Improved FMEA Methods for Proactive Healthcare Risk Analysis

Healthcare risk management.- FMEA in healthcare: A literature review.- FMEA with cloud model and hierarchical TOPSIS method.- FMEA using interval 2-tuple hybrid weighted distance measure.- FMEA using interval 2-tuple linguistic GRA method.- FMEA based on fuzzy set theory and MULTIMOORA method.- FMEA with interval-valued intuitionistic fuzzy hybrid MCDM approach.- FMEA using combination weighting and fuzzy VIKOR method.- FMEA using interval-valued intuitionistic fuzzy sets and MABAC method.- FMEA based on cluster analysis and prospect theory.- FMEA using interval 2-tuple linguistic variables and ELECTRE method.- FMEA using cloud model theory and PROMETHEE method.- FMEA using hesitant 2-tuple linguistic term sets and QUALIFLEX method.

Hu-Chen Liu received his M.Sc. degree in Industrial Engineering from Tongji University, Shanghai, China, in 2010, and his Ph.D. degree in Industrial Engineering and Management from Tokyo Institute of Technology, Japan, in 2013. He is currently a Professor at the School of Management, Shanghai University. His main research interests include quality and reliability management, Petri net theory and applications, and healthcare operation management. He has published more than 100 papers in these areas in leading journals, such as IIE Transactions, IEEE Transactions on Reliability, IEEE Transactions on Cybernetics, IEEE Transactions on Knowledge and Data Engineering, Reliability Engineering & System Safety, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Engineering Management, International Journal of Production Economics, and International Journal of Production Research.Dr. Liu is a senior member of the IEEE Society and the IISE Association. He is a member of the INFORMSand the China Association for Quality. He has accomplished and undertaken over 10 scientific research projects at both national and provincial levels, including National Natural Science of Foundation of China, Shanghai Young Eastern Scholar, and Shanghai Youth Top-Notch Talent.