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PhD course

Equity and fairness in health - an applied approach to ethics

Course description

Language of instruction

English

Course content

The teaching is based on residential teaching at University of Bergen.

The first two days are largely theoretical, and consists of a mixture of lectures and group work/discussions 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 remaining days are combinations of theory and practical, and students will work through exercises on their own laptops on a "learning by doing" principle. Each day will be organized around a number of assignments that must be completed individually. The softwares Microsoft Excel, ADEPT, and Stata will be used throughout the module.

To get credits for PhD course, the student must complete and pass the one week take home exam.

Learning outcomes

On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

  • Know the different key concepts and theories for distributional fairness
  • Know key global policy responses to health challenges, and understand key frameworks of health care priority setting in practice in selected low-, middle- and high income countries
  • Understand the difference between data on average population coverage for a health service, and data on distribution of coverage disaggregated according to key determinants
  • Understand the difference between data on average population coverage for a health service, and data on distribution of coverage disaggregated according to key determinants

Skills

  • Able to explain and justify distribution of scarce resources according to utilitarian, egalitarian and prioritarian principles, and how they apply to health
  • Able to describe milestones in global health priority setting, as articulated in the Alma Ata declaration, MDGs and SDGs.
  • Able to describe health care priority setting in WHO, UK, Norway, Thailand, Mexico, Ethiopia and Tanzania
  • Theoretical essay
  • Know how to explore and describe DHS data and and present standard descriptive statistics on level and distribution
  • Describe data set
  • Know how to analyze DHS data using Stata and DASP to estimate inequity in coverage using common inequality measures such as concentration index and Gini and to present results graphically using concentration curves

General competence

  • Understand key elements of distributive theories.
  • Understand longitudinal global epidemiological and demographic trends and local adaptations to health care priority setting
  • Able to describe a data set in terms of level and distribution of the variable of interest, and link it to relevant theoretical frameworks
  • Able to analyze a data set in terms of average level and distribution of the variable of interest, and discuss results in the context of recent research contributions. link it to relevant theoretical frameworks

Study period

Spring

Specific terms

Pre-requirements

Basic skills in Excel software. Good working knowledge of English (TOEFL score of at least 550 points paper-based or 213 points computer-based, or an equivalent approved test).

Recommended previous knowledge

Basic skills in Stata software

Compulsory Requirements

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

Form of assessment

Students will be graded based on their performance of the three mandatory assignments (20% each), and participation in class (20%) + take home exam (20%).

Grading Scale: A-F

Course overlap

ELMED310 3 credits

Who may participate

Economists, other social scientists, medical doctors, psychologists, nurses, dentists and others with training at the bachelor level or higher in a relevant subject at a recognized institution can be admitted to the MSc level course.

Addtional information

Supplementary course information

Objectives:
The participants will learn how to evaluate equity in access to health services and fairness in distributions of health outcomes, and to integrate tools for equity concerns and health maximization.

Content:
Part 1: Will cover theoretical concepts of equity and fairness as well as health maximization, and how they are applied in global and national health care priority setting.

Part 2: Will cover hands-on exercises in equity analysis, starting with assignments in excel, moving to ADEPT (Software platform for equity analysis developed by the World Bank), and Stata with DASP (Distributive Analysis Stata Package).

Part 3: Take home exam, essay with data analysis and discussion.

Contact

Course Administrator:

Studie@igs.uib.no

Tlf 55 58 6100

Academic responsibility

Prof Ole Frithjof Norheim

Exam information

Study period

Spring