(EQ-5D + VAS) x Rasch = HRQoL Measure

The EQ-5D questionnaire and the EQ Visual Analogue Scale (EQ-VAS) were developed by the EuroQol Group for deriving the preference-weighted single indices used for economics studies involving tradeoffs. This study investigates the extent to which the five EQ-5D items and the VAS together form a valid measure of Health Related Quality of Life (HRQoL) in a U.S. representative sample diagnosed with the most prevalent chronic health conditions.

The EQ-5D-3L has 5 items classifying health in terms of mobility (MO), self-care (SC), usual activities (UA), pain/discomfort (PD) and anxiety/depression (AD), with the 3 response category coding gave lower scores for healthier respondents. The original 101 VAS categories were collapsed to form a 9-category item to ensure sufficient frequency of endorsement for each VAS category with coding reversed to be consistent with the EQ-5D.

Respondents extracted from the 2-year panel (2002-03) from the Medical Expenditure Panel Survey (MEPS) 1) were =18 years of age; 2) had complete EQ-5Ds, and 3) reported primary ICD-9-CM for the top 10 most prevalent chronic health conditions (Table 1).

The Rasch rating scale model (RSM) was used to calibrate the responses on the five items and the partial credit model (PCM) for the categorized VAS scores. Fit of the six items to the Rasch model was assessed by using the INFIT mean square (INFIT MNSQ <1.4).

Figures: Gender-related DIF with VAS - 2002, and Disease-related DIF with VAS - 2003. The x-axis shows the EQ-5D items and the y-axis is the DIF measure by DIF grouping. (p<0.01).

Results: There was significant gender-related DIF (p < 0.01) on the EQ 5D "anxiety/depression" mental health item and significant disease-related DIF (p < 0.01) "anxiety/depression" for respondents diagnosed with depression or anxiety, with or without the VAS, in both years. Responses from the VAS consistently fit the Rasch model (INFIT MNSQ < 1.4) over the two time points and across all ten disease groups.

Misfit was shown by the "anxiety/depression" mental health item, esp. with 2002 data; and improved fit in 2003, esp. with the inclusion of VAS. Analyses using a gender-split on the "anxiety/depression" item improved fit to the model among males (in 8 out of 10 first year and 9 out of 10 second year disease groups). When enhanced by the inclusion of the VAS, the EQ-5D descriptive system exhibited satisfactory Rasch measurement qualities and further enhancement was achieved by purging the gender and disease effects.

Table 1. Respondents (N = 2,057)
Mean age (SD) 52.05 (16.53)
 n% n%
Race  Disease  
VAS  Back Disorder15911.13
0-20492.38Joint Disorder805.60
21-30502.43Chronic sinusitis795.53

Results compared across both years revealed the crucial measurement property of invariance for the EQ-5D. The findings suggest that 1) the EQ-5D descriptive system and the EQ-VAS can be combined together to provide an overall measure of HRQoL and, 2) together they might serve as a suitable measurement framework for deriving population preference-weights.

Ning Yan Gu, Pharmerit North America, LLC, Bethesda, Maryland USA

Trevor G. Bond, School of Education, James Cook University, Townsville, Queensland, Australia

Benjamin M. Craig, Health Outcomes and Behaviors, Moffitt Cancer Center, Tampa, Florida USA

Reference: The EuroQol group (1990) "EuroQol a new facility for the measurement of health related quality of life." Health Policy, 16,199-208.

Based on a poster presented at 26th Plenary meeting of the EuroQol Group , Paris, France, September 3rd - 5th, 2009

Gu N.Y., Bond T.G., Craig B.M. (2009) (EQ-5D + VAS) x Rasch = HRQoL Measure, Rasch Measurement Transactions, 2009, 23:3, 1215-1216

Please help with Standard Dataset 4: Andrich Rating Scale Model

Rasch Publications
Rasch Measurement Transactions (free, online) Rasch Measurement research papers (free, online) Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch Applying the Rasch Model 3rd. Ed., Bond & Fox Best Test Design, Wright & Stone
Rating Scale Analysis, Wright & Masters Introduction to Rasch Measurement, E. Smith & R. Smith Introduction to Many-Facet Rasch Measurement, Thomas Eckes Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr. Statistical Analyses for Language Testers, Rita Green
Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar Journal of Applied Measurement Rasch models for measurement, David Andrich Constructing Measures, Mark Wilson Rasch Analysis in the Human Sciences, Boone, Stave, Yale
in Spanish: Análisis de Rasch para todos, Agustín Tristán Mediciones, Posicionamientos y Diagnósticos Competitivos, Juan Ramón Oreja Rodríguez

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