This is What You Need to know about Clinical Data Management!

Clinical trial is one of the most important parts of today’s world. It has saved lives of millions and will save many more as because of this many diseases which were not curable at sometime are all curable now. Similarly managing clinical data is also very important.

Let us talk about what clinical data management is all about!

What do we understand by the term “Clinical Data Management”?
The process of handling data derived from clinical trials is known as Clinical Data Management. The ultimate goal of any clinical data management system is to maintain and produce quality data.

What are the steps in the process of Clinical Data Management?

The complete cycle of clinical data management is:

1. Data from source are generated. Clinical site medical records, laboratory results & patient diaries are some common examples of source data
2. If there is a usage of paper Case Report Forms (CRFs), then all the clinical site records are completely transcribed onto the CRFs.
3. Clinical trial database is then fed with data from the CRFs, as well as other source data. Source documents data can directly be entered in Electronic CRFs (eCRFs) if allowed. Data that is collected from paper CRFs are often entered multiple times and are rechecked in order to make sure that the error rate is reduced.
4. The complete data is then checked multiple times for accuracy, quality, and completeness, and if there are still any problems then they are resolved. This often involves queries that are related to the clinical site.
5. Once the data is considered final then database is considered locked.
6. The data is then reformatted in order to prepare it reporting and analysis. Tables, listings, and figures are few things which are generated.
7. The data are first analyzed and then the analysis results are reported in the system. When the significant results are found, this step may result in the generation of additional tables, listings, or figures.
8. The results are imbedded into high-level documentation such as Investigator’s Brochures aka IBs and Clinical Study Reports aka CSRs.
9. The database and other study data are then archived.

These steps are not particularly ordered. Just for example, it is a common thing in longer studies to generate intermediate discrepancies and listings on regular periods to find out problems that need correction before the end of study completion.

Elements that effect data quality!
Industry Guidance for FDA: Clinical Investigations uses computerized systems which defines the fundamental of elements of data quality for both paper and electronic records by the term “ALCOA”:

• Attributable: The source of the data is known properly.
• Legible: The data is now readable and comprehensible to humans.
• Contemporaneous: The data is recorded when it was generated.
• Original: The data is the first recording of the primary source.
• Accurate: The data is correct.

If you look at it practically, quality data also requires at least three other aspects in order to ensure quality:

• Data is readily available, transmissible & storable.
• Data is complete and unbiased with any factors.
• Data is in a format that is internally consistent & compliant with all possible readily transformable to the accepted standards.

How can we relate 21 CFR 11 to Clinical Data Management?

21 CFR 11 states the prescribed rules that are required to make sure that all electronic records are “trustworthy & reliable”. A proper implementation of 21 CFR 11 always helps to ensure that all the major aspects which are Attributable, Legible, Original, and Accurate aspects of the ALCOA are standard and are met.

Conclusion

Well in the end what we can conclude is that clinical data management is extremely important in order to make sure all the regularities are officially met.

If you are still looking to know more about this topic click here