Throughout my career in the Life Science industry, I always worked with data using multiple EDC/CDMS tools (Clindex, Oracle Clinical, ERT and Rave). Developing reports and creating study databases has always been part of my daily activities and one of the biggest challenges I always had was being able to map the same type of data across studies.
As we look deeper into how we can really gather data across studies, we find the true value of data standards. Lets look at a simple example within the Medical Device arena - every study uses enrollment date and procedure date. If the "Procedure Date" is designed different for every study using a different field name name (i.e. PROCDT vs. PROCDAT), then the standards are broken and we can not look at procedure dates across similar studies. However, if standards are developed and all studies use the same PROCDT as the field for "Procedure Date", then reviewing the procedure date across studies becomes simpler.
With that said, standards play a big role in being able to run reports across studies. However, there is a lot more work that goes into reporting across studies and more data points have to be identified in order to make this possible.
Back to our topic on standards, many companies are starting to recognize the importance of data standards, but are not sure where to start. Well for beginners, I would recommend to start developing the CRFs using CDASH standards. Keep in mind that while CDISC does not have an answer to every question, they provide a standard way for how it should be done.
