Development of DEMQOL-U and DEMQOL-PROXY-U: generation of preference-based indices from DEMQOL and DEMQOL-PROXY for use in economic evaluation
Background: Dementia is one of the most common and serious disorders in later life and the economic and personal cost of caring for people with dementia is immense. There is a need to be able to evaluate interventions in dementia using cost-effectiveness analyses, but the generic preference-based me...
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| Format: | Article |
| Language: | English |
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NIHR Journals Library
2013-02-01
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| Series: | Health Technology Assessment |
| Subjects: | |
| Online Access: | https://doi.org/10.3310/hta17050 |
| _version_ | 1817989982022795264 |
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| author | B Mulhern D Rowen J Brazier S Smith R Romeo R Tait C Watchurst K-C Chua V Loftus T Young D Lamping M Knapp R Howard S Banerjee |
| author_facet | B Mulhern D Rowen J Brazier S Smith R Romeo R Tait C Watchurst K-C Chua V Loftus T Young D Lamping M Knapp R Howard S Banerjee |
| author_sort | B Mulhern |
| collection | DOAJ |
| description | Background: Dementia is one of the most common and serious disorders in later life and the economic and personal cost of caring for people with dementia is immense. There is a need to be able to evaluate interventions in dementia using cost-effectiveness analyses, but the generic preference-based measures typically used to measure effectiveness do not work well in dementia. Existing dementia-specific measures can effectively measure health-related quality of life but in their current form cannot be used directly to inform cost-effectiveness analysis using quality-adjusted life-years as the measure of effectiveness. Objectives: The aim was to develop two brief health-state classifications, one from DEMQOL and one from DEMQOL-Proxy, to generate health states amenable to valuation. These classification systems consisted of items taken from DEMQOL and DEMQOL-Proxy so they can be derived from any study that has used these instruments. Data sources: In the first stage of the study we used a large, clinically representative sample aggregated from two sources: a sample of patients and carers attending a memory service in south London and a sample of patients and carers from other community services in south London. This included 644 people with a diagnosis of mild/moderate dementia and 689 carers of those with mild/moderate dementia. For the valuation study, the general population sample of 600 respondents was drawn to be representative of the UK general population. Households were sampled in urban and rural areas in northern England and balanced to the UK population according to geodemographic profiles. In the patient/carer valuation study we interviewed a sample of 71 people with mild dementia and 71 family carers drawn from a memory service in south London. Finally, the instruments derived were applied to data from the HTA-SADD (Study of Antidepressants for Depression in Dementia) trial. Review methods: This was a complex multiphase study with four linked phases: phase 1 – derivation of the health-state classification system; phase 2 – general population valuation survey and modelling to produce values for every health state; phase 3 – patient/carer valuation survey; and phase 4 – application of measures to trial data. Results: All four phases were successful and this report details this development process leading to the first condition-specific preference-based measures in dementia, an important new development in this field. Limitations: The first limitation relates to the lack of an external data set to validate the DEMQOL-U and DEMQOL-Proxy-U classification systems. Throughout the development process we have made decisions about which methodology to use. There are other valid techniques that could be used and it is possible to criticise the choices that we have made. It is also possible that the use of a mild to moderate dementia sample has resulted in classification systems that do not fully reflect the challenges of severe dementia. Conclusion: The results presented are sufficiently encouraging to recommend that the DEMQOL instruments be used alongside a generic measure such as the European Quality of Life-5 Dimensions (EQ- 5D) in future studies of interventions in dementia as there was evidence that they can be more sensitive for patients at the milder end of disease and some limited evidence that the person with dementia measure may be able to reflect deterioration. Funding: The National Institute for Health Research Health Technology Assessment programme. |
| first_indexed | 2024-04-14T00:53:20Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 1366-5278 2046-4924 |
| language | English |
| last_indexed | 2024-04-14T00:53:20Z |
| publishDate | 2013-02-01 |
| publisher | NIHR Journals Library |
| record_format | Article |
| series | Health Technology Assessment |
