You are here

F7ADIMDM - Medial Desicion Making

Code Completion Credits Range Language
F7ADIMDM ZK 20P+8C English
Lecturer:
Ilya Ivlev (guarantor)
Tutor:
Ilya Ivlev (guarantor)
Supervisor:
Department of Biomedical Technology
Synopsis:

This course will provide an introduction to the core of medical decision making and decision analysis. Students will learn the concepts of decision-analytic models. Also, this course will teach how to build and apply methods of decision tree analysis and Markov modeling to simulate outcomes of medical interventions. Students will learn how to conduct a medical decision analysis with sensitivity analyses and translate the results into medical decision making and clinical guidelines.

Requirements:

The subjects are concluded by an oral examination preceded by a written preparation (written test and ECG quiz). The student must elaborate a paper on a given topic together with the exam in case of the controlled self-study.

The study is performed in the form of controlled self-study with regular consultations and obligatory participation in laboratory exercises.

Syllabus of lectures:

Osnova přednášek:

1. Introduction: Decision making in healthcare

2. Decision making under uncertainty

3. Diagnostic information and methods for interpretation

4. Modeling the choice.

5. Introduction to TreeAge modeling software

6. Valuing outcomes; their attributes and approaches to the analyses

7. Medical tests and expected value

8. Markov Models and recurring events

9. Medical decision making under constrained resources: cost-effectiveness and comparative analyses

10 Evidence synthesis: methods and interpretation

Syllabus of tutorials:

Osnova cvičení (bloková forma výuky po 4 vyučovacích hodinách):

1. 2x2 tables and introduction to the use of TreeAge software for outcome analysis

2. Expected value decision analysis, Markov models, and cost-effective analysis

Study Objective:

This course will provide an introduction to the core of medical decision making and decision analysis. Students will learn the concepts of decision-analytic models. Also, this course will teach how to build and apply methods of decision tree analysis and Markov modeling to simulate outcomes of medical interventions. Students will learn how to conduct a medical decision analysis with sensitivity analyses and translate the results into medical decision making and clinical guidelines.

Study materials:

Povinná:

[1] Hunink, M., Weinstein, M., Wittenberg, E., Drummond, M., Pliskin, J., Wong, J., & Glasziou, P. Decision Making in Health and Medicine: Integrating Evidence and Values. Cambridge: Cambridge University Press. 2014 doi:10.1017/CBO9781139506779

[2] Sox, H., Higgins, Michael C., & Owens, Douglas K. Medical decision making (2nd ed.). Chichester, West Sussex, UK: Hoboken, New Jersey: John Wiley & Sons. 2013.

Doporučená:

[1] Diefenbach, M., Miller-Halegoua, Suzanne, & Bowen, Deborah J. Handbook of Health Decision Science. New York, NY: Springer New York: Imprint: Springer. 2016.

Note:
The course is a part of the following study plans:
Downloads: