Sine quo non; without which nothing.

This bit of Latin should be on the forefront of your mind when deciding on what system you will use to collect data for your clinical trial. Lacking a reliable method of data collection, no amount of well laid plans in other areas of your project will make up the difference. A subpar system for collecting data in your clinical trial can lead to subpar results; sometimes even unusable results. The success of a clinical trial depends on a well-designed study protocol and on a system capable of capturing and maintaining accurate data collected throughout that study protocol. A centerpiece of clinical trials is the case report form (CRF). Whether you're collecting basic demographics data or collecting experimental data, your CRFs are where it's all recorded. If there's a problem at that stage, there will be problems downstream soon enough.

What's the challenge?

The investigator or physician needs to record all of the relevant clinical and non-clinical data for each subject in their case report forms (CRF). The collected data in the CRF is the life blood of a clinical research organization (CRO), so the accuracy of this data is of paramount importance. The traditional paper documentation is widely use even today, though at the peril of the research organization. In the paper documentation, initially, the data gets collected in the paper-based forms and later the collected data are entered into an electronic database for computer data analysis. However, paper-based CRFs have a number of disadvantages. The most significant problem associated with paper documentation is the frequency of errors in transcription of the data into an electronic database. This task is not only tedious, but is ripe with opportunities to corrupt the data your team has worked painstakingly to collect. Another common issue is for values on paper CRFs to be outside of proper ranges due to the lack of controls and lack of compliance with procedures on the part of those filling out the CRFs. Worse still is when data is recorded on the margins or in other places on CRFs where it should not have been entered, raising concerns about validity.

Paper CRFs lack:

• A scalable way to check for issues in study execution prior to study completion, and as a result, no way to correct them
• The ability to automatically populate common fields such as Study Number, Subject ID, Site ID, Date, Subject Initials, and the like
• Parameters for limiting the data entered at the time of collection
• The ability to run edit checks on the values entered
• A way to easily and affordably aggregate and analyze the collected data at study completion
• Automatic backups, leaving open the possibility of water damage, fire damage, or even loss of the documents
• A safe and affordable way to transport the documents

What's the solution?

Enter Electronic Data Capture. With the ability to review and analyze data in real-time and to implement online data validation checks to ensure data quality more effectively at the point of entry as well as the ability to run edit checks against data after it's been entered, EDC offers huge benefits in the data quality department. The efficiency and effectiveness of these real time edit checks can save hundreds of hours over the course of the study and lead to higher quality data, which is after all the ultimate goal. Because of the problems with PDC, in recent years electronic data capture (EDC) systems have steadily gained popularity among researchers. The steady march of technology made it possible to collect clinical data on portable devices like laptops, tablets, and smart phones. They've even made it possible to collect data from a subject's cell phone using text messages (SMS). Clinical EDC systems have matured into a flexible, affordable, efficient, and, most importantly, reliable, alternative of paper-based data collection (PDC). In many ways EDC emerged primarily as a solution to the many problems associated with PDC. It has often been observed that large scale, especially multicenter, clinical trials involve huge amount of labor and resources are consumed to make PDC work. However, due to difficulties in managing data in this way, it can become impossible to utilize for the analysis which was the goal in the first place. The result is a huge use of manpower and resources for a subpar data set.

The advantages of EDC over PDC are vast:

• Improved data quality via real time edit checks, ensuring data input is in the expected format
• Time savings starting right from the moment of data collection
• Time savings all the way to the moment of database lock, which is almost always faster with EDC
• EDC increase the scope of communication between users
• Faster and more easily traceable online discrepancy management
• Near zero chance of data loss due to automated backups
• Simple exporting and analyzing of data
• Easy transfer of study data
• The ability to collect data in the field using smartphone apps, text messages and more. Application of EDC can lower the risk associated with faulty data entry, incompleteness etc., as alarms, automatic completions and reminders options are there to prevent these
• The ‘just in time' access is possible with EDC which enables faster data searches with high physician efficiency
• The EDC can save a large physical space for record keeping as it can store data in virtual space in comparison to paper records which needs both, space and manpower to physically sift the data
• EDC is extremely cost effective as well (Perhaps we should have mentioned that first)

If you're not sold on the benefits EDC software for clinical research, we don't know what to say! For the majority who are, you should next know what to look for in your EDC software vendor. We'll have another article soon going in depth about what to look for, but to give you a high level overview, any EDC system for use in trials subject to FDA regulations must include:

• Complete audit trails
• Electronic signatures
• Software and system documentation
• Formal system verification

References

1. Comparison of paper-based and electronic data collection process in clinical trials: Costs simulation study.
2. Basics of case report form designing in clinical research
3. Comparison of Electronic Data Capture (EDC) with the Standard Data Capture Method for Clinical Trial Data.
4. Comparison of two data collection processes in clinical studies: electronic and paper case report forms.
5. A comparison of electronic records to paper records in mental health centers