Evaluating Surgical Risk Using FMEA and MULTIMOORA Methods under a Single-Valued Trapezoidal Neutrosophic Environment

Abstract

Background

Human errors during operations may seriously threaten patient recovery and safety and affect the doctor–patient relationship. Therefore, risk evaluation of the surgical process is critical. Risk evaluation by failure mode and effect analysis (FMEA) is a prospective technology that can identify and evaluate potential failure modes in the surgical process to ensure surgical quality and patient safety. In this study, a hybrid surgical risk–evaluation model was proposed using FMEA and multiobjective optimization on the basis of ratio analysis plus full multiplicative form (MULTIMOORA) method under a single-valued trapezoidal neutrosophic environment. This work aimed to determine the most critical risk points during the surgical process and analyze corresponding solutions.

Methods

A team for FMEA was established from domain experts from different departments in a hospital in Hunan Province. Single-valued trapezoidal neutrosophic numbers (SVTNNs) were used to evaluate potential risk factors in the surgical process. Cmprehensive weights combining subjective and objective weights were determined by the best–worst method and entropy method to differentiate the importance of risk factors. The SVTNN–MULTIMOORA method was utilized to calculate the risk-priority order of failure modes in a surgical process.

Results

The hybrid FMEA model under the SVTNN–MULTIMOORA method was used to calculate the ranking of severity of 21 failure modes in the surgical process. An unclear diagnosis is the most critical failure in the surgical process of a hospital in Hunan Province.

Conclusion

The proposed model can identify and evaluate the most critical potential failure modes of the surgical process effectively. In addition, such a model can help hospitals to reduce surgical risk and improve the safety of surgery.

Keywords:

• failure mode and effect analysis
• surgical process
• MULTIMOORA
• best–worst method
• single-valued trapezoidal neutrosophic numbers

Acknowledgments

This work was supported by the Human Philosophy Social Science Fund Projects (No. 18YBA150), the Key Project of Hunan Education Department (No. 18A201), Project of Hunan Federation of Social Sciences (No. XSP20YBC318), and the Hunan Provincial Natural Science Fund (Nos. 2018JJ5004, 2019JJ40088, and 2019JJ40479).

Disclosure

Peng-Fei Cheng reports grants and personal fees from the Department of Science and Technology of Hunan Province, Social Science Planning Office of Hunan Province, and the Department of Education of Hunan Province. Ji-Qun He reports grants and personal fees from the Hunan Provincial Natural Science Fund and Hunan Federation of Social Sciences during the study. The authors declare that they have no other possible conflicts of interest.