MSc Health Analysis, Policy & Management

This module will provide the crucial opportunity for the students to apply their broad knowledge of tools and techniques from other health analysis, policy, and management classes to real-world problems that are typically presented to them by external clients.

This module teaches essential principles, tools and techniques of Healthcare Operations Management – both in general and as applied to specific healthcare organisations, processes and functions.

This module will develop students’ understanding of principles of health economic evaluation. Economic evaluation is concerned with the allocation of scarce resources, which is particularly important in healthcare provision today. Students will learn the tools to assess the effects and economic efficiency of health policy and interventions. The theory and methodologies students learn will provide them with practical tools that can be applied to healthcare provision planning in the public and private sectors. These tools can also help developers of health technologies and services (e.g., biomedical engineers, digital technology developers, and pharmacists) understand where the greatest value lies.

This module will explore the generic problem solving process which underpins the provision of decision support. In particular, it'll consider the role of modelling in that process. The activities of problem structuring, data collection and analysis, identification and evaluation of options, communication and implementation of learning, findings and recommendations will each be discussed along with the issues pertaining to each of them. The skills taught in this module, which are broader than for only the healthcare sector, are extremely important for healthcare policy and management.

This module runs over one semester but in two parts. The first part provides an introduction to the basic theory and application of statistical modelling. Topics covered included data analysis, probability theory, distributions and moments, estimation and hypothesis testing.

The second part focuses mainly on two areas - regression modelling and multivariate analysis. While key background theory will be presented, the emphasis is on the generation and interpretation of output from commercially available software. This module will form a foundation to the quantitative healthcare analysis you will use.

This module will demonstrate how spreadsheets can be used to support the analytical techniques whose theory is taught on other modules. For example, forecasting, simulation, optimisation, data analysis, as well as being used to support technical report writing.

Estimating demand for health care services and technologies is important for designing policy and interventions, and most prominence in this module is given to demand forecasting. You'll be introduced to different types of forecasting technique for short term smoothing through to decompositional analysis. These methods will be implemented using spreadsheet models

The class will consist of two parts. Together, the parts will provide students with knowledge of health systems financing, medical markets and policy innovation, public–private governance objectives and policy levers, health-system performance assessment and monitoring, the role of public financial management, and health systems needs assessment.

The key themes of the class – health systems performance and management, equity as a health policy goal, and the role of health system financing – will be explored through recent policy challenges, including health system reform, progress towards universal health coverage in low- and middle-income countries, the growth of the health system as a driver of economic growth, and health security as a global public good. 

The class will feature a mix of analytic tools and introduction to key policy debates in health policy.  Although concepts will be presented in a way as to be relatable to the UK and Scottish context, the focus of the class will be international.

The final component of the MSc course is a three-month summer dissertation project. The Department will arrange projects with external host organisations, as well as with internal academic clients. The type of placement you pursue will depend on your career goals, preferences, and a host of other factors. You can also propose your own projects.

The module will focus on the two forms of systems simulation; discrete-event simulation (DES) and system dynamics (SD; a continuous simulation technique). For DES, the class will start with an introduction, aiming to familiarise students with the concept and its use.

It continues with discussing a rational approach to simulation using a number of examples from manufacturing and service operations. For system dynamics the class will provide a background to system dynamics including its links to other modelling techniques being taught on the course, in particular, its links to problem structuring methods.

These types of models are often used for modelling health care operations (DES) as well disease dynamics (SD).

Problems from business, industry, and public policy motivate the use of stochastic modelling for analytical decision support.  The class will focus on two methodologies for supporting decision-making under uncertainty: stochastic agent-based modelling (ABM), a systems simulation method, and Bayesian belief network modelling (BBN). 

Agents-based models, also known as individual-based models in mathematical epidemiology, are often used to model infectious disease as well non-communicable disease and human behaviour. Agents may represent humans, institutions, organization, or any decision-making entities. ABMs can be used to project how macro-level order, patterns, and outcomes emerge bottom-up, from chance and actions and interactions of autonomous agents at the micro-level. An agent-based simulation (ABS) is an instance of a stochastic process.

BBN provide a means of modelling causal relationships between variables. The BBN part of the module focuses on methods for learning model structures from empirical data to understand how inference mechanisms behave, how models can be validated and when this type of modelling is useful for decision support.

The class focuses at the strategic, organisational level of PMM while providing the essential knowledge and skills at the technical level.

The module starts with presenting the background to performance measurement to provide you with an understanding of the roots of some of the common problems in measuring and managing performance in organisations. This will follow with discussing PMM from five different but highly inter-related perspectives, namely stakeholder, customer, comparative, operations and integrative perspectives.

This module will explore the entire process of structuring a risk problem, from modelling it to communicating recommendations, both theoretically and in practice.

Risk management is linked with decision analysis in so far as we explore decision making under uncertainty and it has links with quantitative analysis as we explore the use of statistics in understanding risk. However, the topic has some unique attributes such as risk communication and the role that experts play in risk assessment.

This module builds on a number of earlier taught skills, in particular the problem structuring element covered in Foundations of Operational Research and Business Analysis as this provides a basis to qualitative modelling for managing uncertainty and multiple perspectives along with becoming an effective business analyst. This class aims to specific subjects and operational issues surrounding services will be discussed.

This class will cover the fundamental statistical methods necessary for the application of classical statistical methods to data collected for health care research. There will be an emphasis on the use of real data and the interpretation of statistical analyses in the context of the research hypothesis under investigation. Software packages such as Minitab will be introduced.

*If you choose this class, you can only choose one additional elective class.

This covers all aspects of statistical consultancy skills necessary for being a successful statistician working in any research environment. You'll work on real-life problems in small groups and have the opportunity to interact with health care researchers to formulate hypotheses.

Surveys are an important way of collecting data. This class will introduce you to the methods that are commonly used in health care to design questionnaires and analyse data resulting from these questionnaires.

This class provides you with an introduction to health economic policy, a key area for their potential future careers. The purpose of this course is to develop your ability to use economic concepts and theories to analyse existing issues in the health care market and to inform decision making and policy development. The class will provide you with an overview of policy issues from both an academic and practitioner perspective. The class will also focus both on technical skills that are needed to do research in the area of health economics, as well as on policy implications and discussions. Due to its focus on policy evaluation, the course will provide a supporting function for you to proceed to the Summer Project study.

10 credits

This module aims to widen understanding of the relationship between heritage and tourism through examination of cultural resource management concerns in a global context as well as at the individual heritage at operation level. The concept of “world heritage” will be explored in its widest sense, including international treaties, policies and organisations involved in assessing the value (economic/social/political) of heritage globally. Current and future trends in the relationship between tourism, heritage and society will also be explored.

This class examines key moments in the development of modern systems of regulating drugs.

With a focus on western countries since 1800, it explores the political, social and economic contexts of decisions to control and restrict the consumption of both psychoactive and pharmaceutical products.

The objective is to place state enquiries, legislative projects and international agencies in historical context.