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Overview
Overview - Health Decision Science
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How are public and global health decisions made? Which options deserve consideration and what criteria should we use to appraise them? Who should be involved in the process? How can we estimate the benefits, harms, costs, cost-effectiveness, feasibility, equity, and acceptability of alternative options? How can we package the evidence and uncertainty in a coherent and transparent way? What methods can be used to appraise the options? How should we communicate the recommendations? 

This module will equip you to support people in making optimal choices in a world with scarce resources, limited information, and lives and economies at stake. You will examine the process, evidence, uncertainties, ethics, and value judgements that underpin health decision-making.

Health Decision Science uses a structured and transparent process to engage stakeholders, frame problems, integrate evidence from multiple disciplines into an evidence framework (e.g. Evidence-to-Recommendation), support deliberation of options, and communicate recommendations. Decision-makers may range from individual patients through to national and global public health committees. Rather than being dominated by a single discipline, Health Decision Science integrates evidence and methods from multiple fields. The module will introduce you to a range of approaches to stakeholder engagement, disease modelling, health economic evaluation, health service planning, uncertainty analysis, deliberation, and communication. While the module does not provide expert-level training in any of the individual fields, it does provide an overview of the main approaches used within each field, and the situations in which they might be appropriate to use

Intended learning outcomes

Upon successful completion of the module, a student will be able to:

  1. Recognise and explain key elements of the health decision-making process.
  2. Distinguish different decision-making approaches and evaluate their strengths and weaknesses in particular health situations.
  3. Choose and justify decision-making approaches that are appropriate to particular health situations.
  4. Design simple decision-making approaches and apply them to real-world or hypothetical health situations.

Session Content

The lectures will cover the following topics: 

  • Introduction to health decision science.
  • Engaging stakeholders.
  • Disease modelling.
  • Health service planning.
  • Health economics.
  • Uncertainty.
  • Multi-criteria decision analysis.
  • Communication.

Mode of delivery

This module is delivered predominantly face-to-face. Where specific teaching methods (lectures, seminars, discussion groups) are noted in this module specification these will be delivered by predominantly face-to-face sessions. There will be a combination of live and interactive activities (synchronous learning) as well as self-directed study (asynchronous learning).

Assessment

The assessment for this module has been designed to measure student learning against the module's intended learning outcomes (ILOs) as listed above. Formative assessment methods may be used to measure students’ progress. The grade for summative assessment(s) only will go towards the overall award GPA. 

The assessment for this module will be online. 

Formal assessment of this module includes an 2000 word assessed assignment (100%) to be submitted at the end of the module. The assignment will be a written report. Students will be given the opportunity to ask questions about the assignment, through designated timetabled sessions and the appropriate forum on Moodle.

Credits

  • CATS: 15
  • ECTS: 7.5

Module specification

For full information regarding this module please see the module specification.

Entry requirements
Entry requirements - Health Decision Science
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This module is designed for students who are interested in decision-making in public and global health. An interest in quantitative analysis will be useful since many of the techniques in this field are quantitative

Students who undertake this module are expected to be familiar with Excel, and be capable of carrying out basic functions using Excel software (drawing box and arrow diagrams, inserting formulae into cells, producing simple charts and tables etc.). Some of the worked examples do contain some complex formulae and students will benefit from more advanced Excel knowledge if they wish to fully explore these. However, this is not a requirement of the course. Students should be reasonably numerate and feel confident in basic mathematics (primarily arithmetic) and simple logic. Students who are not confident in the use of Excel should attend the Computing Workshops provided in Term 1. Workshops on formulae, functions and formatting, and graphs and charts are particularly relevant. These can be found on Moodle, under “IT Training (MSc)”.

How to apply
How to apply - D2
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Applications for Term 2 D2 modules are now open. Please visit the list of individual modules for more upcoming study opportunities.

The application deadline for 26/27 entry will be 23:59 (UK time) on Sunday, 24 January 2027. We strongly advise that you apply early as courses may close earlier than the stated deadline if they become full.

Visa information

Please refer to the current visa requirements for short-term study.