DESCRIPTION
Practical Guide to Clinical Data Management, Third Edition by Susanne Prokscha is a comprehensive, hands-on resource designed to introduce clinical research professionals to the principles, processes, and technologies involved in managing clinical trial data. Published by CRC Press, this edition reflects the growing importance of electronic data capture (EDC) and modern data management systems in clinical research.
The book provides a complete overview of clinical data management, following the lifecycle of a clinical trial from study initiation and planning through data collection, validation, quality control, and final database lock. It explains the essential responsibilities of clinical data managers and demonstrates how accurate, consistent, and reliable data contribute to successful clinical research and regulatory submissions.
Organized around the three major stages of clinical data management—study startup, study conduct, and study closeout—the book covers important topics such as data management planning, case report form (CRF) design, database development, edit checks, data collection, laboratory data management, adverse event data, data cleaning, reporting, and study closure. It also explores standard operating procedures, staff training, access controls, data security, clinical data management systems, vendor selection, system validation, and change control.
A major feature of this third edition is its expanded emphasis on electronic data capture, reflecting the industry's shift from paper-based documentation to electronic clinical trial systems. It also includes a dedicated chapter explaining the overall clinical trial process, helping readers understand how data management activities fit into the broader research workflow.
Written in a practical and accessible style, this book is an essential resource for clinical data managers, clinical research associates, clinical research coordinators, pharmaceutical professionals, biotechnology specialists, and students pursuing careers in clinical research. It provides valuable guidance for understanding data management responsibilities, improving data quality, and supporting the integrity of clinical trial results.
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