Clinical data validation refers to a collection of activities by data management team to assure validity and accuracy of the clinical data. Data Validation is a process required :
– at the Software level
– at the Applications level
– for human interactions at all levels
The different types of Data inconsistencies are checked by the validation process are:
– Data complete
– Data legible
– Data consistent
– Data Logical
– Data Correct
After validation of different types of data inconsistencies the data get converted to Valid and Cleaned Data.
Why does Clinical Data need Validation?
Clinical data quality and integrity are critical from business and ethical perspective. Clinical data validation is how worth the products is evaluated form the FDA, The Association of the British Pharmaceutical Industry (ABPI), other regulators and business partners. From an ethical perspective, clinical data affect treatment decisions, which affect patient health.
What is the Validation Process?
There are many factors that affect the validation process – it is dependent on the data captured, business and regulatory concerns and not only. The steps in the process are:
– Planning
– Implementation and Testing
– Data Entry and Validation
– Database Lock
Even after database lock, analysts may run further checks to determine if any changes are necessary in order to produce the analysis datasets.
Clinical Data Validation is one of the topics that will be covered in our next webinar on Clinical Data Management Advanced Electronic Data Capture Systems. The webinar will discuss the process of collection, cleaning, and management of subject data in compliance with regulatory standards. The online training session is certified and is taking place on 12-th November 2015. Hurry up and get the Early-bird registration until 5th November, 2015.
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