Data Quality, Rater Training and Regulatory Expectations: Basic Principles and Good Clinical Practice for CNS Clinical Trials

Clinical outcomes, particularly complex clinician-rated scales, are subject to variability and error due to issues of standardization, rater bias, inconsistencies, and scale administration and scoring errors, making it less likely that a study will yield reliable, statistically significant results.

Given the considerable risk these issues present to trial success, they have been a focus for global regulators and consortia. Robust rater training and certification protocols are suggested to ensure greater standardization and reliability.

Appropriate COA instrument selection, rater training and central monitoring are all important and significant means by which study teams are addressing regulatory guidelines and improving data quality.

Please fill out the form below to download the whitepaper and learn more about regulatory expectation and options for data quality assurance programs.

Back to Fact Sheets