Mari Palta1, Han-Yang Chen2, Robert M Kaplan3, David Feeny4, Dasha Cherepanov3, Dennis G Fryback1. 1. Department of Population Health Sciences, University of Wisconsin, Madison (MP, DGF) 2. Center for Urban Population Health, Milwaukee, Wisconsin (H-YC) 3. Department of Health Services, University of California, Los Angeles (RMK, DC) 4. Center for Health Research, Kaiser Permanente Northwest Region, Portland, Oregon (DF)
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.
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 cataractpatients. 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.
Authors: Chris Blanchard; David Feeny; Jeffrey L Mahon; Robert Bourne; Cecil Rorabeck; Larry Stitt; Susan Webster-Bogaert Journal: Qual Life Res Date: 2004-03 Impact factor: 4.147
Authors: David Feeny; William Furlong; George W Torrance; Charles H Goldsmith; Zenglong Zhu; Sonja DePauw; Margaret Denton; Michael Boyle Journal: Med Care Date: 2002-02 Impact factor: 2.983
Authors: Janel Hanmer; Dasha Cherepanov; Mari Palta; Robert M Kaplan; David Feeny; Dennis G Fryback Journal: Med Decis Making Date: 2015-08-27 Impact factor: 2.583
Authors: David Feeny; Karen Spritzer; Ron D Hays; Honghu Liu; Theodore G Ganiats; Robert M Kaplan; Mari Palta; Dennis G Fryback Journal: Med Decis Making Date: 2011-10-18 Impact factor: 2.583
Authors: Robert B Penfold; Jeffrey T Kullgren; Irina Miroshnik; Alison A Galbraith; Virginia L Hinrichsen; Tracy A Lieu Journal: BMC Health Serv Res Date: 2011-05-27 Impact factor: 2.655
Authors: Chris D Poole; Christian A Bannister; Jakob Nørgaard Andreasen; Jens Strodl Andersen; Craig J Currie Journal: Health Qual Life Outcomes Date: 2014-06-13 Impact factor: 3.186
Authors: J Shannon Swan; Inga T Lennes; Natalie N Stump; Jennifer S Temel; David Wang; Lisa Keller; Karen Donelan Journal: MDM Policy Pract Date: 2018-10-15