Can Statistical monitoring really improve data integrity? A consolidated review of multiple analyses
Feb 20, 2017 6:54 AM
| Last Modified: Feb 20, 2017 11:33 AM
Chris Wells - Statistical Scientist @ Roche Products Ltd:
Can Statistical monitoring really improve data integrity? A consolidated review of multiple analyses using JMP Clinical.
It has been said that ‘Data integrity is a fundamental component of information security’ but what is the meaning of this? Broadly, it refers to the accuracy and consistency of data stored in a database over its entire lifecycle but it may have widely different meanings depending on the specific context. Within the context of a clinical trial, it refers to that data being accurate, complete and unique to the associated ‘living’ patient. Data Integrity is needed to protect the well-being of study participants and maintain the integrity of the final analysis results, so that patients, regulators and all interested parties can have belief in the data.
The opposite of data integrity is data corruption, which is a form of data loss. Data that is recorded incorrectly results in a loss of data for that patient or falsified data results in bias of the trial results.
I will review the overall findings from 20 clinical studies using JMP Clinical and report on the level of findings and how they contributed to enhancing the overall data integrity.