The national prevalence of dialysis in China has not been well studied. We aimed to estimate the prevalence of patients receiving dialysis and predict the trend using claims data in order to provide evidence for developing prevention strategies.
Cross-sectional study of insurance claims.
Medical claims data from Jan 1, 2013 to Dec 31, 2017 were extracted from a large claims database, using a two-stage sampling design to obtain a national sample covered by the urban basic medical insurance, the most predominant insurance program in China.
Patients receiving maintenance dialysis, including hemodialysis (HD) and peritoneal dialysis (PD), were identified according to medical billing data and ICD-10 codes.
The age- and sex-standardized population prevalence of kidney disease treated with dialysis was estimated by year and treatment modality.
Crude and age- and sex-standardized prevalence of kidney disease treated with dialysis were calculated stratified by year and treatment modality. The grey Verhulst model was used to predict dialysis prevalence from 2018 to 2025.
The age-and sex-standardized prevalence of dialysis patients increased from 255.11 per million population (PMP) in 2013 to 419.39 PMP in 2017. The age- and sex-standardized prevalence of HD and PD in 2017 were 384.41 PMP and 34.98 PMP, respectively, and the total number of dialysis patients in China was estimated to be 581,273. The prevalence of dialysis was predicted to rise beyond 2017 levels with a predicted prevalence of 534.60 PMP in 2020 and 629.67 PMP in 2025, corresponding to 744,817 and 874,373 patients, respectively.
Claims data have potential errors in classification of patients and population selection bias may have limited inferences to the entire Chinese population.
The prevalence of kidney disease treated with dialysis has risen between 2013 and 2017 in China and is predicted to increase further through 2025. These findings highlight the importance of prevention and control strategies to reduce the escalating burden of kidney failure.

Copyright © 2021. Published by Elsevier Inc.

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