Course Introduction to register-based research

ECTS: 3.5

Course leader: Oleguer Plana-Ripoll

Language: English

Graduate school: Faculty of Health

Graduate program: ClinFO

Course fee: 4,200.00 DKK

Status: Course is open for application

Semester: Fall 2023

Application deadline: 15/10/2023

Start date: 13/11/2023

Administrator: Thilde Møller Risgaard

The course C285/05 Introduction to register-based research is being offered by the Graduate School of Health, Aarhus University, fall 2023.

Criteria for participation: University degree in medicine, public health, dentistry, nursing, or master’s degree in other fields and/or postgraduate research fellows (PhD students and research-year medical students).

Aim: Participants will learn about key Danish national registers and how to use them for research purposes, through a combination of lectures, short research presentations with examples, discussions and exercises. This course will provide participants the necessary knowledge and skills to start their own research project based on national registers and cohorts.

Learning outcomes: 

  • Describe commonly used Danish health registers and how they can be used in research
  • Identify different epidemiological designs used to investigate register data
  • Discuss strengths and limitations of register data
  • Describe how other sources of data, such as genetic data, cohort data and survey data can complement data in the registers
  • Perform simple data management tasks using artificial register data
  • Plan their own research using registers or to critically read publications from register-based studies

Workload: The full workload of the course is expected to be 53 hours

There will be a series of presentations by researchers from the National Centre for Register-Based Research (Aarhus University) and the Department of Clinical Epidemiology (Aarhus University and Aarhus University Hospital), who will use their expertise to introduce the Danish registers and register-based studies. The course will consist of a broad range of topics relevant to carrying out register-based research, including strengths and weaknesses of the registers, different possibilities for study designs, data security and good practices. In addition, there will be special focus on specific types of data, for example related to studying diseases (e.g. psychiatric disorders, using hospitalization or prescription data), socio-economic characteristics, environment (e.g. air and water quality or green space), etc. Furthermore, other sources of data which can be linked with the registers will be discussed (for example iPSYCH genetic data, BERTHA environmental big data, data from surveys and cohorts). Exercises will put theory from the course into practice, in order to provide the participants with the necessary knowledge and skills to carry out their own research projects. The exercises will cover reading register-based studies, describing registers and register-based studies, and managing data from multiple registers. Finally, there will be discussions on potential limitations or different approaches to answer specific research questions, which can include specific issues related to participants’ own projects.

Recommended knowledge for participation: There are no prerequisite courses, but participants will require a basic understanding of statistics and epidemiology (bachelor level). Support for exercises will be provided for Stata or R, so knowledge of basic data management functions in one of these two statistical programs is recommended.

Instructors: Staff from the National Centre for Register-based Research and the Department of Clinical Epidemiology

Venue: National Centre for Register-based Research, Building R (2641) room 130, Fuglesangs Allé 26, 8210 Aarhus V

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:

  • 13 November 2023 09:00 - 15:30
  • 14 November 2023 09:00 - 15:30
  • 15 November 2023 09:00 - 15:30
  • 16 November 2023 09:00 - 15:30
  • 17 November 2023 09:00 - 15:30