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Growing Concerns in Clinical Data Management

Recent research from Veeva Systems highlights alarming inefficiencies within the clinical data management sector. Two-thirds of data managers and clinical research associates (CRAs) voiced concerns that these inefficiencies pose significant risks to the quality of clinical data in the future.

The Scope of Inefficiency

A considerable revelation from the study is that completing tasks such as manual data reconciliation, cleaning, and review often consumes more than 12 hours per week for each clinical study. This substantial time investment is largely due to the predominant reliance on manual data processes. An overwhelming 97% of respondents reported that data reconciliation is primarily conducted outside the clinical systems, leading to heightened workloads and increased potential for data errors.

The main contributing factors to this inefficiency include:

• - Manual Steps and Data Re-entry (68%): A high percentage of data managers expressed that excessive manual operations and re-entry of data inflate the time and effort necessary for managing trials.
• - Inefficient Workflows (58%): The responses point to cumbersome workflows that fail to streamline data management tasks effectively.
• - Multiple Disconnected Systems (59%): The use of various disjointed systems further complicates the workflow, adding to the burden on clinical teams.

The Call for Automation

Amidst these findings, the demand for automation has emerged as a vital priority among clinical data professionals. 71% of data managers anticipate a shift toward increased automation in data cleaning processes within the next two years. The potential for automated systems to alleviate the administrative load currently placed on data managers is clear. By reducing reliance on spreadsheets, teams can redirect their focus to strategic initiatives such as risk-based data management, which could enhance overall productivity significantly.

Furthermore, CRAs emphasized the need for improved documentation and tracking methods, framing this as a top priority. Currently, 44% of CRAs indicated that the absence of connectivity between clinical systems necessitates manual validation during monitoring visits, further exacerbating time inefficiencies.

Barriers to Efficiency

Despite the pressing need for improvement, hurdles remain that obstruct progress toward enhanced data management efficiency. Key challenges identified include:

• - Protocol Complexity (58%): Many professionals cited intricate study protocols as a barrier hindering efficiency and adaptation to new processes.
• - Budget Constraints (57%): Financial limitations present a significant obstacle, stalling the integration of modern technologies necessary for improving workflows.
• - Resistance to Change (48%): A cultural hesitance to embrace new workflows and automated systems poses an enduring challenge for data managers and CRAs.

A Vision for the Future

The survey findings highlight a broader recognition among clinical professionals of the need for connected systems to improve productivity. A remarkable 81% of participants believe that enhancing connectivity between clinical systems could ease study execution, thus mitigating inefficiency in their processes.

The insight that approximately 75% of data managers are currently working toward modernizing their practices signals a cautious yet positive step forward. Yet, many professionals still contend that standard operating procedures do not align effectively with available tools or real-world scenarios, indicating a gap that could impede genuine advancement.

As Manny Vazquez of Veeva Systems stated, "The risk of poor data quality spans far beyond a monitoring visit or listing review, potentially impacting regulatory submission success. The research illustrates that those executing studies require change and are advocating for simpler, automated processes to enable more efficient clinical trials."

The Veeva Clinical Data Industry Research surveyed over 85 data managers and CRAs, providing a fresh lens on productivity levels during Phase III trials and identifying core inefficiencies that need addressing. The need for streamlining operations is clear, calling upon industry stakeholders to cooperate in fostering an environment conducive to advanced clinical data management practices.