Legal Implications Of Ai-Assisted Medical Waste Management In Healthcare Facilities
Main Article Content
Medical waste management in healthcare facilities is critical to protecting public health and the environment. Improper handling of medical waste can lead to environmental pollution and pose serious health risks. In Indonesia, Permenkes No. 2 of 2023 provides a regulatory framework for managing medical waste, but its implementation needs to be improved, especially in remote healthcare facilities with limited infrastructure and resources. Technological advances, especially artificial intelligence (AI), offer potential solutions to optimize medical waste management through real-time tracking, sorting, and monitoring.
This study aims to evaluate the role of AI in supporting the implementation of Permenkes No. 2 of 2023 in several health facilities and identify barriers to AI adoption. Using a normative legal approach combined with case studies from health facilities in Indonesia, this study highlights the effectiveness of AI implementation in medical waste management. The results show that AI has the potential to improve compliance with medical waste management standards, optimize waste processing, and strengthen supervision through real-time data collection. However, AI adoption faces high costs, a lack of infrastructure, and limited technical expertise, especially in remote areas.
The implications of this study emphasize the need for investment in technological infrastructure, health workforce training, and supportive policies to address barriers to AI adoption. This would maximize the potential of this technology in more effective medical waste management for public health and a safer environment.
Keywords:
Artificial;, Intelligence;, Environmental Health;, Health Facilities;, Medical Waste
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Akkajit, P., Romin, H., & Assawadithalerd, M. (2020). Assessment of Knowledge, Attitude, and Practice in Medical Waste Management among Health Workers in Clinics. Journal of Public and Environmental Health, 2020. https://doi.org/10.1155/2020/8745472
Amelia, T., & Budi, H. (2022). Dynamics of Investment Law in Indonesia. PT Kaya Ilmu Bermanfaat.
Ardhani, R. (2016). Managing a Hospital. Lambung Mangkurat University Press.
Asrun, AM, Sihombing, LA, & Nuraeni, Y. (2020). Impact of Medical Waste Management Related to Law No. 36 of 2009 Concerning Health and Law No. 32 of 2009 Concerning Environmental Protection and Management. PAJOUL (Pakuan Judicial Law Journal), 1(1), 33–46. https://doi.org/10.1017/CBO9781107415324.00.
Astuti, AP (2019). Study of waste management in public hospitals in West Nusa Tenggara Province (NTB). Public Health, 2(1), 12–20.
Axmalia , A., & Sinanto , RA (2021). Handling of Household Infectious Waste during the COVID-19 Outbreak. Journal of Community Health, 7(1), 70–76.
Bokhoree , C., Beeharry , Y., Makoondlall-Chadee , T., Doobah , T., & Soomary , N. (2014). Assessment of Environmental and Health Risks Associated with Medical Waste Management in Mauritius. APCBEE Procedia, 9, 36–41. https://doi.org/10.1016/j.apcbee.2014.01.007
Camacho, D. M., Collins, K. M., Powers, R. K., Costello, J., & Collins, J. (2018). Next-Generation Machine Learning for Biological Networks. Cell.
Gade, DS, & Aithal, PS (2021). Smart City Waste Management through ICT and IoT-Based Solutions. International Journal of Applied Engineering and Management, 51–65. https://doi.org/10.47992/ijaeml.2581.7000.0092
Gerke, S., Minssen, T., & Cohen, G. (2020). Ethical and legal challenges in artificial intelligence-driven healthcare. Artificial Intelligence in Healthcare, 295–336. https://doi.org/10.1016/B978-0-12-818438-7.00012-5
Grace, C.S., .G., Sreeja, M., & Deepika, M. (2023). Non-Human Intervention Robot in Biomedical Waste Management. International Journal of Health Technology and Innovation, 2(01), 2–4. https://doi.org/10.60142/ijhti.v2i01.75
Hernanto, TS, & Amelia, T. (2024). Omnibus Law Law Enforcement in Indonesia. PT Kaya Ilmu Bermanfaat.
Hörnle, J. (2019). Artificial intelligence in healthcare: A critical analysis of legal and ethical implications. International Journal of Law and Information Technology, 27(2), 142–170.
Huang, J., & Koroteev, D. D. (2021). Artificial intelligence for energy and waste management planning. Sustainable Energy Technology and Assessment, p. 47. https://doi.org/10.1016/j.seta.2021.101426
Ibrahim, J. (2022). Normative Legal Research Theory & Methodology. Bayumedia Publishing.
