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2019/2020  KAN-CIHCV1604U  Empirical Methods in Health Care Innovation

English Title
Empirical Methods in Health Care Innovation

Course information

Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Quarter
Start time of the course Second Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 50
Study board
Study Board for MSc in Business Administration and Innovation in Health Care
Course coordinator
  • Fane Naja Groes - Department of Economics (ECON)
Main academic disciplines
  • Innovation
  • Statistics and quantitative methods
  • Economics
Teaching methods
  • Face-to-face teaching
Last updated on 14-02-2019

Relevant links

Learning objectives
  • Understanding of the content and organization of health data
  • Lay out testable hypotheses
  • Outline an empirical strategy to test these hypotheses
  • Interpret the results of the quantitative/econometric analysis
  • Critically evaluate the econometric models for bias and causality
  • Demonstrate practical knowledge of analyzing data in a written project
Course prerequisites
This is a mandatory elective course for the MSc in Business Administration and Innovation in Health Care.

The empirical methods will rely on statistical inference, such that prior knowledge in this is an advantage.

To sign up send a 1-page motivational letter and a grade transcript to ihc@cbs.dk before the registration deadline for elective courses. You may find the registration deadlines on my.cbs.dk ( https:/​/​studentcbs.sharepoint.com/​graduate/​pages/​registration-for-electives.aspx )

Please also remember to sign up through the online registration.
Empirical Methods in Health Care Innovation:
Exam ECTS 7,5
Examination form Oral exam based on written product

In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and the individual oral performance.
Individual or group exam Individual oral exam based on written group product
Number of people in the group 4-5
Size of written product Max. 15 pages
Assignment type Project
Written product to be submitted on specified date and time.
20 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Grading scale 7-point grading scale
Examiner(s) Internal examiner and second internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
If a student is ill during the regular oral exam, he/she will be able to re-use the project at the make-up exam. If a student is ill during the writing of the project and did not contribute to the project, the make-up exam can be written individually or in groups (provided that other students are taking the make-up/re-exam). If the student did not pass the regular exam or did not show up at the oral exam, he/she must make a new revised project/business plan (confer advice from the examiner) and hand it in on a new deadline specified by the secretariat.
Course content, structure and pedagogical approach

This course focuses on the use of applied quantitative methods for the analysis of health and innovation in health care data.

Topics to be covered include: methods for the analysis of health data; evaluation of public policies to promote HCI; cross-country comparison of health care responsiveness; Examining the impact of education on HCI and the interaction between HCI and society. Lectures will cover the research question, methodological approach and its empirical implementation. Computer-based practical exercises will complement the lectures to enable participants to gain experience in the application of the methods. 

Throughout the course an emphasis will be placed on the empirical (microeconometric) methods used in addressing research questions. These include, the linear regression model, policy evaluation techniques including methods of matching, regression discontinuity, and regression based difference-in-differences. The empirical methods will rely on statistical inference, such that prior knowledge in this is an advantage.

Description of the teaching methods
Class (lectures and exercises) and group work
Feedback during the teaching period
Feedback will be given at the oral examination and during office hours. Students will meet in groups with professor to discuss written project.
Student workload
class 20 hours
lab session 10 hours
preparation of sessions 65 hours
preparation of lab sessions 25 hours
student presentation 40 hours
exam preparation and exam 65 hours
Expected literature

Mastering ’Metrics: The Path from Cause to Effect
by Joshua D. Angrist (Author), Jörn-Steffen Pischke (Author)

Introduction to Econometrics, 3rd Edition
James H. Stock, Harvard University
Mark W. Watson, Princeton University

Last updated on 14-02-2019