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An error taxonomy system for analysis of haemodialysis incidents
Xiuzhu Gu1, Kenji Itoh, Satoshi Suzuki
1Department of Industrial Engineering and Management, Graduate School of Decision Science and Technology, Tokyo Institute of Technology, Tokyo, Japan.
Objectives:
This paper describes the development of a haemodialysis error taxonomy system for analysing incidents and predicting the safety status of a dialysis organisation.
Methods:
The error taxonomy system was developed by adapting an error taxonomy system which assumed no specific specialty to haemodialysis situations. Its application was conducted with 1,909 incident reports collected from two dialysis facilities in Japan.
Results:
Over 70% of haemodialysis incidents were reported as problems or complications related to dialyser, circuit, medication and setting of dialysis condition. Approximately 70% of errors took place immediately before and after the four hours of haemodialysis therapy. Error types most frequently made in the dialysis unit were omission and qualitative errors. Failures or complications classified to staff human factors, communication, task and organisational factors were found in most dialysis incidents. Device/equipment/materials, medicine and clinical documents were most likely to be involved in errors. Haemodialysis nurses were involved in more incidents related to medicine and documents, whereas dialysis technologists made more errors with device/equipment/materials.
Conclusions:
This error taxonomy system is able to investigate incidents and adverse events occurring in the dialysis setting but is also able to estimate safety-related status of an organisation, such as reporting culture.
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