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May 21, 2024
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MI 17030 - Patient Safety and Quality Improvement2 lecture hours 4 lab hours 4 credits
Course Description
In this course, students will explore the current state of patient safety within the health care environment and opportunities for improvement through effective application of data analytics. Students will investigate the diverse data sources that may track quality and patient safety information, and create concrete problem statements based on statistical analysis of the data. Quality improvement methods such as Lean and Six Sigma will also be discussed and how their applications can improve health care delivery and administration. (prereq: MI 16010 , MI 16030 , MI 17020 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Identify areas of patient safety risk through workflow analysis, data analytics, and event reporting
- Demonstrate how statistics and analytics can be used to identify patterns and analyze quality and patient safety problems
- Based on analysis and data findings, propose an improvement for an existing patient safety and/or quality problem
- Evaluate ethical, legal, and social considerations when implementing patient safety and quality improvements
Prerequisites by Topic
- This course relies on student knowledge of workflow, management of data from disparate sources, and data analytics. As a result, this entire course requires mastery of topics from MI 16010 , MI 16030 , and MI 17020
Course Topics
Coordinator
Katie McCarthy
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