title: Improving the measurement of QALYs in dementia: developing patient- and carer-reported health state classification systems using Rasch analysis.
abstract: OBJECTIVE
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK.
authors.forename: Brendan
authors.initials: B
authors.lastname: Mulhern
authors.forename: Sarah C
authors.initials: SC
authors.lastname: Smith
authors.forename: Donna
authors.initials: D
authors.lastname: Rowen
authors.forename: John E
authors.initials: JE
authors.lastname: Brazier
authors.forename: Martin
authors.initials: M
authors.lastname: Knapp
authors.forename: Donna L
authors.initials: DL
authors.lastname: Lamping
authors.forename: Vanessa
authors.initials: V
authors.lastname: Loftus
authors.forename: Tracey A
authors.initials: TA
authors.lastname: Young
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Howard
authors.forename: Sube
authors.initials: S
authors.lastname: Banerjee
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D017028:Caregivers; D002965:Classification / Q000379:methods; D003704:Dementia / Q000503:physiopathology / Q000523:psychology*; D005163:Factor Analysis, Statistical; D005260:Female; D006304:Health Status; D006801:Humans; D016015:Logistic Models; D008297:Male; D057240:Patient Preference / Q000523:psychology / Q000706:statistics & numerical data; D010361:Patients / Q000523:psychology*; D011594:Psychometrics; D019057:Quality-Adjusted Life Years; D011795:Surveys and Questionnaires / Q000592:standards*; D006113:United Kingdom