The Pitfalls of Using Paper and Excel for Clinical Data

Keeping track of patient data and study progress is crucial to the success of a clinical trial. However, many organizations still rely on outdated methods such as paper records and Excel spreadsheets to manage their clinical data. 

While these methods may seem convenient and familiar, they come with a host of pitfalls that can lead to errors, delays, and increased costs. 

In this blog post, we will explore the dangers of using paper and Excel for clinical data management and discuss why it's time to consider a more advanced solution.

Clinical trial data is unsecured 

The clinical data produced by medical device trials is hugely important to every aspect of a product’s lifecycle. These studies draw upon the first-hand, real-life experiences of subjects using or interacting with your proposed medical device. In fact, these are more than subjects—they’re the very same kind of patients that inspired your device in the first place. 

So with so much of your success riding on the clinical trial data, keeping it secure and untainted should be a top priority. Unfortunately, when medical device companies use paper records or an Excel spreadsheet, the result is just the opposite.

Data integrity plays a big factor here, as you need absolute certainty that the clinical data has not been modified, erased, or tampered with in any way. However, paper records of clinical data can be easily lost or damaged, and Excel simply is not built with the level of permissions or access management found in a pre-validated EDC solution. 

Another hit on data integrity comes from paper and Excel systems’ lack of error control. Excel has no debugging tool or testing frame to inspect all affected cells, such as after a change or new entry. It also fails to provide automated traceability or role assignments for approving or denying changes to data, both of which could be used as a failsafe in the event of human error. 

Lastly, there’s the issue of a lack of centralization in paper and Excel methods. Clinical trials often happen at multiple sites, and without a firm plan for centralizing your data collection, it can create data fragmentation—especially if the methods for each entry location are different.

Poor project management for clinical data

Excel is not specifically designed for project management in clinical trials and may not have the necessary features and capabilities to effectively manage the complexity and rigor of a clinical trial.

• Setting and monitoring study milestones
• Identifying and adjusting for risk events
• Documenting the completion of tasks
• Automatically initiating tasks based on the completion of others

Additionally, it’s important to remember that Excel is simply a spreadsheet program. It is not designed to promote collaboration, nor is it particularly user friendly. Even for those organizations stuck on an archaic system of paper records, that data will all need to be entered into a computer at some point—a process which could be painstaking, time consuming, and potentially riddled with human errors associated with manual input.

BONUS RESOURCES: Click here to access the free, on-demand webinar recording and PDF slides of Key Pitfalls to Avoid in Medtech Clinical Data Collection.

Some additional project management shortcomings of Excel for clinical data collection are:

• No version control
• Lack of automation
• No data-portability
• Low reusability, or an inability to reproduce results
• Ineffective scaling of clinical trial size and scope
• Manual modifications to a spreadsheet are often undocumented
• Excel is not an open system
• No centralization

Lack of regulatory compliance for clinical data

No clinical trial happens in a vacuum, nor is it free from the requirements of its regulatory environment. Regulatory bodies around the world maintain strict requirements for the processes and tools used in clinical trials. 

In both the United States and the European Union, the relevant regulations for clinical trials are harmonized with ISO:14155, the global standard for clinical trials and collecting clinical data for medical devices.

At the core of ISO:14155 2020, you’ll find a set of guiding principles and standards known as Good Clinical Practice (GCP). GCP’s primary goal is to ensure the wellbeing of all human subjects and confirming the accuracy and integrity of the clinical investigation and results. But, what does this have to do with the pitfalls of paper and Excel in clinical trials? 

If we look to section 7.8.3 of ISO:14155, we see that if an electronic system is used as the primary location of document storage and filing, the system must be validated in order to evaluate authenticity, accuracy, reliability, and consistent intended performance of the system. That means that whatever software used for storing clinical data needs to be validated, something that is nearly impossible to do with a general purpose system like Excel.

Clause 6 of ISO:14155 covers clinical investigation conduct. The good clinical practices outlined here are intended to ensure that the investigation maintains strict accountability and tight controls over documentation and recording. 

That means privacy must always be maintained and data should be protected against unauthorized access—two requirements that neither paper records nor Excel spreadsheets can guarantee. 

Another element of GCP is the requirement that all human subjects must be documented and accounted for over the course of the investigational study. Additionally, ISO:14155 gives specific instructions for document retention, all to maintain traceability. Again, paper records or spreadsheets simply don’t have the reliability of an EDC system, where eCRFs feature automatic validity checks, as well as document control practices.

Paper and Excel majorly limit your clinical data collection capabilities.

When performed correctly, clinical trials can be a fruitful process that leads to safer and more effective products being brought to market faster. However, much of that upside depends on your ability to adjust study direction, demographics, and overall scope to best fit your medical device study. 

Optimizing form design is one of the most important best practices when it comes to implementing electronic case report forms (eCRF) for medical device clinical studies. The process of form design includes:

• Determining what data should be collected,
• Determining which data fields are required and which may be optional,
• Formatting your eCRF to facilitate efficient and accurate data entry.

A well-designed eCRF should capture just the data needed to support or refute the research hypothesis, as collecting excess data means wasting time and money on data entry, preparation and analysis.

When you’re saddled with a paper-based record system or stuck staring at Excel spreadsheets, making sudden adjustments on the fly isn’t quite so simple. One of the major limitations of using paper and Excel for data collection is the lack of real-time data.

With paper forms, data must be manually entered into Excel or another database, which can lead to errors and delays in data analysis. This can also make it difficult to quickly identify and address any issues that may arise during the trial. 

Another limitation of using Excel for clinical data collection is its lack of audit trails. In section 7.8.2 of ISO:14155, it states that any change or correction made to written and electronic data on a CRF must be dated, initiated, and explained, all without obscuring the original entry. With Excel, this kind of traceability is not possible, as general purpose tools lack the built-in validation and error-checking that is essential for accurate and reliable data collection.

BONUS RESOURCES: Click here to access the free, on-demand webinar recording and PDF slides of Key Pitfalls to Avoid in Medtech Clinical Data Collection.

Avoid the pitfalls by choosing Greenlight Guru Clinical for your next clinical trial

Electronic data capture (EDC) systems are specifically designed for clinical trials and offer many benefits over paper and Excel. EDC systems provide real-time data, built-in validation and error-checking, and robust security measures. They also allow for efficient data management, analysis, and reporting, which can greatly improve the overall success of the trial.

Greenlight Guru Clinical’s EDC software is the first and only data collection and management solution that’s purpose-built for medical devices and diagnostics. 

With Greenlight Guru Clinical, you can design highly customizable eCRFs, then deploy those eCRFs in clinical studies to replace paper-based data collection, eliminate the risk of transcription errors, and reduce the cost of running your study.

Ready to learn more? Contact us today for a customized demo.