Clinical Epidemiology
[ CK040 ]

Research questions in clinical epidemiology originate from clinical practice. Caring for patients commonly triggers the research-minded clinician to question his/her knowledge and decisions. Questions may revolve around risk factors, prevention, diagnosis, prognosis and/or interventions leading to research studies. Results from clinical epidemiological research are used in patient management decisions. Understanding the research results, recognizing the limitations, and knowing how to apply them are essential to translate clinical research results to application in day-to-day clinical practice.

In this course, the principles and practice of clinical epidemiology and the application of the results to clinical decision making will be discussed, using examples from the literature and from ongoing studies. The course is divided into 3 parts:

1. Diagnosis
2. Prognosis
3. Interventions
We use blended learning: a combination of video’s, readings, assignments, question-and-answer sessions, interactive lectures, and workshops.

The assignments involve performing calculations. For the Diagnosis part we work with Excel. For the Prognosis part you will be using R code that has been written for you. To benefit maximally from this course we advise you to do the introduction to R - online course: install R and R Studio, learn basic R syntax, and learn basic R studio functionality. The DataCamp course Introduction to R is very helpful: https://www.datacamp.com/courses/free-introduction-to-r. The full DataCamp course will be available for course participants.

For students in our master programmes, the core concepts presented in this course will be assessed in the core competences exam that bundles the fall semester courses. This is in addition to the assessment during the course in the form of assignment(s). The core competences exam is only mandatory for students starting their programme in August 2021 or later, while the assignments during the course are mandatory for all participating students.

1. Understand the similarities and differences between diagnostic, prognostic and intervention research.

2. Appraise the design and analysis of clinical studies related to diagnosis, prognosis, and interventions.

3. Apply the methods to analyze the data from diagnostic and prognostic studies.

4. Understand the advantages and disadvantages related to different intervention designs.

5. Design a clinical study.

Clinical researchers, medical doctors, paramedical professionals, healthcare professionals. Students in epidemiology.

Assignment(s)

This course has a fulltime workload. Check MyTimetable for the planning of lectures.