1  Introduction

Clinical Data Management, Written and assembled by: Written and assembled by: Sarah Teichman, Kate Isaac, & Carrie Wright, Contributors/Reviewers: Christopher Battiston, David Hanauer, Guilherme Del Fiol, Harry Hochheiser, Jennifer Kelleher, Abby Robbertz, Meghan McGrady, Megan Othus, and Michael Watkins

1.1 Motivation

This course is intended for researchers (including postdocs and students) with limited to intermediate experience with informatics research. The conceptual material will also be useful for those in management roles who are collecting data and using informatics pipelines.

This course is intended to provide an overview of the different kinds of data commonly used in clinical research, the questions that can typically be asked with such data, as well as guidance for how to manage this data.

For individuals who: Want to learn about the variety of different types of clinical data and how it may be collected or acquired. Want a basic overview of what the clinical data represent and what questions can be asked.Need to know the basics of how to manage clinical data properly

1.2 Topics Covered

Concepts discussed in Clinical Data course: What does your clinical data type represent? What data distortions may impact your work? How do you handle the clinical data securely? What types of analysis questions can one ask when it comes to different kinds of clinical data? Find tools to help you manage your data

1.3 Curriculum

The course will cover key underlying principles and concepts in ethical data handling.

Overall Course Learning Objectives. This course will demonstrate how to: List common sources and types of clinical data, Explain what makes clinical data unique, Describe clinical study designs and considerations, Understand the questions that can be asked with different types of clinical data and other data uses, Recognize major data handling tools and methods for managing clinical data securely