10 Reasons to Avoid Using Excel for Clinical Trials

1. Project Management:

A major shortcoming of using Excel to manage clinical trials is its lack of project management capabilities. For example, defining and tracking study milestones, assigning risk triggers with milestone re-projections, recording the completion of activities, and automatically triggering activities to begin (dependencies) as others are completed.

2. Lack of regulatory compliance:

 The FDA requires compliance with 21 CFR Part 11, which requires, among other things, the traceability of any and all changes that are made to the data. If values in a spreadsheet are changed, the history of who made the change, the date and time the change was made, the old and new values entered, and the reason why the change was made need to be recorded. Audit trial functionality is not available in Excel.

3. Unsecured data:

Who has access to the data? When? Spreadsheets have very limited permission controls when it comes to restricting access for multiple users. This lack of protection can lead to data manipulation, which compromises data integrity. Excel does not have the ability to handle role assignments.

4. Manual entry is error prone

Human data entry is cumbersome and error prone and while Excel has some basic data validation functionality associated with various formulas, data entry errors can still easily occur and go unnoticed. Even though using Excel usually saves time up front because staff already use the program and therefore do not need to be trained, a significant amount of time can be wasted on consolidating files and checking for errors.

5. Lack of version control or centralization:

Who has the master copy? Where is it? Is this version compatible with my system? Spreadsheets can be difficult to locate if they are saved to several files and folders. Often times, important information is scattered and multiple copies of a document are created.

6. Inefficient workflows:

Spreadsheets are not sophisticated enough to ensure organizations are in compliance with their standard operating procedures (SOPs) and/or regulatory requirements with regard to documentation management and workflow. Excel is, at best, a manual tracker of documentation status that is gathered via emails and meetings, meaning, real-time status is seldom available or accurate.

7. Collaboration & Communication:

Clinical trials are routinely outsourced and conducted at sites across the world. Research has become a highly collaborative industry and it is critical that research organizations have the tools to ensure the necessary communication is taking place. Use of Excel to track clinical research can be a nightmare with communications conducted by email and phone and dozens of document versions floating around without any security.

8. Oversight and partner selection:

The size, scope, and complexity of clinical trials and their associated costs are justification enough to warrant a degree of oversight. Sponsors working with numerous partners often have a hard time monitoring and selecting the right partners to work with, and Excel is no help. When selecting research partners, it is important to take a number of factors into account, including past performance, skills and competencies, equipment, and much more. Using Excel to track research makes it very hard to keep this critical information up-to-date, and its on-going monitoring is difficult to maintain using manual processes.

The complexity of oversight becomes evident when working with multiple CROs on multiple concurrent studies. The correlation of results from CROs with different reporting formats makes immediate oversight difficult. CROs’ detailed reporting often masks risk identification and is based on their own siloed custom Excel template, processes, and inaccurate, inconsistent, and outdated data. The end result is a lack of transparency and delayed decision-making, which erodes the foundation of trust.

9. Decentralization:

The use of Excel to manage clinical research, by nature, forces all research activities to be decentralized. An organization might use a database to manage patients, Excel to track finances and visit completions, a scheduling application to track appointments, and a third-party to manage recruitment. Breaking all of these research activities into different applications is not only inefficient, but leaves the door open for mistakes and staff confusion.

10. Real-time reporting:

Using Excel to manually enter data is time-consuming and dangerous, as it can lead to input errors. Any reports that do exist have to be made manually and updated regularly – one mistake can throw off the metrics for an entire study. Additionally, Excel is inflexible and, in many cases, simply can't get the job done. Capabilities not offered by Excel include flexible charts, dashboards, real-time data exploration, and capability to handle vast volumes of data and maps.