Michael D Clark1, Ala Szczepura2, Anil Gumber3, Kirsten Howard4, Domenico Moro5, Rachael L Morton6. 1. Norwich Medical School, University of East Anglia, Norwich, UK. 2. Faculty of Health & Life Sciences, Coventry University, Coventry, UK. 3. Centre for Health and Social Care Research, Sheffield Hallam University, Sheffield, UK. 4. Sydney School of Public Health, The University of Sydney, Camperdown, NSW, Australia. 5. Department of Economics, University of Birmingham, Birmingham, UK. 6. NHMRC Clinical Trials Centre, Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia.
Abstract
Background: Discrete choice experiment (DCE), conjoint analysis or adaptive conjoint analysis methods are increasingly applied to obtain patient, clinician or community preferences in nephrology. This study systematically reviews the above-mentioned published choice studies providing an overview of the issues addressed, methods and findings. Methods: Choice studies relating to nephrology were identified using electronic databases, including Medline, Embase, PsychINFO and Econlit from 1990 to 2015. For inclusion in the review, studies had to primarily relate to kidney disease and include results from statistical (econometric) analyses of respondents' choice or preference. Studies meeting the inclusion criteria were assessed against a range of systematic review criteria, and methods and results summarized. Results: We identified 14 eligible studies from Europe, Australasia, North America and Asia, reporting preferences for treatment or screening, patient experiences, quality of life (QOL), health outcomes and priority-setting frameworks. Specific contexts included medical interventions in kidney transplantation and renal cell carcinoma, health policies for organ donation and allocation, dialysis modalities and end-of-life care, using a variety of statistical models. The characteristics of 'time' (i.e. transplant waiting time, dialysis hours, transport time) and QOL (pre- and post-transplant, or pre- and post-dialysis) consistently influenced patient and clinician preferences across the choice studies. Conclusions: DCE are increasingly used to obtain information about key preferences in kidney transplantation and dialysis. These study methods provide quantitative information about respondents' trade-offs between conflicting clinical and policy objectives, and can establish how preferences vary among stakeholder groups.
Background: Discrete choice experiment (DCE), conjoint analysis or adaptive conjoint analysis methods are increasingly applied to obtain patient, clinician or community preferences in nephrology. This study systematically reviews the above-mentioned published choice studies providing an overview of the issues addressed, methods and findings. Methods: Choice studies relating to nephrology were identified using electronic databases, including Medline, Embase, PsychINFO and Econlit from 1990 to 2015. For inclusion in the review, studies had to primarily relate to kidney disease and include results from statistical (econometric) analyses of respondents' choice or preference. Studies meeting the inclusion criteria were assessed against a range of systematic review criteria, and methods and results summarized. Results: We identified 14 eligible studies from Europe, Australasia, North America and Asia, reporting preferences for treatment or screening, patient experiences, quality of life (QOL), health outcomes and priority-setting frameworks. Specific contexts included medical interventions in kidney transplantation and renal cell carcinoma, health policies for organ donation and allocation, dialysis modalities and end-of-life care, using a variety of statistical models. The characteristics of 'time' (i.e. transplant waiting time, dialysis hours, transport time) and QOL (pre- and post-transplant, or pre- and post-dialysis) consistently influenced patient and clinician preferences across the choice studies. Conclusions: DCE are increasingly used to obtain information about key preferences in kidney transplantation and dialysis. These study methods provide quantitative information about respondents' trade-offs between conflicting clinical and policy objectives, and can establish how preferences vary among stakeholder groups.
Authors: Jennifer E Flythe; Derek Forfang; Nieltje Gedney; David M White; Caroline Wilkie; Kerri L Cavanaugh; Raymond C Harris; Mark Unruh; Grace Squillaci; Melissa West; Carol Mansfield; Cindy S Soloe; Katherine Treiman; Dallas Wood; Frank P Hurst; Carolyn Y Neuland; Anindita Saha; Murray Sheldon; Michelle E Tarver Journal: Kidney360 Date: 2022-05-05
Authors: Tess E Cooper; Amy Dalton; Anh Kieu; Martin Howell; Sumedh Jayanti; Rabia Khalid; Wai H Lim; Nicole Scholes-Robertson; Jonathan C Craig; Armando Teixeira-Pinto; Michael J Bourke; Allison Tong; Germaine Wong Journal: BMC Nephrol Date: 2021-11-21 Impact factor: 2.388
Authors: John M Humphrey; Violet Naanyu; Katherine R MacDonald; Kara Wools-Kaloustian; Gregory D Zimet Journal: PLoS One Date: 2019-10-30 Impact factor: 3.752