Improving the measurement of QALYs in dementia: Developing patient- and carer-reported health state classification systems using Rasch analysis

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Journal Article
Value in Health, 2012, 15 (2), pp. 323 - 333
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Objectives: Cost-utility analysis is increasingly used to inform resource allocation. This requires a means of valuing health states before and after intervention. Although generic measures are typically used to generate values, these do not perform well with people with dementia. We report the development of a health state classification system amenable to valuation for use in studies of dementia, derived from the DEMQOL system, measure of health-related quality of life in dementia by patient self-report (DEMQOL) and carer proxy-report (DEMQOL-Proxy). Methods: Factor analysis was used to determine the dimensional structure of DEMQOL and DEMQOL-Proxy. Rasch analysis was subsequently used to investigate item performance across factors in terms of item-level ordering, functioning across subgroups, model fit, and severity-range coverage. This enabled the selection of one item from each factor for the classification system. A sample of people with a diagnosis of mild/moderate dementia (n = 644) and a sample of carers of those with mild/moderate dementia (n = 683) were used. Results: Factor analysis found different five-factor solutions for DEMQOL and DEMQOL-Proxy. Following item reduction and selection by using Rasch analysis, a five-dimension classification for DEMQOL and a four-dimension classification for DEMQOL-Proxy were developed. Each item contained four health state levels. Conclusion: Combining Rasch and classical psychometric analysis is a valid method of selecting items for dementia health state classifications from both the patient and carer perspectives. The next stage is to obtain preference weights so that the measure can be used in the economic evaluation of treatment, care, and support arrangements for dementia. Copyright © 2012, International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc.
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