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. 2011 Mar-Apr;31(2):260-9.
doi: 10.1177/0272989X10380925. Epub 2010 Oct 8.

Standard error of measurement of 5 health utility indexes across the range of health for use in estimating reliability and responsiveness

Mari Palta  1 , Han-Yang Chen  2 , Robert M Kaplan  3 , David Feeny  4 , Dasha Cherepanov  3 , Dennis G Fryback  1
Affiliations

Standard error of measurement of 5 health utility indexes across the range of health for use in estimating reliability and responsiveness

Mari Palta et al. Med Decis Making. 2011 Mar-Apr.

Abstract

Background: Standard errors of measurement (SEMs) of health-related quality of life (HRQoL) indexes are not well characterized. SEM is needed to estimate responsiveness statistics, and is a component of reliability.

Purpose: To estimate the SEM of 5 HRQoL indexes.

Design: The National Health Measurement Study (NHMS) was a population-based survey. The Clinical Outcomes and Measurement of Health Study (COMHS) provided repeated measures.

Subjects: A total of 3844 randomly selected adults from the noninstitutionalized population aged 35 to 89 y in the contiguous United States and 265 cataract patients.

Measurements: The SF6-36v2™, QWB-SA, EQ-5D, HUI2, and HUI3 were included. An item-response theory approach captured joint variation in indexes into a composite construct of health (theta). The authors estimated 1) the test-retest standard deviation (SEM-TR) from COMHS, 2) the structural standard deviation (SEM-S) around theta from NHMS, and 3) reliability coefficients.

Results: SEM-TR was 0.068 (SF-6D), 0.087 (QWB-SA), 0.093 (EQ-5D), 0.100 (HUI2), and 0.134 (HUI3), whereas SEM-S was 0.071, 0.094, 0.084, 0.074, and 0.117, respectively. These yield reliability coefficients 0.66 (COMHS) and 0.71 (NHMS) for SF-6D, 0.59 and 0.64 for QWB-SA, 0.61 and 0.70 for EQ-5D, 0.64 and 0.80 for HUI2, and 0.75 and 0.77 for HUI3, respectively. The SEM varied across levels of health, especially for HUI2, HUI3, and EQ-5D, and was influenced by ceiling effects. Limitations. Repeated measures were 5 mo apart, and estimated theta contained measurement error.

Conclusions: The 2 types of SEM are similar and substantial for all the indexes and vary across health.

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Figures

Figure 1
Figure 1
Bland-Altman plots of SF6D_36v2 values at 6 months minus 1 month post cataract surgery (open circles) versus mean of same values. Intervals expected to contain 95% of points (solid circles) based on adjusted SEM-S estimated from the NHMS are superimposed.
Figure2
Figure2
Bland-Altman plots of QWB-SA values at 6 months minus 1 month post cataract surgery (open circles) versus mean of same values. Intervals expected to contain 95% of points (solid circles) based on adjusted SEM-S estimated from the NHMS are superimposed.
Figure 3
Figure 3
Bland-Altman plots of EQ-5D values at 6 months minus 1 month post cataract surgery (open circles) versus mean of same values. Intervals expected to contain 95% of points (solid circles) based on adjusted SEM-S estimated from the NHMS are superimposed.
Figure 4
Figure 4
Bland-Altman plots of HUI2 values at 6 months minus 1 month post cataract surgery (open circles) versus mean of same values. Intervals expected to contain 95% of points (solid circles) based on adjusted SEM-S estimated from the NHMS are superimposed.
Figure 5
Figure 5
Bland-Altman plots of HUI3 values at 6 months minus 1 month post cataract surgery (open circles) versus mean of same values. Intervals expected to contain 95% of points (solid circles) based on adjusted SEM-S estimated from the NHMS are superimposed.
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