High quality data management: does it really matter?

Initiating a clinical trial is very tedious, stressful and expensive. Regular authorities impose strict requirements and the Sponsor is required to present high-quality data.

Clinical (or... Critical) data management

Clinical Data Management (DM) is a critical step in a clinical study. A smart EDC design along with efficient data management activities throughout the study are essential to ensure high-quality, clean, reliable data, that can lead to a statistically-proven performance for the investigational product. A high-quality DM also helps to drastically reduce the time needed for enrollment, data entry and monitoring processes, thus keeping a reasonable time from development to marketing.

Designing an EDC? I can do it myself!!

Sometimes, clients think that they can just “play around” with a simple EDC system and build their EDC themselves. What a bad idea! Why? Let me explain:

- Building forms is not about using drag and drop to add checkboxes, radio buttons, numerical & text fields, a nice graphic design and being happy with the visually appealing forms you created...No, it's not (only) about how the forms look like. An efficient design implies strong knowledge about how databases are built in the core system. How data tables are arranged and linked between them in a relational database management system (RDBMS). A lack of expertise in this field will lead to a weak database system, and poor-quality data at the end.

- A professional data manager will write for you a Data Management Plan that describes the whole process followed to design the EDC, collect data properly, assign the user roles, import/ export data, clean data, identify discrepancies. The role of each study member will be clearly described and everything is clarified upstream.

- Clinical Data Management includes EDC building, data collection, cleaning and management. The goal is to get data that are as clean and complete as possible. To meet this objective, the clinical data manager follows strict Standard Operating Procedures (SOPs) at each step, from the very first review of the protocol to the EDC building, data management and discrepancy management later in the trial. Most of the time, the CDM will use strong programming skills to run scripts on the database to check data quality and identify potential issues before they have a dramatic impact on the data. Again, an amateur won’t follow these best practices and as a result, data quality will be highly reduced.

- Most of the clinical database use CDISC standards to submit data to the Regulatory authorities. The CDISC consortium works in collaboration with the FDA and EMA to develop guidelines that could be mandatory for some submissions. A professional data manager will use these standards to increase the quality of the submission to the Regulatory bodies .

- And finally, after all patients were enrolled, once the EDC is completed with all necessary data, the Sponsor will frantically send the data extract to the statistician… and maybe he will find out that the data is simply unusable, due to a misconception of the EDC and fatal mistakes in data collection.

No… cutting budget is not always a good idea. And this is particularly true when it comes to the biggest treasure a clinical trial generates: Data.

If you have any questions or suggestions, please contact me! naomi@clinxl.com