Authors : Fernando GHS; Basnayaka KDB; Attanayaka AMTK; Niyarapola DRGM; Saddasena GMIO; Jayasundara PMCK

Volume/Issue : Volume 11 - 2026, Issue 4 - April

Google Scholar : https://tinyurl.com/yjcx4k8x

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DOI : https://doi.org/10.38124/ijisrt/26apr395

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Abstract : Introduction: Healthcare waste management at District General Hospital (DGH) Matale, Sri Lanka, faced increasing environmental and safety challenges from inadequate segregation, storage, and disposal of clinical and non-clinical wastes. A sustainable, systems-based approach including digital monitoring was introduced to address these issues.  Objective: To develop, implement, and evaluate a sustainable healthcare waste management system at DGH Matale that improves waste segregation, reduces clinical waste volumes and disposal costs, and enhances operational efficiency and compliance.  Methodology: A comprehensive intervention launched in early 2025 included formation of a Waste Management Steering Committee, development of institutional waste management policies, staff training, construction of a dedicated waste management center, and deployment of a real-time digital waste monitoring system. The digital platform tracked waste generation and disposal, supported compliance monitoring, and leveraged behavioral influence (Hawthorne Effect). Waste volumes and disposal costs were measured pre- and post-intervention; trends in clinical and non-clinical waste categories were analyzed.  Results: Post-intervention, clinical waste volume decreased by 42.36% and disposal costs declined by 42.27%. Improvements were observed in segregation practices and operational workflows. Non-clinical waste streams (e.g., clean plastic, food waste) showed mixed trends, indicating variable impacts across categories. Digital tracking improved accuracy of waste data and compliance monitoring.  Conclusion: Integrating institutional policy, staff training, dedicated infrastructure, and digital monitoring substantially improved clinical waste management at DGH Matale, yielding notable reductions in waste volume and disposal costs and enhancing operational efficiency.  Recommendations:  Scale and adapt the model to other healthcare facilities in Sri Lanka with contextual tailoring.  Extend interventions to target non-clinical waste streams through targeted training and source-reduction measures.  Enhance the digital system by incorporating AI-driven predictive analytics for waste forecasting, optimization of reduction strategies, and real-time segregation recommendations.  Conduct longitudinal studies to assess sustained behavioral change and long-term system performance across diverse healthcare settings.

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