ºù«Ӱҵ

Deciding which health care interventions to fund is a complex and emotive question. Objective analyses of cost-effectiveness are a crucial aid to decision making. The Short Form 6 Dimension (SF-6D) algorithm, developed by Jennifer Roberts (School of Economics, University of ºù«Ӱҵ), John Brazier (School of Health & Related Research [ScHARR] University of ºù«Ӱҵ), and Mark Deverill (ScHARR) is used around the world to inform these decisions. It enables the calculation of ‘quality adjusted life years’ (QALYs), which allow calculation of the cost-effectiveness of healthcare interventions given ever increasing demands on scarce resources.

The SF-6D is one of only three such algorithms in general use globally. Public policy and social welfare benefits arise from its use by health regulatory agencies globally to facilitate more efficient use of funds. Commercial benefits arise from licensing the SF-6D to pharmaceutical companies and other private sector users, to enable them to assess the cost effectiveness of their products. Since August 2013, licence sales  have generated more than $2.2 million in royalty income. The SF-6D is also freely available to non-commercial bodies, including researchers and policymakers.

The original research was funded by the global pharmaceutical company GSK. The main research output was published in the ; it won the 2002 International Society for Quality of Life Research Article of the Year, and has since been cited more than 2200 times (Scopus). 

The SF-6D contributes to a more efficient allocation of scarce health care resources. It is used by health regulatory agencies around the world, including in Australia, Canada, China, Ireland, Japan, Netherlands, Norway, Spain and the United States. In the UK the SF-6D has been used in health care decision making by the , the Scottish Medicines Consortium and the All Wales Medicines Strategy Group.

SF-6D licences have been purchased by many of the world’s major pharmaceutical companies including Novartis, Roche, Astrazeneca, Pfizer, Merck and Sanofi. Use covers a broad range of disease areas, including: addiction, asthma, diabetes, heart disease, HIV, multiple sclerosis, rheumatoid arthritis, stroke, and a number of different forms of cancer, including those with the highest population prevalence such as bowel, breast and prostate cancer. 

Research Outputs

• Brazier, J., Roberts, J., & Deverill, M. (2002). The estimation of a preference-based measure of health from the SF-36. Journal of Health Economics, 21(2), 271–292.  
• Brazier, J. E., & Roberts, J. (2004). The Estimation of a Preference-Based Measure of Health From the SF-12. Medical Care, 42(9), 851–859.
• Kharroubi, S. A., Brazier, J. E., Roberts, J., & O’Hagan, A. (2007). Modelling SF-6D health state preference data using a nonparametric Bayesian method. Journal of Health Economics, 26(3), 597–612.  
• Brazier, J. E., Fukuhara, S., Roberts, J., Kharroubi, S., Yamamoto, Y., Ikeda, S., Doherty, J., & Kurokawa, K. (2009). Estimating a preference-based index from the Japanese SF-36. Journal of Clinical Epidemiology, 62(12), 1323–1331.  
• Brazier, J., Czoski-Murray, C., Roberts, J., Brown, M., Symonds, T., & Kelleher, C. (2007). Estimation of a Preference-Based Index from a Condition-Specific Measure: The King’s Health Questionnaire. Medical Decision Making, 28(1), 113–126.  
• Tsuchiya, A. Brazier JE, Roberts J Comparison of valuation methods used to generate the EQ5D and the SF6D value sets in the UK, Journal of Health Economics, 25(2): 334-346
• Brazier, J., Roberts, J., Tsuchiya, A., & Busschbach, J. (2004). A comparison of the EQ- 5D and SF-6D across seven patient groups. Health Economics, 13(9), 873–884.