SITK23001U Course in Register Based Epidemiology

Volume 2026/2027
Education

MSc in Health Informatics - compulsory

MSc. in Business Administration and Innovation in Health Care - mandatory in two tracks at CBS

Content

Denmark's national health registers, built on decades of systematic population data collection, provide exceptional opportunities for public health informatics and disease surveillance.

This course introduces key concepts such as disease classification, good data management, epidemiology, and survival analysis.

Students will explore major registers—including CPR, the Cause of Death Register, Cancer Registry, National Patient Register, and Diabetes Register—focusing on their purpose, development, data content, and validity.

Through hands-on exercises using real register data, students will work with key health indicators and learn to define health outcomes. By the end, they will understand how to apply Danish register data in public health research.

Learning Outcome

This course provides students with a foundation in public health informatics and epidemiological methods, with emphasis on major Danish national health registers and the diseases and causes of death they capture. Learning takes place through hands-on work with register data, statistical programming, and critical reading and presentation of contemporary research articles demonstrating how Danish registers are applied in studies of chronic disease prevention, cancer screening, environmental epidemiology, disease trends, and treatment effects.

Knowledge

Students will be able to:

  • describe the content, structure, and purpose of key Danish health registers

  • explain the disease classification systems used in Danish registers

  • understand and explain epidemiological measures such as prevalence, incidence, relative risk, and odds ratios

  • describe the administrative and research uses of health registers

  • explain quality indicators and methods for assessing the validity of register data

  • explain how register data are applied in public health and epidemiological research

Skills

Students will be able to:

  • prepare and edit register data for statistical analysis

  • conduct analyzes using statistical software, including calculating person-years, mortality, prevalence, and incidence

  • correctly interpret and explain statistical output

  • evaluate whether analyzes are performed correctly and identify potential errors

Competencies

Students will be able to:

  • explain how register-based data serve as quality indicators

  • describe the use of register data in descriptive and analytical epidemiology

  • understand when register data can be used to inform the public

  • analyze registry data independently

  • assess the balance between detail and noise (misclassification and statistical variation) in register data

  • identify biases and limitations in epidemiological studies using register data

  • interpret and communicate findings from epidemiological studies using Danish register data

The course draws on a combination of structured teaching materials designed to support both theoretical understanding and practical skills. Lectures and accompanying slide presentations introduce core concepts in public health informatics, epidemiology, and the structure of Danish health registers. Hands-on coding sessions form a central component of the course, where students work directly with real register data using statistical software to perform data management and analysis. Selected peer-reviewed journal articles are used to illustrate state-of-the-art applications of Danish register data in epidemiological research and to strengthen students' abilities to critically evaluate scientific studies. Together, these materials provide an integrated learning experience that builds both conceptual knowledge and analytical competence.

The course employs a combination of interactive and practice-oriented teaching methods to support both theoretical understanding and applied skills. These methods include:

- Lectures, introducing core concepts in public health informatics, epidemiology, and register-based research

- Hands-on exercises, where students work directly with register data and statistical software

- Group research activities, enabling collaborative problem-solving and deeper engagement with real-world data challenges

- Journal club sessions, where students read, present, and critically evaluate scientific articles

- Coding cafés, providing guided support and peer learning for data management and analysis tasks

- Seminar series, featuring in-depth discussions, guest speakers, or thematic explorations of current research topics

Together, these methods create a varied learning environment that integrates conceptual knowledge with analytical practice.
Be advised that you will have to pass the exam (SITK20002E) connected to this course to receive the ECTS.
  • Category
  • Hours
  • Lectures
  • 28
  • Preparation
  • 142,5
  • Exercises
  • 27
  • Seminar
  • 9
  • Exam
  • 5
  • Total
  • 211,5
Oral
Collective
Continuous feedback during the course of the semester
Credit
7,5 ECTS
Type of assessment
On-site written exam, 5 hours under invigilation
Type of assessment details
Written eksam consists of a number of questions which can be answered by using data sets provided at the time of exam. Questions are answered during the 5 hour exam by programminug in statistical software.
Aid
All aids allowed except Generative AI and internet access

All help/material - including notes uploaded to Digital Notes (you will find a link for this feature in connection with your test in Digital Exam) is allowed, but not devices that allow for external communication (mobile phones, internet access to messenger, artificial intelligence, etc.).

Find more information about written on-site exams in the exam rooms, incl. information about standard programs on the exam PCs at KUnet

Marking scale
7-point grading scale
Censorship form
No external censorship
Internal examination
Re-exam

In case of 10 or fewer students are registered for the re-exam:

Type of assessment: Oral examination
Duration: 30 minutes
Preparation time: 90 minutes

Preparation description:
Students will be provided with datasets and a computer equipped with the necessary statistical software. They will have 90 minutes to review the material and prepare for the oral examination. During the preparation period, students may use permitted aid materials. Personal computers are not allowed.

Permitted aids:

  • Course materials (slides, notes, and analysis code)

  • All aid materials must be submitted to the course leader 48 hours before the exam

  • Internet access and artificial intelligence tools are not permitted

Criteria for exam assesment

To achieve the maximum grade of 12, the student shall be abel to:

Knowledge

Students must be able to:

  • explain the content, structure, and purpose of selected Danish health registers

  • describe disease classification systems used in Danish registers

  • explain quality indicators and the validity of register data, including methods for evaluating validity

  • discuss administrative and research uses of register data

  • explain how register data function as quality, process, and outcome indicators

  • define and explain hypotheses, exposure measures, and outcome measures in epidemiological research

  • describe the application of register data in descriptive and analytical epidemiology

  • explain under which conditions register-based data may be used to inform citizens

  • identify potential confounders relevant to register-based analyses

Skills

Students must be able to:

  • prepare and edit raw register data in formats suitable for statistical analysis

  • perform statistical analyses of register data, including calculating person-years, mortality rates, prevalence, and incidence

  • construct statistical tables that clearly summarize analytical results

  • interpret analytical output correctly and explain its epidemiological meaning

  • produce a coherent analytical summary that addresses findings, potential bias, and limitations

Competences

Students must be able to:

  • assess and discuss sources of bias in epidemiological studies using register data

  • evaluate the appropriateness and validity of analytical approaches in register-based research

  • integrate knowledge of data structures, epidemiological concepts, and analytical methods to draw sound, well-reasoned conclusions from register data