315.709.81
Health Sciences Informatics, Knowledge Engineering and Decision Support
Location
Internet
Term
4th Term
Department
Health Policy and Management
Credit(s)
3
Academic Year
2021 - 2022
Instruction Method
Asynchronous Online
Auditors Allowed
No
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
Resources
Prerequisite
Introduction to on-line learning
Provides a framework for understanding decision support in the workflow of the health sciences. Focuses on the types of support needed by different decision makers, and the features associated with those types of support. Discusses a variety of decision support algorithms, examining advantages and disadvantages of each, with a strong emphasis on decision analysis as the basic science of decision making. Students are expected to demonstrate facility with one algorithm in particular through the creation of a working prototype, and to articulate the evidence for efficacy and effectiveness of various types of decision support in health sciences and practice, in general.
Learning Objectives
Upon successfully completing this course, students will be able to:
- Discuss motivations and needs for real-time decision support
- Identify gaps in a decision support plan
- Provide a high-level design for a decision support intervention and implementation
- Identify opportunities for unintended consequences of decision support
- Discuss strengths and weaknesses of different designs (knowledge-centric vs application-centric) for decision support
- Discuss strengths and weaknesses of different representations for decision support: Tables, Templates, Rules, Data Dictionaries, Taxonomies, Semantic Networks, and Ontologies
- Match candidate decision support representations to a decision support problem
- Match candidate knowledge acquisition methods to a decision support problem
- Classify decision support uses in multiple contexts
This is the same course as SOM 600.901