Circular economy of medical waste: novel intelligent medical waste management framework based on extension linear Diophantine fuzzy FDOSM and neural network approach

A review on digital transformation in healthcare waste management: Applications, research trends and implications

At present, both emerging and developed economies have faced the challenge of higher healthcare waste generation. Developed countries are using these technologies to manage healthcare waste and cope with the challenge. Emerging economies are still struggling to understand and implement digital technologies in healthcare waste management, posing a danger to partners handling toxic and hazardous waste. The proper handling of healthcare waste is essential for social and environmental sustainability. Digital technologies that drive digital transformation in the healthcare sector impact the traditional way of managing healthcare waste. Digital technologies include artificial intelligence, blockchain, the Internet of Things, sensors, data analytics and radio frequency identification. These technologies can potentially address vehicle route planning and scheduling problems, resource optimisation, real-time tracking and the visibility of healthcare waste management. Apart from economic and environmental concerns, the operational workforce also takes care of societal well-being and implements waste management strategies and policies. Past research has focused on integrating blockchain technology to enhance traceability and transparency in waste collection and disposal activities. However, the application and impact of these technologies for managing different operations of healthcare management with sustainability is a gap bridged by the present study. This study adopts a systematic literature review to identify research trends, applications and implications of digital transformation. It proposes a digital technology-driven framework for healthcare waste management for further research.

Bioengineering the Future: Tomato Peel Cutin as a Resource for Medical Textiles

The exponential increase in medical waste production has increased the difficulty of waste management, resulting in higher medical waste dispersion into the environment. By employing a circular economy approach, it is possible to develop new materials by waste valorization. The employment of biodegradable and renewable agro-food, waste-derived materials may reduce the environmental impact caused by the dispersion of medical waste. In this work, tomato peel recovered cutin was blended with poly(L-lactide-co-ε-caprolactone) (PLAPCL) to develop new textiles for medical application through electrospinning. The textile fabrication process was studied by varying Cut content in the starting suspensions and by optimizing fabrication parameters. Devices with dense and porous structures were developed, and their morphological, thermal, and physical-chemical properties were evaluated through scanning electron microscopy, differential scanning calorimetry, thermogravimetric analysis, and Fourier transformed infrared spectroscopy. Textile material stability to γ-irradiation was evaluated through gel permeation chromatography, while its wettability, mechanical properties, and biocompatibility were analyzed through contact angle measurement, tensile test, and MTT assay, respectively. The LCA methodology was used to evaluate the environmental impact of textile production, with a specific focus on greenhouse gas (GHG) emissions. The main results demonstrated the suitability of PLAPCL-cutin blends to be processed through electrospinning and the obtained textile's suitability to be used to develop surgical face masks or patches for wound healing.

A comprehensive review on applications of multi-criteria decision-making methods in healthcare waste management

Effective management of healthcare waste (HCW) imposes a great challenge to all countries. Specially in the developing countries, it is often mixed with municipal waste, adversely affecting the health and safety of the medical personnel, general public and environment. Healthcare waste management (HCWM) basically deals with segregation, collection and storage, routing and transportation, treatment and safe disposal of HCW, while obeying some national legislation. In every stage of HCWM, there are several alternative choices/strategies to be evaluated against a set of conflicting criteria. Numerous multi-criteria decision-making (MCDM) methods have appeared to resolve the issue. This article reviews 101 articles available in Scopus and other scholarly databases on applications of MCDM techniques in solving HCWM problems. Those articles are classified into six groups: (a) selection of the most effective HCW treatment technology, (b) identification of the best HCW disposal site, (c) assessment of the best-performing healthcare unit adopting ideal HCWM strategies, (d) selection of third party logistics providers, (e) identification of HCWM barriers and (f) evaluation of specific HCWM plans. It is observed that the past researchers have mostly preferred to apply MCDM tools for solving HCW treatment technology selection problems, whereas analytic hierarchy process, decision-making trial and evaluation laboratory and best-worst method and fuzzy set theory have been the mostly favoured MCDM tool, criteria weight measurement techniques and uncertainty model, respectively. The outcomes of this article would help the healthcare personnel/policymakers in unveiling the current status of HCWM research, exploring extant research gaps and challenges and providing future directions leading to sustainable environment.

A comprehensive study on the factors influencing the generation of infectious healthcare waste in inpatient healthcare institutions in Hungary

