What is meant by "good data integrity" in clinical research?

Good data integrity in clinical research refers to the accuracy and consistency of data throughout its lifecycle. This principle ensures that data is collected, stored, and processed correctly, enabling researchers to trust that the results generated from this data are valid and reliable. High-quality data integrity prevents errors and discrepancies that could lead to misleading conclusions, ultimately affecting patient safety and the scientific validity of the research findings.

While simplicity in data collection, volume of data, and the use of electronic data management tools can contribute to the overall effectiveness of a clinical study, they do not directly address the core concept of data integrity. It is essential that regardless of how data is collected or managed, its accuracy and consistency must be maintained to uphold the standards of clinical research practice. A failure in data integrity can undermine the entire research process, leading to incorrect results and decisions. Thus, focusing on accuracy and consistency is fundamental in ensuring good data integrity.