Course Description

Drawing upon previous course work and contemporary healthcare topics, this course will examine various aspects of data collection and analysis to address complex healthcare challenges with informed decision-making. Proper data collection techniques, critical evaluation of data sources, and data sufficiency are discussed. Best practices for developing visualizations, the process of cognition and translation of visual displays, as well as ethical standards are explored through assignments.

• Describe and explain the different characteristics of "meaningful" data,
• Compare and contrast the various logistical, legal, and ethical challenges related to data extraction and analysis of archival patient data sets,
• Analyze the process in which research studies are reviewed,
• Explore the special considerations needed in the design and implementation of research data storage,
• Compose basic code in the SAS programming language using the SAS Foundation application to perform statistical functions against a data set and evaluate the output,
• Understand the difference between the SAS Foundation and SAS Enterprise Guide applications and know the advantages/disadvantages of both products,
• Effectively use descriptive and inferential statistics, along with other advanced modeling techniques, to describe a data set, and
• Evaluate the different types of visualizations, and their use cases, using SAS Viya and SAS Visual Analytics suite.