杏吧论坛

Dr Irene Papanicolas COW.3.04

This course is compulsory on the MSc in Health Data Science. This course is available as an outside option to students on other programmes where regulations permit.

Students will not be permitted to take both HP402 Measuring Health Systems and Methods and Data for Health Systems Performance Assessment courses. 

This course aims to present a framework to discuss the opportunities adn challenges with performance measurement in health care, examine the various dimensions and levels of health system performance, identify and apply the measurement instruments and analytic tools needed, and examine the implications of these issues for policy makers and regulators. Lectures generally focus on measuring health system performance in high-income countries but draw on the experience of other countries where relevant. 

After taking this course student will be able to:

1. understand the complexity of different health systems

2. appreciate the challenges, approached and opportunities in performance measurement in four dimensions; population health, patient outcomes, equity, quality adn appropriateness of care, and productivity

3. be familiar with the construction of key indicators used by health systems and providers to measure population health, patient outcomes, equity, quality of care and productivity

4. apply different methodologies used for risk adjustment, to develop composite measures, and to measure attribution and causality

5. identify key issues relevant to policy makers relating to policy evaluation using measures of performance 

15 hours of lectures and 18 hours of seminars in the LT.

Students will be expected to produce 1 project in the LT.

1x 1500 word group research project. Student will be able to submit a short 1500-word individual report based on analysis conducted in class during one of the seminars and in collaboration with other students. This will be graded and feedback given to students to inform their summative submission. This allows students to learn from their peers and work on data analysis in a group. 

• Papanicolas I, Smith P (Eds) Health System Performance Comparison: An Agenda for Policy, Information and Research. Maidenhead: Open University Press, 2013;
• P Smith, E Mossialos, I Papanicolas S. Leatherman (Eds), Performance measurement for health system improvement: experiences, challenges and prospects. Cambridge University Press, 2010.
• Institute of Medicine, Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC, National Academies Press, 2001;
• OECD, Measuring up: improving health system performance in OECD countries. Paris: OECD, 2002. World Health Organization (WHO), (2000)
• The world health report 2000:Health systems: Improving performance, Geneva: WHO Publications

Project (100%, 3500 words) in the ST.

Students will be asked to pick one research project among two. The project will involve data analysis using specialist software used in class seminars. 

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.