A collaborative research effort, featuring a researcher Ahmadian from Near East University, unveils a pioneering approach to address the pressing challenge of efficient clinical diagnosis and disposal of medical waste, particularly prevalent in developing countries. The study introduces the concept of Probabilistic Hesitant Fuzzy Set (PHFS), an extended version of the Hesitant Fuzzy Set (HFS), offering decision-makers greater flexibility in expressing their preferences.
Through the application of Multi-Criteria Decision Making (MCDM) techniques, specifically the Aspiration-Regret Analysis System (ARAS), the research team navigates the complex landscape of healthcare waste (HCW) disposal options. The methodology incorporates the Entropy Weighted Method (EWM) to ensure robust criterion weight assessment, enhancing the decision-making process.
The study addresses the critical need for selecting optimal healthcare plastic waste disposal (HCPWD) strategies by employing a MCDM approach tailored to accommodate the uncertain and hesitant perspectives of decision-makers. Recognizing the importance of addressing both visible and invisible criteria, the proposed methodology combines objective weight assessment with ARAS, a top optimization technique in MCDM.
After rigorous evaluation, the research identifies steam disinfection as the most effective disposal treatment option, considering factors such as energy absorption, treatment efficiency, mechanization level, societal acceptance, land requirements, and cost risks. Steam disinfection not only minimizes environmental pollution but also safeguards human health from the risks of infections, making it a preferred choice.
The conclusions emphasize the significance of informed decision-making in healthcare waste management, advocating for the adoption of secure and appropriate disposal treatment systems across medical facilities. Moreover, the study underscores the potential for further advancements in healthcare waste disposal through technological innovations and effective government regulations.
By combining empirical and subjective data on criterion weight, the research paves the way for future endeavors aimed at refining and improving healthcare waste management practices. Through collaborative efforts and innovative methodologies, the study contributes to addressing global concerns surrounding medical waste disposal, offering tangible solutions for safer and more sustainable healthcare practices.
More Information:
https://link.springer.com/article/10.1007/s11270-022-05970-6
