Current Challenges in Clinical Data Management Today
Critical Insights on Clinical Data Management Efficiency
Recent industry research unveils alarming trends regarding the efficacy of clinical data management, revealing that a significant portion of data managers and clinical research associates (CRAs) are concerned about the future quality of clinical data. This newfound urgency stems from the substantial time and effort dedicated to manual tasks within the clinical data workflow.
Manual Processes Impacting Time and Quality
The findings indicate that completing manual data reconciliation, cleaning, and review tasks requires each data manager to spend over 12 hours each week, per study. This crucial insight underscores a significant concern: approximately 97% of respondents indicate that these tasks are typically handled outside clinical systems, contributing to increased workload and potential risks to data integrity.
Need for Automation in Data Management
A prevalent theme emerging from the survey is the demand for enhanced automation. A substantial 71% of data managers believe they will rely on automation more heavily for data cleaning within the next two years. The push towards automating data management processes aims to minimize time spent on spreadsheets and redirect efforts towards strategic initiatives, such as risk-based data management.
Documentation and Tracking Challenges for CRAs
CRAs, on their part, express a strong desire for improved documentation and tracking systems. The existing lack of seamless connectivity across clinical systems necessitates manual validation of monitoring visits, leading nearly half of the CRAs to identify this as their top priority for enhancing clinical trial efficiency.
Barriers to Efficiency in Clinical Trials
The research also highlights several obstacles hindering efficiency in clinical data management. Major challenges include protocol complexity, resource constraints, and resistance to change. Approximately 58% of respondents cite protocol complexity as a barrier, while 57% point to limited budgets and resources, and 48% acknowledge hesitance to adopt new approaches. Addressing these barriers presents a valuable opportunity for clinical leaders to foster innovative practices that enhance collaboration between data managers and CRAs.
The Importance of Connected Systems
Respondents overwhelmingly agree that employing connected clinical systems could significantly streamline study execution. While 75% of data managers report that their teams are actively modernizing their systems, only 57% of CRAs feel the same. This disparity indicates a substantial gap in the adoption of tools optimized for real-world workflows, which can impede overall progress.
The Future of Clinical Data Management
Manny Vazquez, senior director of Veeva Clinical Data strategy, emphasizes the broader implications of the findings, stating that the risk of poor data quality extends beyond individual monitoring visits and can potentially affect regulatory submission outcomes. The research indicates a clear call to action for those involved in studies to advocate for simpler, more automated processes that could ultimately lead to more efficient clinical trials.
To delve deeper into the state of clinical data management, Veeva recently conducted a comprehensive survey, which evaluated the productivity of over 85 data managers and CRAs across various clinical research organizations and sponsors. The insights gleaned from this research aim to propel advancements in clinical trials, enabling organizations to identify root causes of inefficiency and implement effective changes.
About Veeva Systems
Veeva (NYSE: VEEV) provides innovative cloud solutions designed specifically for the life sciences industry, combining software, data, and business consulting. Veeva is dedicated to driving innovation and excellence, catering to a diverse clientele, including leading biopharmaceutical companies and emerging biotechnology firms. As a Public Benefit Corporation, Veeva balances stakeholder interests, ensuring services meet the needs of customers, employees, and the wider healthcare industry.
Frequently Asked Questions
What did the research reveal about data managers' workloads?
The research highlighted that data managers are spending over 12 hours each week, per study, on manual data reconciliation, cleaning, and review.
Why is automation a key priority for data managers?
A vast majority of data managers are focusing on automation to alleviate the burdens of manual data processing, allowing them to engage in more strategic activities.
What challenges do CRAs face in their data management?
CRAs reported that the lack of system connectivity has led to increased manual validation efforts, which they see as a barrier to efficiency.
How do connected systems influence clinical trial productivity?
Connected systems are viewed as essential for improving workflow efficiency, making clinical trial execution smoother and more effective.
What future changes are anticipated in clinical data management?
The research suggests that clinical data management roles will increasingly rely on automated processes to enhance productivity and data quality over the coming years.
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