| spelling | doaj.art-244cdc69c6b245c1a213017880c8a6362022-12-22T02:21:42ZengNIHR Journals LibraryHealth Technology Assessment1366-52782046-49242013-02-0117510.3310/hta1705007/73/01Development of DEMQOL-U and DEMQOL-PROXY-U: generation of preference-based indices from DEMQOL and DEMQOL-PROXY for use in economic evaluationB Mulhern0D Rowen1J Brazier2S Smith3R Romeo4R Tait5C Watchurst6K-C Chua7V Loftus8T Young9D Lamping10M Knapp11R Howard12S Banerjee13Health Economics and Decision Science, School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UKHealth Economics and Decision Science, School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UKHealth Economics and Decision Science, School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UKDepartment of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UKInstitute of Psychiatry, King's College London, London, UKInstitute of Psychiatry, King's College London, London, UKInstitute of Psychiatry, King's College London, London, UKInstitute of Psychiatry, King's College London, London, UKInstitute of Psychiatry, King's College London, London, UKHealth Economics and Decision Science, School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UKDepartment of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UKInstitute of Psychiatry, King's College London, London, UKInstitute of Psychiatry, King's College London, London, UKCentre for Dementia Studies, Brighton and Sussex Medical School, Brighton, UKBackground: Dementia is one of the most common and serious disorders in later life and the economic and personal cost of caring for people with dementia is immense. There is a need to be able to evaluate interventions in dementia using cost-effectiveness analyses, but the generic preference-based measures typically used to measure effectiveness do not work well in dementia. Existing dementia-specific measures can effectively measure health-related quality of life but in their current form cannot be used directly to inform cost-effectiveness analysis using quality-adjusted life-years as the measure of effectiveness. Objectives: The aim was to develop two brief health-state classifications, one from DEMQOL and one from DEMQOL-Proxy, to generate health states amenable to valuation. These classification systems consisted of items taken from DEMQOL and DEMQOL-Proxy so they can be derived from any study that has used these instruments. Data sources: In the first stage of the study we used a large, clinically representative sample aggregated from two sources: a sample of patients and carers attending a memory service in south London and a sample of patients and carers from other community services in south London. This included 644 people with a diagnosis of mild/moderate dementia and 689 carers of those with mild/moderate dementia. For the valuation study, the general population sample of 600 respondents was drawn to be representative of the UK general population. Households were sampled in urban and rural areas in northern England and balanced to the UK population according to geodemographic profiles. In the patient/carer valuation study we interviewed a sample of 71 people with mild dementia and 71 family carers drawn from a memory service in south London. Finally, the instruments derived were applied to data from the HTA-SADD (Study of Antidepressants for Depression in Dementia) trial. Review methods: This was a complex multiphase study with four linked phases: phase 1 – derivation of the health-state classification system; phase 2 – general population valuation survey and modelling to produce values for every health state; phase 3 – patient/carer valuation survey; and phase 4 – application of measures to trial data. Results: All four phases were successful and this report details this development process leading to the first condition-specific preference-based measures in dementia, an important new development in this field. Limitations: The first limitation relates to the lack of an external data set to validate the DEMQOL-U and DEMQOL-Proxy-U classification systems. Throughout the development process we have made decisions about which methodology to use. There are other valid techniques that could be used and it is possible to criticise the choices that we have made. It is also possible that the use of a mild to moderate dementia sample has resulted in classification systems that do not fully reflect the challenges of severe dementia. Conclusion: The results presented are sufficiently encouraging to recommend that the DEMQOL instruments be used alongside a generic measure such as the European Quality of Life-5 Dimensions (EQ- 5D) in future studies of interventions in dementia as there was evidence that they can be more sensitive for patients at the milder end of disease and some limited evidence that the person with dementia measure may be able to reflect deterioration. Funding: The National Institute for Health Research Health Technology Assessment programme.https://doi.org/10.3310/hta17050dementiademqoldemqol-proxyeconomic evaluationpreference-based measurehealth state classificationqaly |
| spellingShingle | B Mulhern D Rowen J Brazier S Smith R Romeo R Tait C Watchurst K-C Chua V Loftus T Young D Lamping M Knapp R Howard S Banerjee Development of DEMQOL-U and DEMQOL-PROXY-U: generation of preference-based indices from DEMQOL and DEMQOL-PROXY for use in economic evaluation Health Technology Assessment dementia demqol demqol-proxy economic evaluation preference-based measure health state classification qaly |
| title | Development of DEMQOL-U and DEMQOL-PROXY-U: generation of preference-based indices from DEMQOL and DEMQOL-PROXY for use in economic evaluation |
| title_full | Development of DEMQOL-U and DEMQOL-PROXY-U: generation of preference-based indices from DEMQOL and DEMQOL-PROXY for use in economic evaluation |
| title_fullStr | Development of DEMQOL-U and DEMQOL-PROXY-U: generation of preference-based indices from DEMQOL and DEMQOL-PROXY for use in economic evaluation |
| title_full_unstemmed | Development of DEMQOL-U and DEMQOL-PROXY-U: generation of preference-based indices from DEMQOL and DEMQOL-PROXY for use in economic evaluation |
| title_short | Development of DEMQOL-U and DEMQOL-PROXY-U: generation of preference-based indices from DEMQOL and DEMQOL-PROXY for use in economic evaluation |
| title_sort | development of demqol u and demqol proxy u generation of preference based indices from demqol and demqol proxy for use in economic evaluation |
| topic | dementia demqol demqol-proxy economic evaluation preference-based measure health state classification qaly |
| url | https://doi.org/10.3310/hta17050 |
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