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Utilization of a healthcare failure mode and effects analysis to identify error sources in the preanalytical phase in two tertiary hospital laboratories.

Utilization of a healthcare failure mode and effects analysis to identify error sources in the preanalytical phase in two tertiary hospital laboratories.

Biochem Med (Zagreb). 2018 Jun 15;28(2):020713

Authors: Romero A, Gómez-Salgado J, Romero-Arana A, Ruiz-Frutos C

Abstract
Introduction: The presence of errors in the preanalytical phase is a thoroughly studied problem. A strategy to increase their source detection might be the use of the Healthcare Failure Mode and Effects Analysis (HFMEA). The aim of this study is improving the capacity of identifying sources of error during the preanalytical period in samples provided by primary care clinics (PCC) with the use of the HFMEA as a tool in the laboratories of two tertiary hospitals.
Materials and methods: A HFMEA was carried out in each laboratory, by means of the creation of groups of experts with similar characteristics (doctors and nurses from PCC and laboratory, support staff, and laboratory technicians). The Risk Priority Number (RPN) was calculated.
Results: Items with elevated RPN were presented in both centers. The highest RPN were in LAB1: “two request notes for a patient” and “the segregation of oncology urgent samples” (both with 384), while in LAB2 was “the lack of information in patients with oral glucose overload test” (RPN 576). Considering the different steps in the preanalytical phase, LAB1 paid attention in sampling, samples reception and the programming in the Laboratory Information System, while LAB2 paid attention in the request form, the appointment system, sampling procedures, transport and reception.
Conclusion: The laboratories prioritized the problems differently. However, both centers offer solutions to these possible sources of error. We proposed improvement actions that can be resolved easily, with a low cost for the system, mainly to schedule a specific formative programme and a deep revision of the existing protocols.

PMID: 30022888 [PubMed – in process]

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