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Course module: 880005-M-6
880005-M-6
Health Analytics
Course info
Course module880005-M-6
Credits (ECTS)6
CategoryMA (Master)
Course typeCourse
Language of instructionEnglish
Offered byTilburg University; Tilburg School of Humanities and Digital Sciences; TSH: Department Cognitive Science and AI; TSH: Department Cognitive Science and AI;
Is part of
M Communication and Information Sciences
M Data Science and Society
Lecturer(s)
Lecturer
dr. E.M.J. Huis in 't Veld
Other course modules lecturer
Lecturer
Dr V. Powell
Other course modules lecturer
Academic year2019
Starting block
BLOK 1
Course mode
Full-time
Remarks-
Registration openfrom 20/08/2019 up to and including 18/10/2019
Aims

A. Knowledge and understanding

  • Reproduce basic concepts in Epidemiology
  • Efficiently read and interpret scientific articles

B. Applying knowledge and understanding

  • Develop, improve or extent on a data science solution in the healthcare sector, while keeping complex and/or extensive practical requirements that apply into account.

C. Making judgements

  • Approach your solution with curiosity, creativity, and in an analytical manner, incorporating the needs of patients, health care professionals, and other stakeholders.

D. Communication

  • Ability to translate the proposed solution to laymen stakeholders in the healthcare sector
Content

“Health analytics” is a rapidly growing domain of data science. In a world where data is boss, a sensor can solve any problem, and every organization seems eager to let AI decide important matters, it is important that you not only understand how to run analyses, but also how the human factor and unconscious biases may impact your data or decision. Lastly, in your future career you also need to be able to convey your message back to people in the healthcare sector who do not have the same background as you.

In this course, we will focus on key concepts in health analytics and epidemiology. We will discuss the application of these concepts in research and their impact public health and society.

For example, we will explore how data collection is often limited by observational biases. Observational biases typically influence the outcome of an analysis and thus results. Understanding of epidemiological concepts is therefore crucial for the interpretation of results, especially in context of large amounts of health data.

The course will put emphasis on theory, ideas, and their translation back to a business environment. I will attempt to invite practitioners working in the field of health analytics to discuss applications in different medical contexts.

Evaluation:
  1. Individual final exam: 60% of your grade
  2. Group assignment: 30% of your grade
  3. Presentations: 10% of your grade
Students are expected to participate actively in the practical sessions by means of working on assignments and presentations. Low participation rates will result in a lower grade for your group assignment and presentation.
 
Contact person
dr. E.M.J. Huis in 't Veld
Timetable information
Health Analytics
Written test opportunities
DescriptionTestBlockOpportunityDate
Written test opportunities (HIST)
DescriptionTestBlockOpportunityDate
Schriftelijk (60%) / Written (60%)EXAM_01BLOK 1115-10-2019
Schriftelijk (60%) / Written (60%)EXAM_01BLOK 1222-01-2020
Required materials
Literature
Is freely available on the web
Title:Concepts of Epidemiology (2002)
Author:Bhopal RS
Publisher:Oxford University Press;
Articles
Scientific Articles will be announced on blackboard
Recommended materials
-
Tests
Written (60%)

Final Result

Paper (30%)

Presentation (10%)

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