Data Trends in Clinical Trials
July 19th, 2011 by Rick Morrison
At the DIA meeting last month, we spent a lot of time listening to people both at our booth and at sessions, and we noticed several trends within the clinical trial industry, which we’ll try to explain here.
Metadata and Standards
While the current data standards, like CDISC, are great in many ways, there are issues around the fact that they only store data in a specific way. There is no way to take metadata that was created at different times over the study’s lifecycle and effectively track them with the CDISC standards.
Every time data is transferred, information gets lost. The most egregious data loss occurs within the metadata, and by the time data moves from protocol, to the EDC system, to the private database used for lockdown, most metadata is lost. Performing quality checks on this data is impossible, there’s no traceability. If something went wrong, did it happen in the first transition? the second?
Integration of all of these systems ends up providing great benefits for users. Single sign-on alone allows minor but time-saving benefits. Proctor and Gamble combined their EDC and RTSM systems and saw big benefits from a modest integration.
We are now seeing EDC, CTMS, RTSM and Safety systems all becoming more interoperable. This is starting to have real impact. A data manager can be more than just a data manager, when the system they use allows them to have a better understanding of the entire operation.
Quality is King
With this type of integration, there is now the possibility of measuring quality in more effective ways.
Quality is typically measured by protocol deviation. With modern tools, it is possible to look at deviation patterns and what’s driving them. By having full integration of all clinical systems, it’s possible to do near real-time analysis of deviations, and increase quality across the board. It can take days where it used to take months to analyze across all patients.
With the ability to do near real-time analysis, stakeholders need ways of keeping on top of the data as it changes. Giving users a quick way to understand how their sites are progressing or how their finances are changing becomes imperative. This is where powerful and modern executive dashboards can help. A powerful dashboard can provide the ability to summarize, and then drill down into the underlying data to answer questions quickly and effectively.
Near real-time dashboards mean that the fundamental processes surrounding clinical trials are changing. Advances like data-triggered monitoring and data-driven data management become a reality. It now becomes easier to identify protocol deviations, data quality issues, patient safety issues, enrollment issues, safety issues, and a ton of other potentially devastating problems.
The New Data Manager
Right now data managers act like a “monkey in the middle”:
- Clinical monitor gives data to the data manager.
- The data manager hands the data off to the statisticians
- The statisticians complain the data is not clean enough, and give it back to the data manager
- The data manager interfaces with the monitor, or cleans the data manually, and gives it back to the statistician
- Repeat steps 3 and 4 ad nauseum
By using data-driven, trigger-based monitoring it becomes possible to keep your data clean and avoid this mess.
To learn more about the future of clinical trials, sign up for our upcoming webinar, Uncovering Hidden Problems in Clinical Trial Data. We are the makers of next-generation reporting and visualization software, called Comprehend Clinical.