Course Applying clinical epidemiological methods and Danish databases to study chronic disease

ECTS: 2.5

Course leader: Reimar W. Thomsen

Language: English

Graduate school: Faculty of Health

Graduate program: ClinFO

Course fee: 3,000.00 DKK

Status: Course is open for application

Semester: Fall 2023

Application deadline: 14/08/2023

Start date: 11/09/2023

Administrator: Lena Melchior Villadsen

Criteria for participation

Participants must have some knowledge of statistics and bring their own computer with Stata or R installed.

The course C296/04 Applying clinical epidemiological methods and Danish databases to study chronic disease is being offered by the Graduate School of Health, Aarhus University, 2023.

Criteria for participation: : University degree in medicine, dentistry, nursing, or master’s degree in other fields and/or postgraduate research fellows (PhD students and research-year medical students). Participants must bring their own computer with Stata or R installed to the course.

Recommended knowledge for participation: Basics of epidemiology or clinical epidemiology (introductory level). Knowledge related to the chronic disease topic of interest; For example, oncology/cancer research knowledge for those working in cancer; cardiometabolic disease knowledge for those working in this field, etc. Some knowledge of statistics and a computer with Stata or R.     

Aim: To provide students with an overview on how to take a research idea through to implementing, analysing, and interpreting an epidemiologic study, using Denmark’s unique network of medical and population-based registries. Each concept will be introduced in a lecture. Through a combination of exercises and computer labs, students will be provided with guidance on implementing, analysing and interpreting studies using data on important chronic diseases from the Danish databases and registries. Students are not required to complete an exam at the end of the course.

This course is relevant to those working with clinical and epidemiological studies of any chronic disease.  There will be an introduction to the basic and advanced observational methodology toolbox within clinical outcome studies. We will present methods applied to the study of chronic diseases including cancer, cardiovascular disease, respiratory disease, diabetes/obesity, kidney disease, and bone disease, among others. Methods will include traditional epidemiological study designs for a single chronic disease, but also novel approaches to study treatment, multi morbidity, and chronic disease in a life-course perspective.

Learning outcomes: 

  • The course includes lectures, exercises and computer labs on the following:
  • Identify and design a clinical epidemiologic research study using the Danish databases and registries – comparing and contrasting study designs in order to suitably address a research question
  • Identifying and ascertaining data from the Danish databases and registries
  • Assessing study validity and implementing validity checks
  • Data analysis including data cleaning and implementing survival analysis using Stata
  • Evaluating study findings, interpreting and reporting study findings

Workload: The full workload of the course is expected to be 25 hours.


  • Monday: How can we address a research question?
  • Tuesday: What data can we use?
  • Wednesday: Can we trust the data?
  • Thursday: Evaluating wether an observed association suggests a causal association: Can we trust the analysis?
  • Friday: How can we interpret and present our findings?

Instructors: Deirdre Cronin Fenton, PhD, Mette Nørgaard, MD, PhD, Christian F. Christiansen, MD, PhD, Reimar W. Thomsen, MD, PhD

Venue: Aarhus University, Aarhus

Participation in the course is without cost for:

  • PhD students, Health Research Year students and Health Research Honours Programme students from Aarhus University
  • PhD students enrolled at partner universities of the Nordoc collaboration
  • PhD students from other institutions in the open market agreement for PhD courses

Course dates:

  • 11 September 2023 08:00 - 16:00
  • 12 September 2023 08:00 - 16:00
  • 13 September 2023 08:00 - 16:00
  • 14 September 2023 08:00 - 16:00
  • 15 September 2023 08:00 - 16:00