Jeff Richardson1, Kompal Sinha, Angelo Iezzi, Munir A Khan. 1. Faculty of Business and Economics, Centre for Health Economics, Monash University, Wellington Road, Clayton, VIC, 3800, Australia, jeffrey.richardson@monash.edu.
Abstract
PURPOSE: The objective of this paper is to describe the four-stage methodology used to obtain utility scores for the Assessment of Quality of Life (AQoL)-8D, a 35-item 8 dimension multi-attribute utility instrument, which was created to achieve a high degree of sensitivity to psycho-social health. METHODS: Data for the analyses were obtained from a representative group of 347 members of the Australian public and from 323 mental health patients each of whom provided VAS and time trade-off valuations of multiple health states. Data were used initially to create multiplicative scoring algorithms for each of the instrument's 8 dimensions and for the overall instrument. Each of the algorithms was then subject to a second-stage econometric 'correction'. RESULTS: Algorithms were successfully created for each of the AQoL-8D's dimensions, for physical and mental 'super-dimensions' and for the overall AQoL-8D instrument. The final AQoL-8D algorithm has good predictive power with respect to the TTO valuations. CONCLUSIONS: The AQoL-8D is a suitable instrument for researchers conducting cost utility analyses generally but, in particular, for the analysis of services affecting psycho-social health.
PURPOSE: The objective of this paper is to describe the four-stage methodology used to obtain utility scores for the Assessment of Quality of Life (AQoL)-8D, a 35-item 8 dimension multi-attribute utility instrument, which was created to achieve a high degree of sensitivity to psycho-social health. METHODS: Data for the analyses were obtained from a representative group of 347 members of the Australian public and from 323 mental health patients each of whom provided VAS and time trade-off valuations of multiple health states. Data were used initially to create multiplicative scoring algorithms for each of the instrument's 8 dimensions and for the overall instrument. Each of the algorithms was then subject to a second-stage econometric 'correction'. RESULTS: Algorithms were successfully created for each of the AQoL-8D's dimensions, for physical and mental 'super-dimensions' and for the overall AQoL-8D instrument. The final AQoL-8D algorithm has good predictive power with respect to the TTO valuations. CONCLUSIONS: The AQoL-8D is a suitable instrument for researchers conducting cost utility analyses generally but, in particular, for the analysis of services affecting psycho-social health.
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