SITK20002E Exam in Register Based Epidemiology

Volume 2020/2021
Education

Master in Innovation in Health Care

For information about student work load during the course: please see the course desciption for "Course in Public Health Informatics".
  • Category
  • Hours
  • Exam
  • 5
  • Total
  • 5
Credit
4,5 ECTS
Type of assessment
Written examination, 5 hours under invigilation
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 Stata.
Exam registration requirements

Approved course attestation from the course "Course in Public Health Informatics

Aid
All aids allowed

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 acces to messenger, etc.).

 

Marking scale
7-point grading scale
Censorship form
No external censorship
Criteria for exam assesment

To get the highest grade, student should illutsrate:

  • explain the content and structure of the data in the selected Danish health registers
  • explain different disease classification systems used in Danish registers
  • explain the quality indicators and validty of register data and can explain the methods for evaluation of validty
  • explain the use of registers for both administrative and research purposes
  • explain how collected register data can be used as quality, process and result indicators
  • perform editing of raw register data in format suitable for statistical analyses in Stata
  • perform analyses of register data in Stata and calculate person-years, mortality rates, prevalence and incidence rates
  • explain application of register data in descriptive and analytical epidemiology
  • explain under which circumstances data can be used in informing the citizens 
  • explain the balance between detail and 'noise' in data (missclasification and statistical variation) i registers
  • explain the quality indicators and validty of register data and can explain the methods for evaluation of validty