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Data ownership and accountability throughout the lifecycle.Use of statistical methods for detecting data issues.Controls may include procedural controls, organizational controls, and functional controls. The World Health Organization (WHO) draft guideline on data integrity recommends having governance control strategies in place using quality risk management principles, which enables error detection, lapses, and omissions of results and data during the data life cycle. However, you also need to have systems and processes in place to ensure everyone knows their role in maintaining data integrity throughout its lifecycle. Having procedural documents, such as policies, standard operating procedures (SOPs), and risk management plans for data management available is important.
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Data is critical to decision making, therefore, it is imperative for organizations to have systems and processes in place to assure data integrity. Data integrity is critical throughout the “data lifecycle,” from the initial creation of the data through any transfers, replication, or reporting stages. Why Data Integrity is ImportantĮnsuring data integrity is an important component of the pharmaceutical industry’s responsibility to protect the safety, efficacy, and quality of drugs, as well as a regulatory authority’s ability to protect public health. Instances of data integrity failure can occur at almost any point in data creation or processing in a clinical trial, so you need multi-dimensional strategies to help prevent and mitigate data integrity issues.Īssuring data integrity throughout clinical trials requires appropriate quality and risk management systems, including adherence to sound scientific principles and good documentation practices. The Medicines and Healthcare products Regulatory Agency ( MHRA) additionally refers to “ALCOA+.” The “+” stands for “complete, consistent, enduring, and available.” The MHRA GXP Data Integrity Guidance and Definitions focuses on promoting a risk-based approach to data management, including data risk, criticality, and lifecycle.ĭata integrity is agnostic of the system used and may be collected via electronic means, on paper, a hybrid of the two, or other imaging techniques such as photographs. The Food and Drug Administration ( FDA) uses the ALCOA acronym to define expectations for data, indicating data should be: This includes all phases in the data lifecycle, from generation and recording through processing (including analysis, transformation, or migration), use, data retention, archive/retrieval, and destruction. When we think of clinical trials and the critical data we collect, we have to be very cognizant of how the data is obtained, as well as how data integrity is maintained throughout its lifecycle. In this increasingly digital world, we have to remember data is now available in many different medians, including paper.