Infectious healthcare waste (IHCW) poses a significant biohazard and public health risk. This study examines IHCW formation and influencing factors in Hungarian inpatient healthcare institutions. Factors such as hospital type, regional location, indicators related to patient traffic, educational activity, patients of certain types of medical specialties, and healthcare-associated infections (HAIs) were examined. Univariate and multivariate statistical methods identified significant predictors of IHCW occurrence. The generation rate of IHCW ranged from 0.15 to 0.81 kg/bed/day nationally, and it increased by 40.74% between 2017 and 2021, significantly impacted by the COVID-19 pandemic. The data also showed that as the number of beds increased, the IHCW production rate increased proportionally. The results indicate that IHCW generation rates vary significantly by hospital type, with university hospitals producing the most waste. The incidence of HAI multidrug-resistant (MDR) bacterial infections emerged as the primary driver of IHCW generation, along with educational activity, the number of intensive care unit patients, and regional differences. The Southern Great Plain region had the highest IHCW production (0,42 kg/bed/day) among the seven regions studied. The study highlights the critical impact of HAI MDR infections on IHCW production, emphasizing the need for targeted waste management in high-risk areas. Regional differences indicate the necessity for tailored strategies to address local waste management challenges. This study provides essential insights into IHCW formation and influencing factors in Hungary, offering valuable information for policy and practice.Implications: Nowadays, one of the main problems related to waste management is the uncontrollable amount of waste generated in the healthcare sector. Infectious healthcare waste (IHCW) represents a significant biological hazard and a high public health risk, both on an individual and a community level, so a more precise knowledge of these risks is extremely important. In the Central European region, very few studies have dealt with the infectious waste generated in the healthcare sector, and this is the first such research in Hungary. The primary aim of this study is to measure the amount of IHCW produced in various regions and hospital types in Hungary, and to examine the general and specific factors that affect the generation rate of this waste. The findings reveal that IHCW generation rates (GR) vary considerably across different hospital types and regions. This highlights the need for targeted waste management practices in individual institutions. In addition, the study emphasizes the importance of developing region-specific waste management strategies in view of regional inequalities. A crucial insight from the study is that the incidence of healthcare-associated infections (HAIs), particularly multidrug-resistant (MDR) bacterial infections, has the most significant impact on IHCW GR, surpassing other known factors. This suggests that effective control of HAIs, especially MDR bacterial infections, can lead to a substantial reduction in IHCW. The study also showed the impact of the COVID-19 pandemic not only on the production of IHCW, but also on individual influencing factors. Overall, the study provides valuable insights for informing policy and practice. By understanding the specific factors influencing IHCW production, policymakers and healthcare practitioners can develop more effective waste management policies and practices. This highlights the need for tailored waste management strategies that take into account the unique characteristics of each hospital type and geographic region, ultimately reducing the healthcare waste burden and providing a healthier and safer environment for all.

Monitoring of Medical Wastewater by Sensitive, Convenient, and Low-Cost Determination of Small Extracellular Vesicles Using a Glycosyl-Imprinted Sensor

The monitoring of small extracellular vesicles (sEVs) in medical waste is of great significance for the prevention of the spread of infectious diseases and the treatment of environmental pollutants in medical waste. Highly sensitive and selective detection methods are urgently needed due to the low content of sEVs in waste samples and the complex sample composition. Herein, a glycosyl-imprinted electrochemical sensor was constructed and a novel strategy for rapid, sensitive, and selective sEVs detection was proposed. The characteristic trisaccharide at the end of the glycosyl chain of the glycoprotein carried on the surface of the sEVs was used as the template molecule. The glycosyl-imprinted polymer films was then prepared by electropolymerization with o-phenylenediamine (o-PD) and 3-aminophenylboronic acid (m-APBA) as functional monomers. sEVs were captured by the imprinted cavities through the recognition and adsorption of glycosyl chains of glycoproteins on sEVs. The m-APBA molecule also acted as a signal probe and was then attached on the immobilized glycoprotein on the surface of sEVs by boric acid affinity. The electrochemical signal of m-APBA was amplificated due to the abundant glycoproteins on the surface of sEVs. The detection range of the sensor was 2.1 × 104 to 8.7 × 107 particles/mL, and the limit of detection was 1.7 × 104 particles/mL. The sensor was then applied to the determination of sEVs in medical wastewater and urine, which showed good selectivity, low detection cost, and good sensitivity.

Optimal selection of healthcare waste treatment devices using fuzzy-rough approach

The escalating volume of healthcare waste (HCW) generated by healthcare facilities poses a pressing challenge for all nations. Adequate management and disposal of this waste are imperative to mitigate its adverse impact on human lives, wildlife, and the environment. Addressing this issue in Bosnia and Herzegovina involves the establishment of a regional center dedicated to HCW management. In practice, there are various treatments available for HCW management. Therefore, it is necessary to determine the priority for procuring different treatments during the formation of this center. To assess these treatment devices, expert decision-making employed the fuzzy-rough approach. By leveraging extended sustainability criteria, experts initially evaluated the significance of these criteria and subsequently assessed the devices for HCW treatment. Employing the fuzzy-rough LMAW (Logarithm Methodology of Additive Weights), the study determined the importance of criteria, highlighting "Air emissions" and "Annual usage costs" as the most critical factors. Utilizing the fuzzy-rough CoCoSo (the Combined Compromise Solution) method, six devices employing incineration or sterilization for HCW treatment were ranked. The findings indicated that the "Rotary kiln" and "Steam disinfection" emerged as the most favorable devices for HCW treatment based on this research. This conclusion was validated through comparative and sensitivity analyses. This research contributes by proposing a solution to address Bosnia and Herzegovina's HCW challenge through the establishment of a regional center dedicated to HCW management.