MIS544

042785

With the increasing adoption of electronic health record systems, new forms of data are becoming available that can be used to measure healthcare delivery and improve patient outcomes. This healthcare analytics course provides the working professional in a broad range of roles (clinical and non-clinical) with the foundational knowledge of analytics, covering key components of the data analysis process, including strategies for effectively capturing and communicating information gleaned from data analytics efforts. The overarching goal is to equip participants to contribute to and/or conduct data analytics projects effectively. In this course, we will explore the variety of clinical data collected during the delivery of healthcare. You will learn to construct analysis-ready datasets and apply computational procedures to answer clinical questions. This course will further introduce the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. We will explore machine learning approaches, medical use cases, metrics unique to healthcare, as well as best practices for designing, building, and evaluating machine learning applications in healthcare. The course will empower those with non-technical backgrounds in healthcare, health policy, pharmaceutical development, as well as data science with the knowledge to critically evaluate and use these technologies.

GRD - Regular Grades A, B, C, D, E

Graduate