Data
Official data in SubjectManager for the following academic year: 2024-2025
Course director
-
Pótó László
associate professor,
Institute of Bioanalysis -
Number of hours/semester
lectures: 12 hours
practices: 0 hours
seminars: 0 hours
total of: 12 hours
Subject data
- Code of subject: OAF-ODA-T
- 1 kredit
- General Medicine
- Optional modul
- autumn
OAA-MET-T finished , OAP-KN1-T parallel
Course headcount limitations
min. 5 – max. 24
Topic
There are two characteristic features at decision making in medicine (as well as in real life) which we have learned at our statistics course(s) earlier in the studies (at Biometrics in first year for example):
- (1) The different outcome options are characterized by (different) probabilities. And (even more importantly) - (2) in case of yes/no type decisions there is always a risk of error. Each of the decision options can be wrong. That is highly similar like in case of statistical hypothesis testing: Reject or accept a hull-hypothesis - with type-1 or type-2 error risk.
In case of a medical decision making (MDM) that can be critical feature of a decision making point!
There were created a tool-set to analyze and improve decision making along the past few decades. These can be applied to introduce some decision making aid (expert systems) to MDs daily decision making in the near future. The goal is to improve decision making quality and reduce the risk of serious errors at decision making.
Students can take a first insight to this exciting new field of medical sciences in this course.
Some of the main chapters are (from our suggested textbook):
1 Introduction - Tasks and problems to solve
2 Differential diagnosis concepts
The principles of hypothesis-driven differential diagnosis
3 Probability: quantifying uncertainty
Uncertainty and probability in medicine
4 Measuring the accuracy of diagnostic information
How to describe test results: abnormal and normal, positive and negative
Pitfalls of predictive value
5 Expected value decision making
Decision trees: structured representations for decision problems
6 Selection and interpretation of diagnostic tests, 243
Taking action when the consequences are uncertain: principles and definitions
Choosing between diagnostic tests, 259
7 Cost-effectiveness analysis and cost–benefit analysis
By the end of the course students will be able to analyze some complex real life (or medical) decision making situation.
And recognize differences between the main options at a given decision making situation. However, the lecture form of the course the output goal is to obtain some basic decision making skill over learning some fundamental new concepts of MDM.
Lectures
- 1. Introduction. MDM features from the point of view of statistics. - Pótó László
- 2. Refresh some basic features of statistical data evaluation and decision making - Pótó László
- 3. Differential diagnosis - How clinicians make a diagnosis? - Burzánné Pétervári Erika
- 4. The principles of hypothesis-driven differential diagnosis - Balaskó Márta
- 5. Probability - Pótó László
- 6. Quantifying uncertainty - Pótó László
- 7. Measuring the accuracy of diagnostic information - Pótó László
- 8. Pitfalls of predictive values - Pótó László
- 9. Decision trees - Pótó László
- 10. Selection and interpretation of diagnostic tests - Pótó László
- 11. Cost-effectiveness and cost-benefit analysis - Pótó László
- 12. Integration, Summary. - Balaskó Márta
Practices
Seminars
Reading material
Obligatory literature
Literature developed by the Department
Task exercises to some classes to complete and practice.
Notes
Recommended literature
Medical Decision Making; Sox H. C., Higgins M. C. Owens D.K., (Wiley, 2nd Ed. 2013)
Conditions for acceptance of the semester
Maximum 1 missed class. Submit the assignment by the deadline.
Mid-term exams
Submit a home assignment by the deadline.
Making up for missed classes
One replacement class will be available.
Exam topics/questions
The home assignment should be a case study of a complex decision making situation. It should contain several decision points.
The student should describe each of those decisions in details. And analyze the given decision point characteristics using the knowledge and features which they studied at the course.
It should be pointed out what are the critical points of each of those decisions. And selecting those which is / are the (one or more) critical decisions of the given case study.
Especially important to analyze those output options which are unacceptable - so that the given decision / outcome option and the potential consequences should be excluded.
Make your final conclusion concerning the examined case-study decision(s).