Development of an Online Time Trade off Methods for Health State Valuation

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Kularatna, S
Byrnes, J
Chen, G
Scuffham, P
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2018
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Tokyo, Japan
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Abstract

Objectives Face to face time trade off (TTO) applications are expensive and time consuming. Therefore, it is important to explore an alternative robust online application for this classical valuation method. This study assessed the feasibility of using an online TTO method to elicit preferences for health states defined by the EQ-5D-5L classification system.

Methods An online panel (n=400) between 18 to 73 years of age was recruited for this study with the sample demographically similar to the Australian general population. The TTO procedure was developed following the TTO user manual from the University of York. Eighty six EQ-5D-5L health states were directly valued. Each respondent was given a randomly selected 10 health states to value as compared with full health (‘11111’). Basic demographics, co-morbidities and visual analogue scale data were also collected. The direct valuation of 86 health states from this online study were compared with the modelled values based on the Australian EQ-5D-5L algorithm based on discrete choice experiment (DCE). The degree of agreement between the two measures were determined using the Pearson and intra class correlation.

Results There were 4,280 observations. Direct utility measures recorded as 0.5 (n=1,106) were excluded as it improves the agreement. Mean utility difference between this study and those calculated based on DCE approach was -0.03 (SD=0.24). Pearson correlation and ICC were 0.84 and 0.75 respectively.

Conclusions Further analysis need to be conducted to assess the reliability of excluded data. There are substantial similarities between the recorded direct valuation based on this online task and the derived values from the online DCE task used to develop the Australian EQ5D-5L algorithm. Further improvements to the online methods, such as including a confirmatory question for responses of 0.5 are suggested for further consideration.

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Value in Health
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21
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S2
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Health economics
Applied economics
Health services and systems
Policy and administration
Social Sciences
Science & Technology
Life Sciences & Biomedicine
Economics
Health Care Sciences & Services
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Kularatna, S; Byrnes, J; Chen, G; Scuffham, P, Development of an Online Time Trade off Methods for Health State Valuation, Value in Health, 2018, 21, pp. S100-S100