# Preface

This is a book about the Observational Health Data Sciences and Informatics (OHDSI) collaborative. The OHDSI community wrote the book to serve as a central knowledge repository for all things OHDSI. The Book is a living document, community-maintained through open-source development tools, and evolves continuously. The online version, available for free at http://book.ohdsi.org, always represents the latest version. A physical copy of the book is available from Amazon at cost price.

## Goals of this Book

This book aims to be a central knowledge repository for OHDSI, and it focuses on describing the OHDSI community, OHDSI data standards, and OHDSI tools. It is intended for both OHDSI newcomers and veterans alike, and aims to be practical, providing the necessary theory and subsequent instructions on how to do things. After reading this book you will understand what OHDSI is, and how you can join the journey. You will learn what the common data model and standard vocabularies are, and how they can be used to standardize an observational healthcare database. You will learn the three main use cases for these data: characterization, population-level estimation, and patient-level prediction. You will read about OHDSI’s open-source tools that support all three activities and how to use those tools. Chapters on data quality, clinical validity, software validity, and method validity will explain how to establish the quality of the generated evidence. Lastly, you will learn how to use the OHDSI tools to execute these studies in a distributed research network.

## Structure of the Book

This book is organized in five major sections:

1. The OHDSI Community
2. Uniform data representation
3. Data Analytics
4. Evidence Quality
5. OHDSI Studies

Each section has multiple chapters, and, as appropriate, each chapter follows the sequence: Introduction, Theory, Practice, Summary, and Exercises.

## Contributors

Each chapter lists one or more chapter leads. These are the people who lead the writing of the chapter. However, there are many others that have contributed to the book, whom we would like to acknowledge here:

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 Hamed Abedtash Mustafa Ascha Mark Beno Clair Blacketer David Blatt Brian Christian Gino Cloft Frank DeFalco Sara Dempster Jon Duke Sergio Eslava Clark Evans Thomas Falconer George Hripcsak Vojtech Huser Mark Khayter Greg Klebanov Kristin Kostka Bob Lanese Wanda Lattimore Chun Li David Madigan Sindhoosha Malay Harry Menegay Akihiko Nishimura Ellen Palmer Nirav Patil Jose Posada Nicole Pratt Dani Prieto-Alhambra Christian Reich Jenna Reps Peter Rijnbeek Patrick Ryan Craig Sachson Izzy Saridakis Paola Saroufim Martijn Schuemie Sarah Seager Anthony Sena Sunah Song Matt Spotnitz Marc Suchard Joel Swerdel Devin Tian Don Torok Kees van Bochove Mui Van Zandt Erica Voss Kristin Waite Mike Warfe Jamie Weaver James Wiggins Andrew Williams Seng Chan You

## Software Versions

A large part of this book is about the open-source software of OHDSI, and this software will evolve over time. Although the developers do their best to offer a consistent and stable experience to the users, it is inevitable that over time improvements to the software will render some of the instructions in this book outdated. The community will update the online version of the book to reflect those changes, and new editions of the hard copy will be released over time. For reference, these are the version numbers of the software used in this version of the book:

• ACHILLES: version 1.6.6
• ATLAS: version 2.7.3
• EUNOMIA: version 1.0.0
• Methods Library packages: see Table 0.1
Table 0.1: Versions of packages in the Methods Library used in this book.
Package Version
CaseControl 1.6.0
CaseCrossover 1.1.0
CohortMethod 3.1.0
Cyclops 2.0.2
DatabaseConnector 2.4.1
EmpiricalCalibration 2.0.0
EvidenceSynthesis 0.0.4
FeatureExtraction 2.2.4
MethodEvaluation 1.1.0
ParallelLogger 1.1.0
PatientLevelPrediction 3.0.6
SelfControlledCaseSeries 1.4.0
SelfControlledCohort 1.5.0
SqlRender 1.6.2