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National Health Measurement Study Dennis Fryback PI P01AG020679 Jeffrey W. Elias Ph.D - NIA. Project 1: Complete national survey benchmarking cross-sectional norms simultaneously on 5 Health Related QOL measures: SF36.v2 QWB-SA HUI2/3.
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NationalHealth Measurement StudyDennis Fryback PIP01AG020679Jeffrey W. Elias Ph.D - NIA DHHS/NIH/NIA/BSR
Project 1: Complete national survey benchmarking cross-sectional norms simultaneously on 5 Health Related QOL measures: • SF36.v2 QWB-SA HUI2/3. • EQ-5D & HALex
National Health Measurement Study • Project 1 (Leader Dennis Fryback _University of Wisconsin) • a) requires a computer assisted telephone interview (random digit dialed) of 2,800 non-institutionalized persons , age 35-89 to establish age-specific and gender norms (large subset of African Americans) simultaneously on the 5 HRQOL measures. • b) allows discrimination among common self-reported conditions and means and SD’s for persons reporting and not reporting each condition
National Health Measurement Study • c) Project 1 • will develop cross-walk regression equations between pairs of measures to eventually allow predictions of summary scores on each measure from the other measures. • d) will develop a public use data set.
National Health Measurement Study • Project 2 (Leader Robert Kaplan UCLA) • a) will compare measures of HRQOL in cohorts of patients with heart failure (N = 450) or cataracts N= 450). • b) evaluates the responsiveness of measures to change in status and treatment over time (1-6 months post intervention).
National Health Measurement Study • Project 3 (Leader Theodore Ganiats UCSD) • a) develop measures of symptom duration that patients think that are important for 5 disease states • b) quantitatively evaluate how symptom duration affects valuation of HRQOL via vignettes and HRQOL scales
National Health Measurement Study • Project 4 (Leader Ronald Hays UCLA) • a) assess impact of psychometric equivalence of mode of administration: self, mailed, telephone interview administered • b) examine central tendency, missing data, variance, reliability, item difficulty, item discrimination