Programmes that convert your SF-36 or SF-12 data into an SF-6D health state and corresponding utility score for each observation in your dataset.

The programme will generate for each row of your dataset the six dimension scores of the SF-6D, the six digit health state and a utility value anchored at 1 for full health and 0 for dead.

The SF-6D is a generic preference-based single index measure of health that can be used to generate QALYs and hence which can be used in cost-utility analysis.

There are excel, SPSS and SAS programmes available to convert SF-36 data into SF-6D data and there are SPSS and SAS programmes available to convert SF-12 data into SF-6D.

All programmes generate the SF-6D utility score estimated using a set of parametric preference weights obtained from a sample of the general population using the recognised valuation technique of standard gamble. In addition a new excel programme is now available from the University of Sheffield to convert SF-36 data into the SF-6D utility score estimated using a set of non-parametric Bayesian preference weights. These nonparametric preference weights are an improvement on the parametric preference weights as the nonparametric model has many advantages over the conventional parametric random effects model which is reflected in improvements in the predictive ability of the model. For further details see Kharroubi et al. (2007).

Furthermore a new excel programme is available to convert SF-36 data into the SF-6D utility score estimated using a set of preference weights obtained using an ordinal valuation technique for a sample of the general population. The estimates using ordinal data represent an alternative value set based on a different valuation technique which produces estimates that are comparable to estimates produced using standard gamble data. For further details see McCabe et al. (2006).

No. You need a licence agreement for each study for which you use the SF-6D algorithm.

The SF-6D comes with a set of preference weights obtained from a sample of the general population in the UK using the recognised valuation technique of standard gamble. Members of the general population in the UK were asked to value a selection of health states from which a model has been estimated to predict all the health states described by the SF-6D.

Instructions are available for each of the programmes available but these do not outline how the process can be done using a different software package. We currently have algorithms available for use on SF-36 data in SAS, SPSS and excel, and for SF-12 data in SAS and SPSS.

The SF-6D utility score is generated using preference weights obtained from a sample of the general population in the UK. The UK population may have different preferences to non-UK populations.

 Please watch this video for more information 

There is emerging evidence that SG health state values differ between countries for SG. There have been valuation surveys completed in Japan, Hong Kong, Portugal, Brazil and Spain using similar methods to those used
in UK. Details on these surveys can be found in the publications listed at the bottom of this note. Surveys have also been undertaken in Australia and Singapore, but the results have yet to be published.

Researchers interested in using the SF-6D in these countries should contact the names listed below:-

Australia
Rosalie Viney: rosalie.viney@chere.uts.edu.au
Brendan Mulhern: Brendan.Mulhern@chere.uts.edu.au

Brazil
Luciane Cruz:lncruz@ig.com.br
Marcelo Fleck: mfleck.voy@zaz.com.br

Hong Kong
Cindy Lam: clklam@hku.hk
Sarah McGhee: smmcghee@hkucc.hku.hk

Japan
Shunichi Fukuhara: fukuhara@pbh.med.kyoto-u.ac.jp

Portugal
Lara Nobre Noronha Ferreira: lnferrei@ualg.pt
Pedro Lopes Ferreira: pedrof@fe.uc.pt

Singapore
Nan Luo: medln@nus.edu.sg

Spain
José María Abellán: dionisos@um.es

Publications on valuation surveys conducted in other countries:
Lam CLK, Brazier J, McGhee SM. Valuation of the SF-6D health states is feasible, acceptable, reliable and valid in a Chinese population. Value in Health 2008;11:295-303.

Brazier JE, Fukuhara S, Roberts J, Kharoubi S et al. Estimating a preference-based index from the Japanese SF-36.

Journal of Clinical Epidemiology; 62(12): 1323-1331.

Ferreira LN, Ferreira PL, Brazier J, Rowen D. A Portugese value set for the SF-6D. Value in Health 2010; 13(5): 624-630.

Abellan-Perpiñan JM, Sanchez-Martinez FI, Martinez-Perez JE, Mendez I. Lowering the 'floor' of the SF-6D scoring algorithm using a lottery equivalent method. Health Economics 2012: 21; 1271-1285.

Méndez I, Abellán JM, Sanchez FI, Martinez JE. Inverse probability weighted estimation of social tariffs: An illustration using SF-6D value sets. Journal of Health Economics 2011: 30; 1280-1292.