Informing ‘Realistic Medicine’: Can Economic Evaluations Account for Heterogeneity in Care Preferences?

The Chief Medical Officer in Scotland recently outlined her vision for realistic medicine, with key objectives to:

(1) build a personalised approach to care;

(2) promote shared decision making between patients and their doctors;

(3) reduce unnecessary variation in practice and outcomes;

(4) reduce harm and waste;

(5) improve risk management; and

(6) promote improvement and innovation.

This vision is based on the idea that treatments should add value for patients and carers through personalised approaches to care. This requires appropriate variation in the provision of treatment that is in line with heterogeneity in the preferences and attitudes of patients. Shared decision making is advocated as the process by which to identify the preferences of patients and better align these with the treatment options available. The objective of shared decision making is therefore to guide patients toward the treatments that will provide maximum value to them. Such an approach is appealing as it offers scope to increase the value of health care to users, whilst potentially reducing costs through the avoidance of wasteful treatment that patients do not value. In fact, such an approach may naturally lead to appropriate marginal disinvestment driven by the preferences and values of service users, enabling reinvestment in services and treatments that offer greater value.

Personalised care based on the individual preferences challenges established methods that are used for determining the cost-effectiveness of alternative treatment options. The standard approach to economic evaluation focuses on the costs and benefits of alternative interventions, using a measure of benefit which reflects population-averaged preferences (most frequently for health outcomes). It does not account for preference heterogeneity. The results are generally used to support the adoption of one technology over all other relevant alternatives for a given indication. In the context of personalised care, these approaches can result in an inefficient allocation of health care resources, because patients may not receive the care they would value most.

This PhD programme will explore if preference heterogeneity can be incorporated into the economic evaluation of health care interventions, and how resulting policy recommendations may differ from those based on traditional evaluation methods. Stated preference methods will be used to measure heterogeneity in treatment preferences (Train, 2009). The elicited preferences will be used in a cost-benefit analysis. For example, comparing an invasive surgical approach with a more conservative approach to treatment, one could determine the value of the surgical approach based on the preferences of those who would choose it, and the value of the conservative approach to those with a preference for that option. This might involve a trade-off between some measure of clinical effectiveness and the risk of treatment related complications. Preferences for these characteristics may differ between patients based on their expectations, social backgrounds and the severity of their clinical condition. The underlying hypothesis of the proposed research is that accounting for such preference heterogeneity in the evaluation and provision of treatment will increase value to patients and lower costs to the health system. The successful candidate can explore a variety of methodological issues in this context such as the use of qualitative methods to better understand preference heterogeneity or compare different methods of quantifying preference heterogeneity.

You will join a multidisciplinary collaborative team with an international reputation in the development of stated preference methods and health technology assessment. This project will suit a numerically skilled student with an interest in these two areas of health economics research, and who preferably holds a postgraduate qualification in economics, health economics or other related quantitative discipline.

Prospective students should include a written statement of no more than 1,000 words that outlines their initial ideas about how they would like to focus and conduct this project. Please upload this document with your formal application.