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J Environ Health Sustain Dev 2023, 8(1): 1923-1937 |
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Al Fatlawi S, Al-Alwani M. A Model for Predicting Medical Solid Waste in Hilla City, Iraq. J Environ Health Sustain Dev 2023; 8 (1) :1923-1937
URL: http://jehsd.ssu.ac.ir/article-1-580-en.html
URL: http://jehsd.ssu.ac.ir/article-1-580-en.html
Department of Environmental Engineering, University of Babylon, Babylon, Iraq.
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| Abstract (HTML) (675 Views)
Table 2: Major sources of medical waste in hospitals and medical centers 21
Table 3: Colour coding and types of container for collecting different types of wastes 21
.PNG)
Figure 1: Map of the city of Hilla, Iraq 22
.PNG)
A fundamental correlation matrix was constructed in order to construct a model for facilitating the nature and strength comprehension of the correlation between the variables used in the study. The F-test was used to look at the removal efficiency and find significant factors. The calibrated instruments and knowledgeable supervisors ensured the quality of the data.
Ethical issues
All participants provided written informed consent for their anonymous information to be published in this article prior to enrollment in this study, which was carried out in accordance with the principles of the Declaration of Helsinki.
Results
In order to have an effective solid waste management system, it is necessary to anticipate future rates of solid medical waste production. The generation rate has an effect on the size of storage facilities, the variety and quantity of collecting tools, and the capacity requirements for subsequent treatment and disposal. Despite the increase in the number and variety of treatment facilities in Iraq, the challenges associated with managing solid medical waste have remained constant over the past few years. The significant rise in the production of solid medical waste is primarily attributed to Iraq's expanding population and economy. Hilla city, like other cities in the country, has a lot of people and makes a lot of solid medical waste. Therefore, in order to successfully manage solid medical waste in other cities of Iraq, it is necessary to locate a suitable model to explain the data. This research aims to gather and analyze data from various sources and then come up with a method that effectively finds the mean generation rates for solid medical waste. To this end, the researcher plans to use a combination of analytical and statistical processes, such as collecting and analyzing existing data or conducting surveys with national and local organizations. The methods used to calculate the mean generation rate (kg/bed/day) are relatively straightforward by simply taking samples from a known volume of MSW and calculating the mean concentration thorough analysis. According to the data that was gathered, the mean generation rates at Hilla General Teaching Hospital, Babel Women's and Children's Hospital, Al Noor Children's Hospital, Imam Sadiq Hospital, and Murjana Teaching Hospital were 0.688, 0.47, 0.167, 0.679, and 0.278, respectively (Table 4). Hilla General Teaching Hospital and Imam Sadiq Hospital experienced the worst conditions, since they provided residential or food services to patient’s andgenerated the highest percentage of waste compared to other hospital. According to the data, 72 % of the wastes were for general, 19% for infectious, 1% for acute (acute waste is any waste material that is highly toxic or hazardous such as chemical waste and oil waste), 0% for pharmaceutical, 8% for pathological, and 0% for radioactive wastes of the hospitals. Compared to the WHO estimates of 80%, 15%, 1%, 3%, and less than 1% for general, pathological and infectious, sharp, pharmaceutical, and radioactive medical solid waste, these results are significantly higher. However, the lack of segregation policies for hospital samples may be the reason why the generation rate for hospitals in Hilla is lower than in other countries. The rates of MSW generation in various nations are presented in Table 5. Additionally, a variety of solids are typically present in clinical strong waste.
Table 4: Typical generation rates for Hilla hospitals (kilograms per bed per day)
Table 5: Mean rate of medical waste generation in different countries/cities hospitals 23
.PNG)
Figure 3: The correlation between the daily numbers of inpatients and outpatients and the amount of soild medical waste produced per kilogram per day at Hilla General Teaching Hospital
.PNG)
Figure 4: The correlation between the daily numbers of inpatients and outpatients and the amount of soild medical waste produced per kilogram per day at Babel Hospital for Women and Children
.PNG)
Figure 5: The correlation between the daily numbers of inpatients and outpatients and the amount of soild medical waste produced per kilogram per day at Al Noor Children's Hospital
.PNG)
Figure 6: The correlation between the daily numbers of inpatients and outpatients and the amount of soild medical waste produced per kilogram per day at Imam Sadiq Hospital
.PNG)
Figure 7: The correlation between the daily numbers of inpatients and outpatients and the amount of soild medical waste produced per kilogram per day at Murjan Teaching Hospital
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A Model for Predicting Medical Solid Waste in Hilla City, Iraq
