A Fuzzy Inference System for the Assessment of Indoor Air Quality in an Operating Room to Prevent Surgical Site Infection

Abstract

Indoor air quality in hospital operating rooms is of great concern for the prevention of surgical site infections (SSI). A wide range of relevant medical and engineering literature has shown that the reduction in air contamination can be achieved by introducing a more efficient set of controls of HVAC systems and exploiting alarms and monitoring systems that allow having a clear report of the internal air status level. In this paper, an operating room air quality monitoring system based on a fuzzy decision support system has been proposed in order to help hospital staff responsible to guarantee a safe environment. The goal of the work is to reduce the airborne contamination in order to optimize the surgical environment, thus preventing the occurrence of SSI and reducing the related mortality rate. The advantage of FIS is that the evaluation of the air quality is based on easy-to-find input data established on the best combination of parameters and level of alert. Compared to other literature works, the proposed approach based on the FIS has been designed to take into account also the movement of clinicians in the operating room in order to monitor unauthorized paths. The test of the proposed strategy has been executed by exploiting data collected by ad-hoc sensors placed inside a real operating block during the experimental activities of the “Bacterial Infections Post Surgery” Project (BIPS). Results show that the system is capable to return risk values with extreme precision.

Risk Factors Analysis of Surgical Infection Using Artificial Intelligence: A Single Center Study

“…Finally, processes to identify causes and solutions of the most critical cases were not analyzed. Approaches such as Lean Six Sigma [ 47 , 48 , 49 ] or Fuzzy Logic [ 50 ] have been shown to be valid supports for reducing the risk of infection and will, therefore, be the subject of future studies.…”

Design of a Fuzzy Logic Evaluation to Determine the Ergonomic Risk Level of Manual Material Handling Tasks

“…The fuzzy logic allows the interpretation of data with predefined linguistic variables using conditional operators defined as IF-THEN rules [ 32 ], written as: IF situation 1 AND situation 2 THEN the decision where the situations represent the premise in fuzzy terms connected by fuzzy operators, while the output is the decision expected. Therefore, fuzzy logic defines the inferential mechanism needed to reach the output value related to the work condition and its ergonomic risk level.…”

“…Some investigations are based on designing fuzzy assessments of environments; however, this kind of research has no ergonomic purposes. For example, Colella et al [ 32 ] proposed a fuzzy inference system for the assessment of indoor air quality in an operating room to prevent surgical-site infections.…”

Multi-attribute decision-making using Archimedean aggregation operator in T-spherical fuzzy environment

“…An efficient surgery instruments supply selection methodology to hospital pharmacy by using fuzzy the MADM approach by Manivel and Ranganathan (2019). By using the MADM algorithm to measure the effect of air quality on the surgical instruments in operation theater by Colella et al (2022). Rahman and Lee (2013), by using fuzzy logic studied the assessment of the disturbance of surgical instruments during surgery.…”