Abstract: Objective To analyze the related markers for cost and hemodialysis quality in hemodialysis patients in a local area in 2013 via big data analyses. Method Maintenance hemodialysis patients in 2013 were screened out from medical cost database in this area. Target population was divided into urban worker group
and urban and rural resident group according to their medical insurance type. Results There was significant difference in total cost between hemodialysis patients in urban worker group and urban and rural resident group (t=23.107, P<0.001). Some biased data existed in hospitalization and rehospitalization, vascular access operation, blood transmissible disease, cost proportion for use of hemoperfusion apparatus and drug in certain hospitals, suggesting the potential risks for quality control in some hemodialysis centers. Conclusion Big data analytical method for cost-centered database can detect possible cost bias and medical quality defects, hopefully providing the data useful for the continuous hemodialysis quality improvement.

Key words: Hemodialysis, Cost, Quality evaluation, Big data