Application of failure mode and effect analysis in ICU admission of potentially COVID-19 infected patients

Mao Ye; Fuqin Tang; Ching-Wen Chien; Yen-Ching Chuang; James J H Liou; Xixi Qu

doi:10.1016/j.ajic.2023.12.012

Application of failure mode and effect analysis in ICU admission of potentially COVID-19 infected patients

Am J Infect Control. 2024 May;52(5):552-562. doi: 10.1016/j.ajic.2023.12.012. Epub 2023 Dec 22.

Authors

Mao Ye¹, Fuqin Tang², Ching-Wen Chien³, Yen-Ching Chuang⁴, James J H Liou⁵, Xixi Qu⁶

Affiliations

¹ Department of Intensive Care Unit, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, China.
² Nursing Department, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China.
³ Institute for Hospital Management, Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, China.
⁴ Business College, Taizhou University, Taizhou, Zhejiang, China; Institute of Public Health and Emergency Management, Taizhou University, Taizhou, Zhejiang, China; Key Laboratory of evidence-based Radiology of Taizhou, Linhai, Zhejiang, China. Electronic address: yenching.chuang@gmail.com.
⁵ Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, Taiwan. Electronic address: jamesjhliou@gmail.com.
⁶ Department of Intensive Care Unit, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, China. Electronic address: xi380464933@yeah.net.

PMID: 38142777
DOI: 10.1016/j.ajic.2023.12.012

Abstract

Background: To analyze the admission and treatment process of potentially COVID-19-infected patients in the intensive care unit under normalization, prevention, and control of the pandemic.

Methods: A multidisciplinary team was assembled to develop a flowchart of potentially COVID-19-infected patients admitted to the intensive care unit and identify potential failure steps and modes throughout the process using the failure mode and effect analysis method. Through risk priority number (RPN) analysis of each failure mode, those with the highest impact on nosocomial infection were identified, and the priority of implementation was determined. Related corrective measures have been developed to continuously improve clinical practice and management.

Results: Eighty potential failure modes were identified, and 8 potential failure modes were identified with RPNs greater than 100. These high RPNs of the failure modes were associated with careless inquiries of epidemiological histories by nurses, inadequate implementation of management standards by nursing assistants, and exposure of attending physicians to potentially risky environments. Finally, 18 general corrective measures are proposed.

Conclusions: Application of the failure mode and effect analysis method for quality improvement is a powerful tool for predicting potential failures in the process and can suggest corrective measures that could help avoid nosocomial infection during a pandemic.

Keywords: Admission and treatment process; Potential failure mode; Potentially infected patients; Risk analysis.