Ishaq, A., Mohammad, S.J., Bello, A.-AD, Wada, S.A., Adebayo, A., & Jagun, Z.T. (2023). Smart dustbin monitoring using IoT for sustainable biomedical waste management. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-023-30240-1
Jose, R. (2024). Healthcare Waste Management; Its Impact: A Case Study in the Greater Accra Region. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4751230
Karnavel, K., Feroz, A. M., & Fathima, S. S. (2023). Surveillance of Infectious Medical Waste Using IoT. 11(5), 2320–2882.
Kassou , M., Bourekkadi , S., Khoulji , S., Slimani , K., Chikri , H., & Kerkeb , M.L. (2021). Blockchain-based medical waste and water management concept. E3S Web of Conferences, 234. https://doi.org/10.1051/e3sconf/202123400070
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Li, F., Ruijs, N., & Lu, Y. (2023). Ethics & AI: A Systematic Review of Ethical Issues and Related Strategies for Designing with AI in Healthcare. AI (Switzerland), 4(1), 28–53. https://doi.org/10.3390/ai4010003
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Marzuki, PM (2019). Legal Research Revised Edition. Kencana.
Maulana, M., Kusnanto, H., & Agus, S. (2017). Solid Waste Processing of Medical Care Father Hazardous and Toxic Material Waste in Private Hospitals in Jogja City. Proceedings of the 5th Urecol, 2 (1) (February), 184–190.
Musa, AE (2014). Assessment of medical, solid waste management in Khartoum state hospitals. Journal of Applied and Industrial Sciences, 2(4), 2328–4609.
Naik, N., Hameed, B., Shetty, D.K., Swain, D., Shah, M., Paul, R., Aggarwal, K., Ibrahim, S., Patil, V., Smriti, K., Shetty, K., Rai, B.P., Ch?osta, P., & Somani, B. (2022). Legal and Ethical Considerations in Artificial Intelligence in Healthcare: Who is Responsible? Frontiers in Surgery.
Namen, A. A., Da Costa Brasil, F., Abrunhosa, J. J. G., Abrunhosa, G. G. S., Tarré, R. M., & Marques, F. J. G. (2014). RFID technology for hazardous waste management and tracking. Waste Management and Research, 32, 59–66. https://doi.org/10.1177/0734242X14536463
Pandey, S. (2016). Nosocomial Infection through Hospital Waste. International Journal of Waste Resources, 06(01). https://doi.org/10.4172/2252-5211.1000200
Rahno, D., Roebijoso, J., & Leksono, AS (2015). Management of Solid Medical Waste at Borong Health Center, East Manggarai Regency, East Nusa Tenggara Province. Journal of Sustainable Development and Nature, 6(1), 22–32.
Ratu, WK (2014). Study of Hospital Waste Management and Its Development Prospects in Makassar City. Scientific Scholar.
Rong, G., Mendez, A., Bou Assi, E., Zhao, B., & Sawan, M. (2020). Artificial Intelligence in Healthcare: A Review and Prediction Case Study. Engineering, 6(3), 291– 301. https://doi.org/10.1016/j.eng.2019.08.015
Sengeni, D., Padmapriya, G., Imambi, S.S., Suganthi, D., Suri, A., & Boopathi, S. (2023). Biomedical waste management method using artificial intelligence techniques. Handbook of Research on Safe Disposal Methods of Municipal Solid Wastes for a Sustainable Environment, pp. 306–323. https://doi.org/10.4018/978-1-6684-8117-2.ch022
Singh, A.V., Rosenkranz, D., Ansari, M.H.D., Singh, R., Kanase, A., Singh, S.P., Johnston, B., Tentschert, J., Laux, P., & Luch, A. (2020). Artificial Intelligence and Machine Learning Empower Advanced Biomedical Material Design for Toxicity Prediction. Advanced Intelligent Systems, 2(12). https://doi.org/10.1002/aisy.202000084
Stephina, R., Sushmitha, S., Thanmaya, H.K., Thejaswini, Y.N., & M.S.A. (2020). Innovative Waste Disposal System in Hospitals Using Robots. 3961–3966.
Vollmer, S., Mateen, B. A., Bohner, G., Király, F. J., Ghani, R., Jonsson, P., Cumbers, S., Jonas, A., McAllister, K. S. L., Myles, P., Granger, D., Birse, M., Branson, R., Moons, K. G. M., Collins, G. S., Ioannidis, J. P. A., Holmes, C., & Hemingway, H. (2020). Machine learning and artificial intelligence research for patient benefit: 20 key questions about transparency, replicability, ethics and effectiveness. BMJ, p. 368. https://doi.org/10.1136/bmj.l6927
Zhao, Z., & Niu, M. (2022). Other medical waste treatment and disposal are based on Bluetooth and LoRa Wireless IoT. International Health Review (Online). https://doi.org/10.56226/ihr.v1i2.34
