Before the 90s, clinical data management using paper and Excel was still a to-go way. Nowadays, even though leading enterprises are planning to use EDC for 100% of their trials, the traditional method is still utilized in about 30% of clinical studies. Certain reasons exist for this choice, but in comparison with EDC, the conventional method not only causes inconvenience but also poses a threat to data quality, as well as standard and regulation compliance, causing undesirable mistakes in the trial.
Below are three main reasons why we should forget paper and Excel to use EDC now for clinical data management.
Unreliable and insecure data
Different from EDC systems that strictly comply with FDA regulations on clinical data management (21 CFR Part 11), procedures with paper and Excel don’t respond well to these demands. 21 CFR Part 11 regulates that any item must be retrievable when necessary and all changes must be recorded. However, with Excel, we CAN’T know who made the change, when they did it, what the old and new values are and why the change is made.
The traditional method doesn’t allow user decentralization because Excel doesn’t offer this feature like EDC. Excel is highly limited in access authority management, which can result in data misconduct and consequently do harm to data integrity.
One of the limited features in Excel is that with different devices, versions and default settings, data can be differently organized. At the same time, each person taking charge of their own Excel file will lead to difficulties in identifying who created the original file. Too many copies mean high chances of insecure data.
High error possibility in data entry
Since Excel is a software used worldwide, studies that use this method will shorten the time for training on data management procedure. Data entry on Excel must follow the double data entry process to minimize risks. Nevertheless, in many cases, an incentive to reduce workloads and costs as well as an unsupervised environment can lead to single data entry.
Excel has some basic integrated functions to verify data with multiple formulas, which makes data entry susceptible to errors without any caution. With EDC, thanks to edit checks built in advance during set-up, users can reduce faults with regards to the determined data range. What’s more, since all involved personnel works on the same platform with constantly updated real-time data, it is convenient to put up one or some queries which will be resolved in no time. As a result, data accuracy is better guaranteed.
Complex and passive operation
Conducting clinical trials is an activity that is frequently outsourced and carried out on multiple sites around the world as well as over a country (multicenter study and multinational study). Besides, a clinical trial is conducted with the collaboration of various related parties, from authorized agencies and sponsors to conducting agencies to other vendors. Therefore, this activity needs to cater for the tight collaboration, in which communication becomes highly crucial. Yet Excel fails to meet this demand. Information exchange is via email and phone, which means dozens of files are transferred without a bit of security.
With EDC, any data exchange can be done directly on the problems/errors of that datum without the need to communicate outside the system. Decentralization system helps make data access safer and more reliable. Thanks to the cloud-based technology, all members involved in the process can work on a single platform as well as work proactively in any space and time with internet-connected electronic devices.
Conducting a clinical trial is no doubt extremely expensive. A company on average spends $2.6 billion on a new drug, in which drug trial is one of the periods that costs the most resources. Not only is the expenditure nowhere near small, it is constantly increasing (at a rate of 11.8% per year) while revenue is only growing at about 4.5 – 5.5%.
In traditional methods, FDA requires researchers to double data entry. This leads to a significant increase in human resources and lengthens trial data processing. At the same time, due to disadvantages of not working on the same system, data is not tackled in real time, meaning that data monitors have to travel to sites more frequently.
Using EDC helps to reduce 43% of the time to data lock, 86% of the number of queries as well as 30% of study duration. Besides, expenditures on personnel and other operational spendings are also remarkably cut down because data verification process is much more simple and convenient. Consequently, the overall cost of collecting and managing data is saved up to 30%.
In small studies (at Phase I and II) that are not too complicated and located in undeveloped areas, data collection and management are still mainly done by traditional methods via paper and Excel. Yet EDC is an inevitable trend that is playing an increasingly important role in conducting complex studies with cost efficiency and trusted data.