Comparison of general population, patient, and carer utility values for dementia health states.
Utility values to estimate quality-adjusted life years (QALYs) for use in cost-utility analyses are usually elicited from members of the general population. Public attitudes and understanding of dementia in particular may mean that values elicited from the general population may differ from patients and carers for dementia health states. This study examines how the population impacts utility values elicited for dementia health states using interviewer-administered time tradeoff valuation of health states defined by the dementia-specific preference-based measures DEMQOL-U (patient-report) and DEMQOL-Proxy-U (carer-report). Eight DEMQOL-U states were valued by 78 members of the UK general population and 71 patients with dementia of mild severity. Eight DEMQOL-Proxy-U states were valued by 77 members of the UK general population and 71 carers of patients with dementia of mild severity. Random-effects generalized least squares regression estimated the impact of population, dementia health state, and respondent sociodemographic characteristics on elicited values, finding that values for dementia health states differed by population and that the difference varied across dementia health states. Patients with dementia and carers of patients with dementia gave systematically lower values than members of the general population that were not due to differences in the sociodemographic characteristics of the populations. Our results suggest that the population used to produce dementia health state values could impact the results of cost-utility analyses and potentially affect resource allocation decisions; yet, currently, only general population values are available for usage.
Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK (DR, BM, TAY, JEB)
Donna
D
Rowen
Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK (DR, BM, TAY, JEB)
Brendan
B
Mulhern
Institute of Psychiatry, King's College London, London, UK (SB, RT, CW, MK)|Brighton and Sussex Medical School, University of Brighton, Brighton, UK (SB)
Sube
S
Banerjee
Institute of Psychiatry, King's College London, London, UK (SB, RT, CW, MK)
Rhian
R
Tait
Institute of Psychiatry, King's College London, London, UK (SB, RT, CW, MK)|University College London Hospital Stroke Research Team, North Thames Clinical Research Network, London, UK (CW)
Caroline
C
Watchurst
Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK (SCS)
Sarah C
SC
Smith
Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK (DR, BM, TAY, JEB)
Tracey A
TA
Young
Institute of Psychiatry, King's College London, London, UK (SB, RT, CW, MK)|Personal Social Services Research Unit, London School of Economics, London, UK (MK)
Martin
M
Knapp
Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK (DR, BM, TAY, JEB)
John E
JE
Brazier
D000293:Adolescent; D000328:Adult; D000368:Aged; D017028:Caregivers / Q000523:psychology*; D003704:Dementia / Q000523:psychology*; D005260:Female; D006304:Health Status; D006801:Humans; D007407:Interviews as Topic; D008297:Male; D008875:Middle Aged; D011594:Psychometrics; D011788:Quality of Life; D019057:Quality-Adjusted Life Years; D012720:Severity of Illness Index; D012959:Socioeconomic Factors; D055815:Young Adult
Alzheimer’s disease; dementia; health-related quality of life; preference-based measures of health; quality-adjusted life years; utilities