4.7 Article

Developing an effectiveness index for biomedical waste management in Indian states using a composite indicators approach

Journal

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 28, Issue 45, Pages 64014-64029

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-021-13940-4

Keywords

Biomedical waste; Framework; Indicators; Composite index; Healthcare India

Funding

  1. Ministry of Human Resource Development (MHRD), New Delhi, India

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This paper aims to establish an effectiveness index for assessing the performance of biomedical waste management for the Indian states, using the proportional normalization technique and entropy method to determine the weights of the indicators, categorizing the states into red, yellow, and green zones.
The waste from healthcare facilities (HCFs) is most devastating as they induce health hazards and pollute the environment. The effective management of biomedical waste is an essential function of the state governments, depending on state policies and facilities in HCFs. The performance assessment at the state level provides explanatory information for the decision-makers to dispose of biomedical waste. Therefore, this paper aims to establish an effectiveness index for assessing the performance of biomedical waste management for the Indian states. The designed conceptual framework, which acts as the building block for the index, interlinks the technical, managerial, and sustainability dimensions. To assess the existing waste management practices, significant sub-indicators are analyzed for India's northern and southern states. The indicators are transformed into comparable units using the proportionate normalization technique. The weight to the respective indicators follows the entropy method and additive aggregation to form the indices for various states. The developed index allows comparing management practices among the states and highlights the alarming situation. Based on the magnitude of indices values, states are categorized as red, yellow, and green zones. The robustness of the model is validated by performing sensitivity analysis and the cluster analysis tests the reliability of indicators and categorization of states with the existing methodology. The analysis will be useful to the decision-makers of state pollution boards by providing special attention to capacity building and waste prevention technologies.

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