Applying Healthcare Failure Mode & Effect Analysis to Patient Pain Management in the Anesthesia Recovery Period: An Evaluative Case Study


Pain can be the worst feeling experienced by patients, and it is also among the most common and most serious forms expressing uncomfortable feelings. In nursing practice, pain is seen as the fifth key vital sign in addition to body temperature, pulse, respiration and blood pressure and is increasingly valued.  Statistically, obvious post-operative pain occurs in 75% of surgical patients. Poor management of postoperative pain can cause complications of the respiratory and cardiovascular systems and adversely influence postoperative rehabilitation.

To reduce (alleviate) patients' postoperative pain, we applied HFMEA for patient pain management during the anaesthesia recovery period. HFMEA is a team-based, systemic and prospective crisis analysis approach. As a quality improvement process, HFMEA represents a new management concept that can be described as “getting all things done at once”  to prevent failures before malfunctions occurs and eliminate or reduce the occurrence of potential failure modes to make designs and programs more secure. Identifying and analyzing the potential causes of the problems and then solving those problems enables the goal of quality improvement to be achieved. The American Pain Society (APS) proposed that through quality improvement, pain management can be improved.


This study aims to standardise pain management in the anaesthesia recovery period and improve the effects of analgesia on acute post-operative pain.


Using healthcare failure mode and effect analysis (HFMEA), we analyzed the primary cause of patients' pain and subsequently determined the process and risk priority number (RPN).


Actions were taken to improve patients' pain. After using HFMEA, the experimental group's visual analogue scale (VAS) scores were lower than those of the control group at 1 h and at discharge from the post-anaesthetic intensive care unit (PAICU). The differences were statistically significant (P < 0.05).


The application of failure mode and effect analysis can relieve pain and improve the quality of nursing.

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