2014
DOI: 10.1001/jamaophthalmol.2013.7639
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Development of a Preference-Based Index From the National Eye Institute Visual Function Questionnaire–25

Abstract: IMPORTANCE Understanding how individuals value health states is central to patient-centered care and to health policy decision making. Generic preference-based measures of health may not effectively capture the impact of ocular diseases. Recently, 6 items from the National Eye Institute Visual Function Questionnaire-25 were used to develop the Visual Function Questionnaire-Utility Index health state classification, which defines visual function health states.OBJECTIVE To describe elicitation of preferences for… Show more

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Cited by 42 publications
(44 citation statements)
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“…The questionnaire is composed of 25 questions that evaluate various domains of quality of life and visual functioning, as outlined in Table 1 [4]. …”
Section: Methodsmentioning
confidence: 99%
See 2 more Smart Citations
“…The questionnaire is composed of 25 questions that evaluate various domains of quality of life and visual functioning, as outlined in Table 1 [4]. …”
Section: Methodsmentioning
confidence: 99%
“…The means were calculated according to the following equation: the mean is defined as the sum of the numerical values of each question within a given domain divided by the number of items evaluated in that domain [4]. …”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…26 One of the strengths of VRQoL measures is that they have the potential to integrate the multifaceted effects of disease on visual function. This ability makes the NEI-VFQ-25 and its corresponding preference-based index 27 potentially valuables tools for cost-effectiveness analyses by providing a method for capturing disease-specific trade-offs to complement the more commonly described general health trade-offs assessed using metrics such as the EQ-5D. However, the NEI-VFQ was not originally designed for patients with uveitis, so it may not be able to capture the impact on quality of life from disease-specific visual symptoms.…”
Section: Discussionmentioning
confidence: 99%
“…Rather than using individual dimension-levels as the independent variables in the regression analysis, these studies used corresponding Rasch logit values for health states to predict HSUVs. Two subsequent studies have used similar techniques to select a sample of health states [23] or predict HSUVs [35]. Although there remain some issues to resolve, particularly the ability of the technique to predict values for individual health states rather than groups of states based on total dimension-level scores [23], this is a promising new approach that is an important area for further research.…”
Section: Methods For Generating a Tariffmentioning
confidence: 99%