Nephrology Dialysis Transplantation, Vol 12, Issue 12 2512-2516, Copyright © 1997 by Oxford University Press
R Davies and P Roderick
Background: The purpose of the study was to estimate
the future demand for renal replacement therapy in England. Simulation
modelling was used to estimate the future demand, under varying
assumptions, about the growth in the acceptance rate for renal replacement
therapy, patient and treatment survival, and the availability of kidney
transplants. Methods: Data were obtained from the
National Renal Review, the European Dialysis and Transplant Registry, and
the United Kingdom Transplant Support Services Authority. They were
analysed to provide transfer and survival data on patients treated for
end-stage renal failure in England and in four exemplary district health
authorities. The simulation runs provided estimates of numbers of patients
being treated by dialysis and transplantation over the next 15 years.
Results: The results indicated that the number under
treatment was predicted to rise by between 50 and 100% over the next 15
years, with a disproportionate increase in dialysis of up to 150%. There
will be more 'high-risk elderly' people under treatment, particularly
amongst the dialysis patients. The growth in numbers will vary between
districts depending on their level of need and current service position.
Conclusion: There will be increasing numbers of
patients, particularly elderly patients with associated comorbidity,
receiving treatment. Given the shortage of kidneys for transplantation, the
demand will fall on haemodialysis and continuous ambulatory peritoneal
dialysis facilities. Purchasers are thus faced with steeply rising costs
for this patient group, especially in areas of high need, whilst needing to
find improvements in their quality of care. Key words:
ageing population; computer simulation ethnic minorities; planning;
predicting demand; renal replacement therapy
DIALYSIS AND TRANSPLANTATION NEWS
Predicting the future demand for renal replacement therapy in England using simulation modelling
Wessex Institute of Health Research and Development, University of Southampton, UK; Corresponding author at: School of Management, Highfield, University of Southampton, Southampton SO17 1BJ, UK
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