Health Preferences: Can They Be Predicted By Quality Of Life?
A utility mapping algorithm has been developed by Texas MD Anderson Cancer Centre, researches within the United States. This algorithm is able to use data input regarding the quality of life of various individuals to then predict the health preferences of these individuals.
A quality of life survey produced at the UT MD Anderson Cancer centre was developed using quality of life scores from the Functional Assessment of Cancer Therapy- Melanoma. The researchers that developed this were attempting to form an approximation of the health preferences of the EQ-5D (Euro –QOLD Dimension) health program that is designed to make an assessment of health preferences such as the quantitative values for given health states. These are required in order to make cost effective studies when no other direct means of obtaining a patient's health preferences are at hand.
Many scientific researchers were restricted in their capacity to administer survey instruments while following patients across extended periods of time. This is because every extra survey would lead to an increase in the 'burden of participation' felt by survey participants. If they have to deal with this type of choice, a large number of people prefer quality of life instruments such as the FACT-M. This is because instruments like the FACT-M have increased responsiveness and sensitivity to variation and alteration. Nonetheless, instruments like the FACT-M are not able to perform cost effective analysis which requires a certain measure of preference for health states.
Quality of life, as is concerned with health states is assessed within the contexts of clinic tests and trials with the use of instruments that are designed specifically for their known responsiveness and sensitivity to variation and alteration. Nonetheless, methods of cost effective analysis may end up being preluded by a choice such as this one. The main aim of this analytical method was the exploration of whether reliable mapping functions may be developed to enable imputing of EQ-5D health utility values obtained from the FACT-M (FACT-Melanoma) quality of life results that would allow for the facilitation of future proof cost effective analysis in cases where direct preference inputs where unavailable.