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Using the failure mode and effects analysis model to improve parathyroid hormone and adrenocorticotropic hormone testing

BACKGROUND: Risk management in health care systems applies to all hospital employees and directors as they deal with human life and emergency routines. There is a constant need to decrease risk and increase patient safety in the hospital environment. The purpose of this article is to review the labo...

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Detalles Bibliográficos
Autores principales: Magnezi, Racheli, Hemi, Asaf, Hemi, Rina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5144891/
https://www.ncbi.nlm.nih.gov/pubmed/27980440
http://dx.doi.org/10.2147/RMHP.S117472
Descripción
Sumario:BACKGROUND: Risk management in health care systems applies to all hospital employees and directors as they deal with human life and emergency routines. There is a constant need to decrease risk and increase patient safety in the hospital environment. The purpose of this article is to review the laboratory testing procedures for parathyroid hormone and adrenocorticotropic hormone (which are characterized by short half-lives) and to track failure modes and risks, and offer solutions to prevent them. During a routine quality improvement review at the Endocrine Laboratory in Tel Hashomer Hospital, we discovered these tests are frequently repeated unnecessarily due to multiple failures. The repetition of the tests inconveniences patients and leads to extra work for the laboratory and logistics personnel as well as the nurses and doctors who have to perform many tasks with limited resources. METHODS: A team of eight staff members accompanied by the Head of the Endocrine Laboratory formed the team for analysis. The failure mode and effects analysis model (FMEA) was used to analyze the laboratory testing procedure and was designed to simplify the process steps and indicate and rank possible failures. RESULTS: A total of 23 failure modes were found within the process, 19 of which were ranked by level of severity. The FMEA model prioritizes failures by their risk priority number (RPN). For example, the most serious failure was the delay after the samples were collected from the department (RPN =226.1). CONCLUSION: This model helped us to visualize the process in a simple way. After analyzing the information, solutions were proposed to prevent failures, and a method to completely avoid the top four problems was also developed.