Skip to 0 minutes and 9 seconds Earlier in the course, we looked at an example of a generic PROM, the SF-36. As we discovered, this measure is of limited use for informing healthcare spending or in an economic-evaluation context, as the scores it generates are not based on preferences. That is, it does not generate utility data which can be used to calculate QALYs. However, Professor John Brazier, here at the University of Sheffield, has taken a selection of items from the SF-36 measure and developed the SF-6D to create a preference-based classification for describing health. He did this by developing preference weights for all of the states described by the SF-6D classification. To develop these preference weights, a method called the “standard gamble” was used to value health states.
Skip to 0 minutes and 49 seconds This is different to the time trade off method but is still a choice-based method. The development of these preference weights allows an analyst to obtain utilities and calculate QALYs. This is a hugely powerful piece of research, as it allows researchers who have SF-36 data to be able to generate QALYs. Let’s hear more detail about the SF-6D and its development from Professor John Brazier. The SF-6D is a preference-based measure of health designed for calculating Quality Adjusted Life Years. Like all preference-based measures, it’s composed of two parts, a health state classification system that describes health, and a set of values for scoring it.
Skip to 1 minute and 33 seconds The health state classification system is made up of six dimensions covering physical functioning, role limitation, social functioning, pain, mental health, and vitality. The dimensions of the SF-6D have between four and six levels that together generate 18,000 health states. The SF-6D was developed from the SF-36. And essentially we selected items from the SF-36 that best represented each of the dimensions measured by the SF-36, to come up with the 6D.
Skip to 2 minutes and 9 seconds The preference weights for the SF-6D were obtained by interviewing over 800 members of the general population, asking them to value a small sample of health states generated by the 6D using standard gamble, which is a choice-based elicitation technique, a bit like time trade off that had been used to value the EQ-5D before. The main SF-6D publication has now been cited in over 1,000 papers. And it’s been used in clinical trials, and it’s also been used to populate cost-effectiveness models for conducting economic evaluation. It’s available in many translations. And there are also preference weights available in countries including Japan, Hong Kong, Brazil, Spain, and Australia. Future work is looking at more advanced methods for analysing the valuation data.
Skip to 3 minutes and 1 second And we’re also developing a version 2 of the SF-6D, which includes an improved descriptive system and also estimating preference weights using a new valuation method.
Case study of a utility measure: The SF-6D
In this video, we hear from Professor John Brazier who has developed a preference based classification for describing health using the SF-36; one of the most widely used measures of general health in clinical studies throughout the world.
Earlier in the course we saw how a generic PROM, the SF-36, is of limited use for informing healthcare spending or for use in economic evaluation, as the scores it generates are not based on preferences. That is, it does not generate utility data which can be used to calculate QALYs.
In this video, John explains how he used a selection of items from the SF-36 to develop a preference based classification for describing health; the SF-6D.
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