ADaM Structure for Occurrence Data (OCCDS) Implementation Guide

Preface

Welcome to this comprehensive guide to the CDISC Analysis Data Model (ADaM) Structure for Occurrence Data (OCCDS) Implementation Guide. In the intricate world of clinical research, the ability to transform raw clinical trial data into clear, analysis-ready formats is paramount.

This guide aims to bridge the gap between the theoretical specifications of CDISC standards and their practical application, particularly for programmers who are at the forefront of this crucial data transformation.

Based on a detailed review and reinterpretation of Chapters 1, 2, and 3 of the official CDISC ADaM Structure for Occurrence Data (OCCDS) Implementation Guide Version 1.1, this “book” is crafted with the SAS/R/Python programmer in mind.

While the official guide provides the foundational principles and metadata, this rendition seeks to illuminate the direct implications for your daily programming tasks. We delver into the nuances of defining, deriving, and presenting occurrence data, translating abstract concepts into tangible programming considerations.

For those new to SAS/R/Python programming in the clinical domain, or seasoned professionals looking for a focused interpretation, this guide offers:

A Programmer’s Lens: Every concept, every standard, and every nuance is examined from the perspective of how it impacts your code, your data structures, and your validation processes.

Detailed Summaries: Chapters 1, 2, and 3 are broken down into digestible sections, highlighting the most critical information for data derivation, quality control, and analysis preparation.

Practical Insights: I explore the ‘why’ behind the OCCDS, helping you understand its unique role compared to other ADaM structures, and how to effectively leverage it for adverse events, concomitant medications, and medical history.

Focus on Key Derivations: Understand the critical flags and variables, such as Treatment-Emergent indicators, dictionary coding principles, and the importance of correct denominator derivation.

Metadata Mastery: Gain clarity on the naming conventions, dataset classifications, and traceability requirements essential for robust Define-XML generation.

My goal is to empower you with a deeper understanding of the OCCDS, fostering not just compliance with industry standards, but also efficiency and confidence in your programming endeavors. By demystifying the complexities of occurrence data analysis, I hope to equip you with the knowledge to produce high-quality, analysis-ready datasets that drive meaningful insights in clinical research.

I encourage you to use this guide alongside the official CDISC documentation, allowing these practical insights to complement the foundational knowledge.

Happy coding!