Your browser doesn't support javascript.
loading
Projecting the future: modelling Australian dialysis prevalence 2021-30.
Keuskamp, Dominic; Davies, Christopher E; Irish, Georgina L; Jesudason, Shilpanjali; McDonald, Stephen P.
Afiliación
  • Keuskamp D; Australia & New Zealand Dialysis & Transplant Registry, South Australian Health & Medical Research Institute, Adelaide, SA, Australia; and Faculty of Health & Medical Sciences, University of Adelaide, Adelaide, SA, Australia.
  • Davies CE; Australia & New Zealand Dialysis & Transplant Registry, South Australian Health & Medical Research Institute, Adelaide, SA, Australia; and Faculty of Health & Medical Sciences, University of Adelaide, Adelaide, SA, Australia.
  • Irish GL; Australia & New Zealand Dialysis & Transplant Registry, South Australian Health & Medical Research Institute, Adelaide, SA, Australia; and Faculty of Health & Medical Sciences, University of Adelaide, Adelaide, SA, Australia; and Central Northern Adelaide Renal & Transplantation
  • Jesudason S; Australia & New Zealand Dialysis & Transplant Registry, South Australian Health & Medical Research Institute, Adelaide, SA, Australia; and Faculty of Health & Medical Sciences, University of Adelaide, Adelaide, SA, Australia; and Central Northern Adelaide Renal & Transplantation
  • McDonald SP; Australia & New Zealand Dialysis & Transplant Registry, South Australian Health & Medical Research Institute, Adelaide, SA, Australia; and Faculty of Health & Medical Sciences, University of Adelaide, Adelaide, SA, Australia; and Central Northern Adelaide Renal & Transplantation
Aust Health Rev ; 47(3): 362-368, 2023 Jun.
Article en En | MEDLINE | ID: mdl-37188536
Objectives To project the prevalence of people receiving dialysis in Australia for 2021-30 to inform service planning and health policy. Methods Estimates were based on data from 2011 to 2020 from the Australia & New Zealand Dialysis & Transplant (ANZDATA) Registry and the Australian Bureau of Statistics. We projected dialysis and functioning kidney transplant recipient populations for the years 2021-30. Discrete-time, non-homogenous Markov models were built on probabilities for transition between three mutually exclusive states (Dialysis, Functioning Transplant, Death), for five age groups. Two scenarios were employed - stable transplant rate vs a continued increase - to assess the impact of these scenarios on the projected prevalences. Results Models projected a 22.5-30.4% growth in the dialysis population from 14 554 in 2020 to 17 829 ('transplant growth') - 18 973 ('transplant stable') by 2030. An additional 4983-6484 kidney transplant recipients were also projected by 2030. Dialysis incidence per population increased and dialysis prevalence growth exceeded population ageing in 40-59 and 60-69 year age groups. The greatest dialysis prevalence growth was seen among those aged ≥70 years. Conclusion Modelling of the future prevalence of dialysis use highlights the increasing demand on services expected overall and especially by people aged ≥70 years. Appropriate funding and healthcare planning must meet this demand.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Trasplante de Riñón / Fallo Renal Crónico Tipo de estudio: Prevalence_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Oceania Idioma: En Revista: Aust Health Rev Año: 2023 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Trasplante de Riñón / Fallo Renal Crónico Tipo de estudio: Prevalence_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Oceania Idioma: En Revista: Aust Health Rev Año: 2023 Tipo del documento: Article País de afiliación: Australia