ABSTRACT
With the rise of accidental injury in India, it has become important to improve service quality in the healthcare industry, because any type of failure or error in the system significantly affects the safety of the patient as well as the goodwill of the hospital. An integrated failure mode and effect analysis (FMEA) and fuzzy logic rule-based inference model to study the different failure modes for risk assessment and to make corrective decisions were applied to this system. Under classical FMEA, risk priority numbers (RPNs) were tabulated using probability of occurrence (O), severity (S) and non-detection (D) values. In classical FMEA some causes of failure are difficult to distinguish in terms of their accurate priority. To overcome such limitations, a rule-based fuzzy logic based on the linguistic assessment of risk factors has been applied to compute fuzzy RPN. The ranking results were compared for effective decision making about the causes of the failure. From analysis of the results, cause C3 was found to be the most critical one. The results were supplied to the hospital concerned for their implementation.
