SFOK19005U  Precision medicine in public health – concepts, assumptions of causality and prediction, methods and societal challenges

Volume 2019/2020
Education

MSc in Public  Health - elective course

MSc in Global Health - elective course

MSc in Health Informatics - elective course

MSc in Health Science - elective course

MSc in Human Biology - elective course

Content

Precision medicine is an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person. This approach will allow doctors and researchers to predict more accurately which treatment and prevention strategies for a particular disease will work in which groups of people. It is in contrast to a one-size-fits-all approach, in which disease treatment and prevention strategies are developed for the average person, with less consideration for the differences between individuals.” ( https://ghr.nlm.nih.gov/primer/precisionmedicine/definition)

The aim of the course is to provide the course participants with an understanding of the concepts of precision medicine, and of the assumptions of causality and prediction, methods, and societal challenges when dealing with precision medicine in public health. The course attempts to balance the overwhelming promises in this area with underlying theories, and thus challenges in getting causal insight and in providing solid evidence for the health benefits both at the individual and societal level. It further focuses on teaching the participants how to analyse data from various designs within the area of precision medicine in public health. Finally, the course will focus on various societal challenges such methods may cause – both when the results are interpreted incorrectly as well as correctly.

Learning Outcome

After completing the course the student is expected to:

Knowledge

  • Understand the concepts of precision medicine in public health
  • Understand the underlying assumptions of causality versus prediction in relation to precision medicine
  • Know the major current initiatives in Denmark

 

Skills

  • Analyse sufficient cause interactions
  • Be able to analyse data from various designs within the area of precision medicine in public health
  • Implement an artificial neural network algorithm for disease prediction

 

Competencies

  • Design studies to assess the possible beneficial effects of precision medicine in the public health settings vis-a-vis conventional approaches.
  • Project societal implications of precision medicine solutions in public health
  • Critically engage in the debate of the role of precision medicine in public health
This course is targeted Public Health students with knowledge of epidemiology and statistics on MSc level. Students from other study programmes are welcomed to join the course, but should be aware knowledge of knowledge of epidemiology and statistics on MSc level is recommended in order to take part of this course.
Forelæsninger og øvelser

Oral feedback at dialogue-based lectures and exercises.

Credit
10 ECTS
Type of assessment
Written assignment
Oral defence under invigilation
Written assigment:
Students will in groups of max. 3 persons prepare a protocol for a research protocol (max. 3 pages of 2400 keynstrokes pr. page).

Oral exam:
The students will have 5 minutes each to present followed by 10 minutes discussion for the entire group.
Both the protocol, the student presentation and the discussion are included in the final individual grading.
Aid

All aids allowed when preparing the research protocol.

No aids allowed for the oral presentation and discussion.

Marking scale
7-point grading scale
Censorship form
No external censorship
More interal examiners.
Exam period

Please see the exam schedule

Re-exam

Please see the exam schedule

Criteria for exam assesment

To receive the grade 12, the student will be able to:

Knowledge

  • Understand the concepts of precision medicine in public health
  • Understand the underlying assumptions of causality versus prediction in relation to precision medicine
  • Know the major current initiatives in Denmark

 

Skills

  • Analyse sufficient cause interactions
  • Be able to analyse data from various designs within the area of precision medicine in public health
  • Implement an artificial neural network algorithm for disease prediction

 

Competencies

  • Design studies to assess the possible beneficial effects of precision medicine in the public health settings vis-a-vis conventional approaches.
  • Project societal implications of precision medicine solutions in public health
  • Critically engage in the debate of the role of precision medicine in public health
  • Category
  • Hours
  • Lectures
  • 30
  • Preparation
  • 180
  • Class Exercises
  • 25
  • Exam
  • 40
  • Total
  • 275