Survival of hemodialysis patients: modeling differences in risk of dialysis centers

被引:12
作者
Carvalho, MS
Henderson, R
Shimakura, S
Sousa, IPSC
机构
[1] Univ Lancaster, Dept Math & Stat, Lancaster, England
[2] Fiocruz MS, Natl Sch Publ Hlth, BR-21045900 Rio De Janeiro, Brazil
[3] Univ Fed Parana, Dept Estatist, BR-80060000 Curitiba, Parana, Brazil
关键词
health services assessment; renal replacement therapies; survival frailty models; STAGE RENAL-DISEASE; LIFE-TABLES; MORTALITY; ADEQUACY; FRAILTY;
D O I
10.1093/intqhc/mzg035
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Objective. Dialysis is the most common renal replacement therapy for patients with end stage renal disease. This paper considers survival of dialysis patients, aiming to assess quality of renal replacement therapy at dialysis centers in Rio de Janeiro, Brazil, and to investigate differences in survival between health facilities. Methods. A Cox proportional hazards model, allowing for time-varying covariates and prevalent data, was the basic method used to analyze the survival of 11 579 patients on hemodialysis in 67 health facilities in Rio de Janeiro State from January 1998 until August 2001, using data obtained from routine information systems. A frailty random effects model was applied to investigate differences in mortality between health centers not explained by measured characteristics. Results. The individual variables associated with the outcome were age and underlying disease, with diabetes being the main isolated risk factor. Considering covariates of the health unit, two factors were associated with performance: bigger units had on average better survival times than smaller ones and units which offered cyclic peritoneal dialysis performed less well than those that did not. There were significant frailty effects among centers, with relative risks varying between 0.24 and 3.15, and an estimated variance of 0.43. Conclusions. Routine assessment based on health registries of the outcome of any high technology medical treatment is extremely important in maintaining quality of care and in estimating the impact of changes in therapies, units, and patient profiles. The frailty model allowed estimation of variation in risk between centers not attributable to any measured covariates. This can be used to guide more specific investigation and changes in health policies related to renal transplant therapies.
引用
收藏
页码:189 / 196
页数:8
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