Developing preference-based health measures: using Rasch analysis to generate health state values.
OBJECTIVE
Condition-specific measures may not always have independent items, yet existing techniques of developing health state utility values from these measures are inappropriate when items are not independent. This study develops methods for deriving and valuing health states for a condition-specific preference-based measure where items are not independent.


METHODS
The analysis has three stages: firstly, Rasch analysis is used to develop a health state classification system from the Flushing Symptoms Questionnaire (FSQ) that is amenable to valuation and to identify a set of health states for valuation. Secondly, a valuation survey of the health states using time-trade-off (TTO) methods is conducted to elicit health state values. Finally, regression models are applied to map the relationship between mean TTO values and Rasch logit values. The model is then used to estimate health state values for all possible health states.


RESULTS
Rasch models were fitted to 1,270 responders to the FSQ and a series of 16 health states were identified for the valuation exercise. An ordinary least squares model best described the relationship between mean TTO values and Rasch logit values (R (2) = 0.958; root mean square error = 0.042).


CONCLUSIONS
This study demonstrates how health state utility values can be mapped onto Rasch logit values in order to value all states defined by the FSQ, a condition-specific measure where items are not independent. This should significantly enhance research in this field.
Young
Tracey A
TA
School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield S1 4DA, UK.
Rowen
Donna
D
Norquist
Josephine
J
Brazier
John E
JE
D000293:Adolescent; D000328:Adult; D000368:Aged; D005260:Female; D006304:Health Status; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D017060:Patient Satisfaction; D011594:Psychometrics / Q000295:instrumentation*; D011788:Quality of Life; D012044:Regression Analysis; D011795:Surveys and Questionnaires / Q000592:standards; D013997:Time Factors; D055815:Young Adult
Res Nurs Health. 1993 Dec;16(6):459-65
8248573
Value Health. 2004 Sep-Oct;7 Suppl 1:S22-6
15367240
Health Technol Assess. 1999;3(9):i-iv, 1-164
10392311
Value Health. 2009 Jan-Feb;12(1):159-66
18647258
J Outcome Meas. 1999;3(2):103-22
10204322
Qual Life Res. 2011 Apr;20(3):321-33
20972629
Curr Med Res Opin. 2007 Jul;23(7):1549-60
17559750
Br J Pharmacol. 2008 Mar;153 Suppl 1:S68-75
18037924
J Clin Epidemiol. 1998 Nov;51(11):1115-28
9817129
Qual Life Res. 2009 Mar;18(2):253-65
19082759
Med Care. 1997 Nov;35(11):1095-108
9366889
Med Care. 2002 Feb;40(2):113-28
11802084