Carlos K H Wong1, Elegance T P Lam, Cindy L K Lam. 1. Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F, Ap Lei Chau Clinic, 161 Ap Lei Chau Main Street, Ap Lei Chau, Hong Kong Island, Hong Kong, carlosho@hku.hk.
Abstract
PURPOSE: The short form six dimensions (SF-6D) are derived from the SF-36 Health Survey with the intention that item data of the latter are often converted to a preference value, which was subsequently used in economic evaluations of interventions. The aim was to compare the equivalence and sensitivity of health preference values derived from the SF-36/SF-12 Health Surveys to that measured directly by the SF-6D for chronic hepatitis B (CHB) patients. METHODS: This was a secondary analysis of the SF-6D and SF-36 data from a baseline sample of 589 patients with CHB infection with different stages of liver diseases. Degree of agreement (equivalence) between direct-measured and derived SF-6D values was determined using spearman correlation and intra-class correlation. Sensitivity and discriminative power of different SF-6D values were compared by standardized effect size and relative efficiency (RE) statistics. RESULTS: Significant differences in the direct-measured or derived SF-6D preference values were found between CHB groups. Degree of agreement between SF-6D values was satisfactory. Direct-measured SF-6D was the most efficient, followed by SF-12-derived and the SF-36-derived was the least, based on the standardized effect size and the RE statistics. Sensitivity and discriminative power of direct-measured SF-6D were superior to derived SF-6D among people with different CHB health states. CONCLUSIONS: Although direct-measured and derived SF-6D preference values had satisfactory sensitivity in discriminating between CHB groups, direct-measured SF-6D is the most sensitive and preferable method of obtaining health preference.
PURPOSE: The short form six dimensions (SF-6D) are derived from the SF-36 Health Survey with the intention that item data of the latter are often converted to a preference value, which was subsequently used in economic evaluations of interventions. The aim was to compare the equivalence and sensitivity of health preference values derived from the SF-36/SF-12 Health Surveys to that measured directly by the SF-6D for chronic hepatitis B (CHB) patients. METHODS: This was a secondary analysis of the SF-6D and SF-36 data from a baseline sample of 589 patients with CHB infection with different stages of liver diseases. Degree of agreement (equivalence) between direct-measured and derived SF-6D values was determined using spearman correlation and intra-class correlation. Sensitivity and discriminative power of different SF-6D values were compared by standardized effect size and relative efficiency (RE) statistics. RESULTS: Significant differences in the direct-measured or derived SF-6D preference values were found between CHB groups. Degree of agreement between SF-6D values was satisfactory. Direct-measured SF-6D was the most efficient, followed by SF-12-derived and the SF-36-derived was the least, based on the standardized effect size and the RE statistics. Sensitivity and discriminative power of direct-measured SF-6D were superior to derived SF-6D among people with different CHB health states. CONCLUSIONS: Although direct-measured and derived SF-6D preference values had satisfactory sensitivity in discriminating between CHB groups, direct-measured SF-6D is the most sensitive and preferable method of obtaining health preference.
Authors: Sammy Saab; Ayman B Ibrahim; Bijal Surti; Francisco Durazo; Steven Han; Hasan Yersiz; Douglas G Farmer; R Mark Ghobrial; Leonard I Goldstein; Myron J Tong; Ronald W Busuttil Journal: Liver Int Date: 2008-07-25 Impact factor: 5.828
Authors: Garry R Barton; Tracey H Sach; Anthony J Avery; Claire Jenkinson; Michael Doherty; David K Whynes; Kenneth R Muir Journal: Health Econ Date: 2008-07 Impact factor: 3.046
Authors: Adrian R Levy; Kris V Kowdley; Uchenna Iloeje; Eskinder Tafesse; Jayanti Mukherjee; Robert Gish; Natalie Bzowej; Andrew H Briggs Journal: Value Health Date: 2007-12-17 Impact factor: 5.725
Authors: Carlos K H Wong; William C W Wong; Eric Y F Wan; Winnie H T Wong; Frank W K Chan; Cindy L K Lam Journal: Health Qual Life Outcomes Date: 2015-08-12 Impact factor: 3.186