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Discrete Choice Experiments

Emma McIntosh is involved in the development of discrete choice experiment methodologies including strength of preference modelling and best attribute scaling.A number of projects, such as the Home Visiting Trial and genetics projects incorporate methodological aspects of discrete choice experiments. Emma is currently completing a project with HERC colleague Stavros Petrou which uses the methodology of discrete choice experiments alongside a randomised controlled trial of miscarriage management (MIST).

Work has recently been completed in this methodological area with the ETHOX Centre at the University of Oxford. This project used discrete choice experiment methodology to explore the reasons that those with experience of real decision-making around resource allocation think relevant in deciding on the priority of new interventions. This collaboration has given rise to two pieces of work, a qualitative paper (in press) and a quantitative paper (under revision) as well as a DPhil thesis.

There is also an ongoing collaboration in the form of an MRC Research Initiation Grant on which Emma McIntosh is a co-applicant with the MRC Health Services Collaboration at the University of Bristol, the Health Economics Research Unit at the University of Aberdeen and the Centre for Health Economics Research and Evaluation at the University of Technology, Sydney. The objective of this Research Initiation Grant is to explore the potential use of best-attribute scaling in health care.

Emma has recently completed a systematic review of discrete choice experiments in health care to establish what health and non-health attributes matter to patients and the population more generally. This commissioned review was part of the Office of Health Economics' programme ‘NHS Outcomes, Performance and Productivity’.  Based on the results of the review the aim is to draw some conclusions regarding which of these attributes the NHS should be trying to measure . See for further details.

Using willingness to pay methods within a Cost-benefit Analysis Framework 

Emma McIntosh and Alastair Gray have worked in collaboration with the Centre for Spinal Surgery, University of Balgrist, Zurich, Switzerland on a cost-benefit-analysis (CBA) feasibility study using a contingent valuation (CV) survey with ex post willingness-to-pay/-to-accept (WTP/WTA) questions.

The study objectives were:
(i) to demonstrate the feasibility of the CV approach to identify net-benefits gained from spinal interventions, and (ii) to conduct a formal CBA using a retrospective study design.


Hasman, A, McIntosh, E, and Hope, T (2008). What reasons do those with practical experience use in deciding on priorities for healthcare resources? A qualitative study. J Med Ethics, 34(9):658-63.

Petrou S, McIntosh E (2008). Measuring the benefits of growth hormone therapy in children: a role for preference-based approaches? Arch Dis Child, 93(2):95-7 (Published online January 27th 2008).

Barlow, J, Davis, H, McIntosh, E, Jarrett, P, Mockford, C, and Stewart-Brown, S (2007). Role of home visiting in improving parenting and health in families at risk of abuse and neglect: results of a multicentre randomised controlled trial and economic evaluation. Arch Dis Child, 92(3):229-33.

Haefili, M, Elfering, A, McIntosh, E, Gray, A, Sukthankar, A, and Boos, N (2007). A cost-benefit analysis using contingent valuation techniques: A feasibility study in spinal surgery. Value Health, Epub ahead of print.

Lloyd, A, McIntosh, E, Rabe, KF, and Williams, A (2007). Patient preferences for asthma therapy: a discrete choice experiment. Prim Care Respir J, 16(4):241-8.

Ossa, DF, Briggs, A, McIntosh, E, Cowell, W, Littlewood, T, and Sculpher, M (2007). Recombinant erythropoietin for chemotherapy-related anaemia: economic value and health-related quality-of-life assesment using direct utility elicitation and discrete choice experiment methods. Pharmacoeconomics 25(3): 223-37.

McIntosh, E (2006). Using discrete choice experiments within a cost-benefit analysis framework: some considerations. Pharmacoeconomics 24(9):855-68.