Predictive Modeling of Chemical Waste Generation in Healthcare Facilities: Enhancing Waste Management Strategies

The escalating generation of chemical waste in healthcare facilities is a pressing concern, particularly during rapidly spreading epidemics. This study proposes a system dynamics model to predict hospital chemical-waste generation rates. The model incorporates various variables, such as patient arrival and departure rates, to provide accurate estimations of waste generation. A case study conducted at a hospital validates and demonstrates the proposed model's practical application. The findings reveal that specific departments, such as Main Operations, Obstetrics, and Catheter, significantly influence healthcare chemical-waste generation rates. Additionally, the Tissue Department plays a substantial role. This research has two important implications. Firstly, it offers valuable insights into the complex factors affecting waste generation in healthcare facilities, identifying the departments that contribute most to the problem. Secondly, it provides waste management departments with a insights for capacity planning, scheduling, and resource allocation. Hospitals can enhance their waste management practices, leading to improved environmental sustainability and better public health outcomes. This study's ability to anticipate chemical waste generation and drive the development of comprehensive and long-term waste management programs is highlighted by its identification of the most significant departments in generating chemical waste. This study blends predictive intelligence with pragmatic insights, emerging as a crucial instrument for tackling the severe difficulties posed by the rising flow of chemical waste. It ultimately protects both individual well-being and the balance of the ecosystem. Keywords: system dynamics, chemical waste, healthcare facilities