and Opportunity
As the complexity of clinical trials increases, so do the challenges facing ClinOps leaders. The 2016 ClinOps Benchmark Report shows that most of these leaders are experiencing the same issues. Data quality is the biggest challenge and opportunity facing clinical operations today.
This article can also be found in the September/October 2016 issue of Pharmaceutical Processing.
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Filed Under: Drug Discovery
