DECISION MAKING IN HEALTH CARE

Prerequisites & course information

Requisites: ( STAT/MATH 309 , 409, 431 , STAT 311 , MATH 331 ) and ( I SY E 323 or E C E/COMP SCI/I SY E 524 ), graduate/professional standing, or member of Engineering Guest Students Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2025 Learning Outcomes: 1. Explain how decision sciences are used in the health-care industry Audience: Both Grad & Undergrad 2. Describe concepts related to medical decision making and cost-effectiveness analysis Audience: Both Grad & Undergrad 3. Apply technical skills in decision analysis including the creation and evaluation of decision trees, the use of sensitivity analysis, and the use of Markov processes and Monte Carlo simulation Audience: Both Grad & Undergrad 4. Incorporate specific patient preferences into medical decision models through the use of utility analysis Audience: Both Grad & Undergrad 5. Identify and apply an advanced decision analytical modeling framework to solve medical decision making problems Audience: Graduate Learning Outcomes: 1. Explain how decision sciences are used in the health-care industry Audience: Both Grad & Undergrad 2. Describe concepts related to medical decision making and cost-effectiveness analysis Audience: Both Grad & Undergrad 3. Apply technical skills in decision analysis including the creation and evaluation of decision trees, the use of sensitivity analysis, and the use of Markov processes and Monte Carlo simulation Audience: Both Grad & Undergrad 4. Incorporate specific patient preferences into medical decision models through the use of utility analysis Audience: Both Grad & Undergrad 5. Identify and apply an advanced decision analytical modeling framework to solve medical decision making problems Audience: Graduate