Foundations of Decision Analytic Modelling for Health Technology Assessment (Online) MED5376
- Academic Session: 2021-22
- School: School of Health and Wellbeing
- Credits: 10
- Level: Level 5 (SCQF level 11)
- Typically Offered: Semester 2
- Available to Visiting Students: Yes
- Available to Erasmus Students: Yes
- Taught Wholly by Distance Learning: Yes
This course will teach the methods of decision analytic modelling that provides a coherent framework to inform decision making under uncertainty.
5 week online course comprising 5 lectures and 5 accompanying practical exercises. The lectures will be 45 mins/1 hr in duration and the exercise associated with each lecture will take a notional 2 hours for the student to complete. Each week the academic lead will contribute to and answer questions on a discussion board.
Requirements of Entry
MED5373 - Decision Analytic Modelling for HTA
Written Assignment/Coursework - Students to develop a conceptual framework for a decision model and then implement the model in a spreadsheet package. The written report should detail the development of the conceptual model and the parameterisation of that model (1000 words - 50%). The spreadsheet will also be submitted (50%).
This course aims to equip students with the necessary skills so they can design and conduct decision analytic modelling.
Intended Learning Outcomes of Course
By the end of this course students will be able to:
■ Critically assess the role of modelling and how models inform health care decision making
■ Conceptualise and design a decision making problem
■ Create, populate and evaluate decision trees for health care decision making problems
■ Critically analyse diagnostic information using the decision tree framework and evaluate the expected value of perfect diagnostic information
■ Create, populate and evaluate Markov models for health care decision making problems
Minimum Requirement for Award of Credits
Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.