Nigar Sekercioglu1, Bryan Curtis2,3, Sean Murphy2,3, Gord Blackhouse4, Brendan Barrett2,3. 1. Department of Clinical Epidemiology, Faculty of Medicine, Memorial University, 300 Prince Philip Drive, St. John's, NL, Canada. nigars2003@yahoo.com. 2. Department of Clinical Epidemiology, Faculty of Medicine, Memorial University, 300 Prince Philip Drive, St. John's, NL, Canada. 3. Division of Nephrology, Faculty of Medicine, Memorial University, 300 Prince Philip Drive, St. John's, NL, Canada. 4. Programs for Assessment of Technology in Health, McMaster University, 3 Charlton Ave E, 2nd Floor, Hamilton, ON, L8N 1Y3, Canada.
Abstract
INTRODUCTION: Coverage decisions in publicly funded healthcare systems require a formal, systematic and transparent assessment process for policies related to distribution of resources. The process is complex and employs multiple types of information, such as clinical effectiveness, costs and health utility scores which are used to produce quality-adjusted life years. The purpose of this study was to create health utility scores for CKD patients within the Canadian population. METHODS: This is a cross-sectional study of CKD patients. We administered the Short-Form 36 Quality of Life Questions to all participants and employed the Short-Form 6 Dimension index to create health utility scores which were created using a set of parametric preference weights, nonparametric preference weights and ordinal health state valuation techniques obtained from a sample of the general population. RESULTS: Utility values in the dialysis group were lower than in the non-dialysis group. There was a significant relationship between age and health utility scores: As age increases, health utility scores decrease. Diabetes was associated with lower health utility scores in dialysis patients, whereas other covariates did not reach levels of statistical significance in our stepwise regression models. The parametric Bayesian model and standard gamble approach yielded the same results, while the correlation between the nonparametric and parametric methods was above 0.9. CONCLUSION: Health utility scores were low relative to the general population norm in our study cohort. Longitudinal assessment of CKD patients to capture possible fluctuations in health utility scores may add useful information.
INTRODUCTION: Coverage decisions in publicly funded healthcare systems require a formal, systematic and transparent assessment process for policies related to distribution of resources. The process is complex and employs multiple types of information, such as clinical effectiveness, costs and health utility scores which are used to produce quality-adjusted life years. The purpose of this study was to create health utility scores for CKDpatients within the Canadian population. METHODS: This is a cross-sectional study of CKDpatients. We administered the Short-Form 36 Quality of Life Questions to all participants and employed the Short-Form 6 Dimension index to create health utility scores which were created using a set of parametric preference weights, nonparametric preference weights and ordinal health state valuation techniques obtained from a sample of the general population. RESULTS: Utility values in the dialysis group were lower than in the non-dialysis group. There was a significant relationship between age and health utility scores: As age increases, health utility scores decrease. Diabetes was associated with lower health utility scores in dialysis patients, whereas other covariates did not reach levels of statistical significance in our stepwise regression models. The parametric Bayesian model and standard gamble approach yielded the same results, while the correlation between the nonparametric and parametric methods was above 0.9. CONCLUSION: Health utility scores were low relative to the general population norm in our study cohort. Longitudinal assessment of CKDpatients to capture possible fluctuations in health utility scores may add useful information.
Authors: Christopher McCabe; John Brazier; Peter Gilks; Aki Tsuchiya; Jennifer Roberts; Anthony O'Hagan; Katherine Stevens Journal: J Health Econ Date: 2006-02-24 Impact factor: 3.883
Authors: M Gonzalez-Saenz de Tejada; A Bilbao; M Baré; E Briones; C Sarasqueta; J M Quintana; A Escobar Journal: Psychooncology Date: 2015-11-18 Impact factor: 3.894