Economic and quality of care evaluation of dialysis service models in remote Australia: protocol for a mixed methods study

Abstract

BackgroundAustralia’s Northern Territory (NT) has the country’s highest incidence and prevalence of kidney disease. Indigenous people from remote areas suffer the heaviest disease burden. Concerns regarding cost and sustainability limit the provision of dialysis treatments in remote areas and most Indigenous people requiring dialysis relocate to urban areas. However, this dislocation of people from their family, community and support networks may prove more costly when the broader health, societal and economic consequences for the individual, family and whole of government are considered.MethodsThe Dialysis Models of Care Study is a large cross organisation mixed methods study. It includes a retrospective (2000–2014) longitudinal data linkage study of two NT cohorts: Renal Cohort 1- comprising approximately 2000 adults who received dialysis and Renal Cohort 2- comprising approximately 400 children of those adults. Linkage of administrative data sets from the Australian and New Zealand Dialysis and Transplant Registry, NT Departments of Health, Housing and Education by a specialist third party (SA/NT Datalink) will enable extraction of activity, financial and outcome data. Interviews with patients, clinicians and service providers, using a snowball technique, will canvass relevant issues and assist in determining the full costs and impacts of the five most used dialysis Models of Care.DiscussionThe study uses a mixed methods approach to investigate the quantitative and qualitative dimensions of the full costs and outcomes associated with the choice of particular dialysis models of care for any given patient. The study includes a large data linkage component that for the first time links health, housing and education data to fully analyse and evaluate the impact on patients, their families and the broader community, resulting from the relocation of people for treatment. The study will generate a large amount of activity, financial and qualitative data that will investigate health costs less directly related to dialysis treatment, costs to government such as housing and/or education and the health, social and economic outcomes experienced by patients. This approach fills an evidence gap critical to health service planners.