This paper presents a study to derive a preference-based measure of health from the SF-36, a widely used generic health-related quality of life (HRQoL) questionnaire. The SF-36 was revised into a six-dimensional health state classification called the SF-6D. A sample of 249 health states defined by the SF-6D were valued by a representative sample of 611 UK members of the general public using standard gamble. Models were estimated to predict health state valuations for all 18,000 states defined by the SF-6D. The econometric models produced significant coefficients for levels of the SF-6D, which were robust across model specifications. However, there were concerns with some inconsistent estimates and over-prediction of the value of the poorest health states. These issues must be weighed against the rich descriptive ability of the SF-6D and its potential application to existing and future SF-36 datasets. The SF-36 was reduced in size and complexity to make it easier for respondents to process and give reliable valuations of health states. A preference-based valuation survey was conducted using a version of standard gamble. The results of the survey were used in a model to predict values for all health states defined by the SF-6D. Econometric methods were chosen over multi-attribute utility theory due to the structure of the SF-6D system. The study used a pilot survey to demonstrate the feasibility of this approach. The results showed that the SF-6D could be used to generate health state utility values needed to construct QALYs and conduct cost-utility analyses. The study involved a representative sample of the UK population, with 836 individuals participating in the valuation survey. Each respondent was asked to value six health states. The data were used to estimate models for predicting health state valuations. The models were tested for their predictive ability and showed that the median model had the best predictive ability. The results of the study suggest that the SF-6D is a useful tool for generating preference-based health measures and can be used in economic evaluations of healthcare interventions. The study also highlights the importance of considering the potential inconsistencies in the coefficients of the SF-6D dimensions and the need for further research to address these issues. The study concludes that the SF-6D is a valuable tool for generating preference-based health measures and can be used in economic evaluations of healthcare interventions.This paper presents a study to derive a preference-based measure of health from the SF-36, a widely used generic health-related quality of life (HRQoL) questionnaire. The SF-36 was revised into a six-dimensional health state classification called the SF-6D. A sample of 249 health states defined by the SF-6D were valued by a representative sample of 611 UK members of the general public using standard gamble. Models were estimated to predict health state valuations for all 18,000 states defined by the SF-6D. The econometric models produced significant coefficients for levels of the SF-6D, which were robust across model specifications. However, there were concerns with some inconsistent estimates and over-prediction of the value of the poorest health states. These issues must be weighed against the rich descriptive ability of the SF-6D and its potential application to existing and future SF-36 datasets. The SF-36 was reduced in size and complexity to make it easier for respondents to process and give reliable valuations of health states. A preference-based valuation survey was conducted using a version of standard gamble. The results of the survey were used in a model to predict values for all health states defined by the SF-6D. Econometric methods were chosen over multi-attribute utility theory due to the structure of the SF-6D system. The study used a pilot survey to demonstrate the feasibility of this approach. The results showed that the SF-6D could be used to generate health state utility values needed to construct QALYs and conduct cost-utility analyses. The study involved a representative sample of the UK population, with 836 individuals participating in the valuation survey. Each respondent was asked to value six health states. The data were used to estimate models for predicting health state valuations. The models were tested for their predictive ability and showed that the median model had the best predictive ability. The results of the study suggest that the SF-6D is a useful tool for generating preference-based health measures and can be used in economic evaluations of healthcare interventions. The study also highlights the importance of considering the potential inconsistencies in the coefficients of the SF-6D dimensions and the need for further research to address these issues. The study concludes that the SF-6D is a valuable tool for generating preference-based health measures and can be used in economic evaluations of healthcare interventions.