Using the failure mode and effects analysis model to improve parathyroid hormone and adrenocorticotropic hormone testing
Authors Magnezi R, Hemi A, Hemi R
Received 18 July 2016
Accepted for publication 5 November 2016
Published 1 December 2016 Volume 2016:9 Pages 271—274
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Colin Mak
Peer reviewer comments 2
Editor who approved publication: Professor Frank Papatheofanis
Racheli Magnezi,1 Asaf Hemi,1 Rina Hemi2
1Department of Management, Public Health and Health Systems Management Program, Bar Ilan University, Ramat Gan, 2Endocrine Service Unit, Sheba Medical Center, Tel Aviv, Israel
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.
Keywords: failure mode and effect analysis (FMEA), laboratory medicine, team work, rank failures, test repetition
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