NEW CLASSIFICATION AND COLOUR CODE DEVELOPMENT FOR AN EFFICIENT MEDICAL WASTE SEGREGATION

Abstract

Medical waste poses serious threat to the environmental health without comprehensive guidelines and efficient management as it contains highly toxic chemicals, pathogenic viruses and bacteria. Therefore, proper handling of medical waste with specialised treatment from its source to final disposal has been a primary concern among medical institute, public and private agencies. The existing medical waste classification in many countries does not contain clear and appropriate segregation, which has created confusion among the medical staff in handling medical waste.  It is pertinent to mention that, World Health Organisation (WHO) guidance recommends different countries to conduct assessments prior to any decision-making process and improve their own guidelines incorporated with recent technologies. Therefore, the objectives of this research are: 1) to develop a new classification of medical wastes by identifying the gaps in the current classes and 2) to suggest colour code for the medical waste segregation that is adopted from the WHO's colour code with few amendments as per the recent technological development. Due to the challenge in managing medical waste, there is an urgent need in developing and adopting comprehensive medical waste segregation classification to separate the medical waste at the source itself. The methodology of classification is aimed at applying a source separation practiced by the medical personnel on the spot and given them awareness on the segregation process. The proposed new classification of medical waste is based on Malaysia's Scheduled Waste Regulations together with European Waste Code. By extracting the best classification from these two regulations and by overcoming the lacuna in them, a new classification is developed for current use. The developed medical waste classification and its colour codes must provide a better segregation and achieve cost saving at waste disposal. The current methods of classification could be extended to research on application of such classification to other parts of the world.