Quantitative Methods for Studying Equity and Poverty impact in Health (CISMAC 900A-3)

Course content:
The participants will learn about equity analysis, financial risk protection, poverty impact, and how to build on cost-effectiveness analysis to analyze distributional equity objectives, such as giving priority to the severely ill, reducing inequality in health, and promoting equal access to health services. We will use a mixture of lectures, group work/discussions and hands-on excercises on the main topics described above. Students are required to participate in group work on assigned topics. This includes daily student active teaching exercises, with alternating group compositions and presentation of results for the class.

The lecturers will be:

Kjell Arne Johansson, Tarun Shankar Choudhary, Ole F Norheim (Tentative), Halvor Sommerfelt (Tentative)

Learning outcomes:
After the course, the student should have acquired knowledge about:

• Principles and methods of equity impact analysis,
• Study designs in extended cost-effectiveness analyses, and how equity and household finance can be measured in randomised controlled trials
• Selection of appropriate questionnaires and measures for assessing equity and household financial outcomes
• Critical issues in planning and conducting a successful equity and household finance impact RCT

After the course, the student should be able to:

• Analyze epidemiological data in Stata using the Distributive Analysis Stata Package (DASP) for 2-7 below
• Manage stratified epidemiological data, and conduct visualisation and descriptive analysis of distribution
• Evaluate baseline distribution of health and impact of health interventions on this using indeces of inequality
• Evaluate patient costs and financial risk (catastrophic health expenditure, poverty)
• Design and analyse equity randomised controlled trials (RCTs that assess impact of health interventions on distribution and financial risk protection).

Teaching and Learning methods:
This is a full digital course with lectures and active participation in discussions and group work taking place in Teams or Zoom (or similar). There will be basic readings, hands on analyses on computers, plenary presentations and discussion. Participants need a laptop with Stata and R preinstalled.

Form of assignment and assesment
There are three mandatory assignments, with a combination of individual work and group work. In addition, group work in class, which requires attendance, will be graded.

Students will be graded based on their performance on the three mandatory assignments (25% each), and participation in class (25%).

Reading List
Reading List will be available in CANVAS (mitt.uib)

Required Previous Knowledge
Basic skills in quantitative data analysis. Good working knowledge of English (TOEFL score of at least 550 points paper-based or 213 points computer-based, or an equivalent approved test). Economists, other social scientists, health policy makers, medical doctors, ethicists, psychologists, nurses, dentists and others with training at the master level or higher in a relevant subject at a recognized institution can be admitted to the PhD level course.

Recommended previous knowledge
Basic skills in Stata/R software and basic understanding of distributive justice.

Registration
PhD students at UiB will be given priority, but the course is open for students and researchers from other international academic institutions outside of UiB as well.

There is a maximum capacity of 30 students. Registration will close on the 5th of November or when course is full.

To register apply here