Suad Al Fatlawi 1*, Mustafa Al-Alwani 2
1 Department of Environmental Engineering, University of Babylon, Babylon, Iraq.
2 Republic of Iraq, Ministry of Higher Education and Scientific Research, Iraq.
Suad Al Fatlawi 1*, Mustafa Al-Alwani 2
1 Department of Environmental Engineering, University of Babylon, Babylon, Iraq.
2 Republic of Iraq, Ministry of Higher Education and Scientific Research, Iraq.
| A R T I C L E I N F O | ABSTRACT | |
| ORIGINAL ARTICLE | Introduction: To improve current practices and create the most effective healthcare waste treatment system, solid medical waste composition needs to be analyzed. This study aims to develop models to predict the rate of medical waste production in hospitals in Hilla city, Iraq. Predictive mode can be used to set standards, evaluate current methods for treating and disposing medical waste, and optimize healthcare solid waste management systems. Materials and Methods: Predictive models and long-term data on the composition and rate of solid medical waste generation were developed using a longitudinal study design. A standardized questionnaire and weighted scale were used to measure solid medical waste generated from the five public hospitals. Statistics were used to create models predicting the amount of waste generated at each hospital. Results: These models demonstrated a significant correlation between inpatient and outpatient numbers and waste generation. Different hospitals treat different numbers of inpatients and outpatients. Different models have been created based on various types of hospitals. Conclusion: Linear rule-based models accurately represent the weights of variables, identify the sources and implications of solid medical waste, and control waste levels by using a variety of parameters. The research model can help in the development of an effective strategic plan for setting up a medical solid waste (MSW) management system. |
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Article History: Received: 12 November 2022 Accepted: 20 January 2023 |
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*Corresponding Author: Suad Al Fatlawi Email: suad.glewa@uobabylon.edu.iq Tel: +96 47703338172 |
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Keywords: Medical Waste, Solid Waste, Waste Management, Mathematical Model, Statistical, Iraq. |
Citation: Al Fatlawi S, Al-Alwani M. A Model for Predicting Medical Solid Waste in Hilla City, Iraq. J Environ Health Sustain Dev. 2023; 8(1): 1923-37.
Introduction
The associated term ‘medical waste’ is frequently used worldwide. The term ‘solid medical waste’ is utilized in China, Korea, and the United States, while the WHO and the EU uses the term ‘healthcare waste’. In addition, the term ‘infectious waste’ is used in Japan 1. Patients receive assistance from healthcare to overcome health issues brought on by pollution. Additionally, one of the largest polluters is the healthcare sector 2. Effective decontamination and waste management, including recycling options, are crucial because active waste management reduces the risk of virus transmission through litter 3. The number of hospitals and other health care facilities is rising to accommodate the expanding population 4. In hospitals, the amount of medical waste varies 5. Today, there is a greater risk of environmental contamination and disease transmission. This has resulted in the production of a significant amount of medical waste, which is exacerbated by inadequate handling and disposal procedures 6. Additionally, the healthcare industry has produced more hazardous waste because of the COVID-19 pandemic. Hand sanitizer, rubber boots and gowns, disposable gloves, and masks make up the majority of this waste. Plastic from various personal protective equipment, as well as medical supplies like syringes, test kits, plastic trays, and bandages, are also discarded 7. It has been observed that the composition of medical solid waste during the COVID-19 pandemic is roughly comparable to that of normal waste, with the exception of the production of a significant quantity of plastics. However, as a result of the pandemic, waste production has increased dramatically. 8. The first step in setting up a system for managing medical waste is gathering sufficient data about the volume and composition of the generated solid medical waste 9. According to the World Health Organization (WHO), the proportion of medical institutions, hospitals, specialties, proportional daily patient care, and medical care materials affect the amount of waste generated by hospitals 10. In order to monitor and manage the current systems for managing medical solid waste (MSW), it is necessary to classify MSW according to generation rates, waste types generated, and composition 11. By establishing a correlation between key factors that influence the rate of MSW production, such as the hospital's specialty, type, size, and percentage of patients treated per day, and the proportion of MSW produced 12, the evaluation of the various types of hospital-generated MSW looks promising. The number of hospitalized patients has the greatest impact on the amount of waste produced 13. A technique for determining the connection between these significant variables and the quantity of solid waste produced is statistical analysis 1. For current MSW management, the production rate, type of waste produced and waste composition ought to be characterized 10. Utilizing mathematical prediction models to accelerate the production of solid medical waste can improve solid medical waste management. Scientists have developed predictive models that can be used to estimate the rate at which healthcare waste is produced 14-15. The researchers have developed three distinct multiple linear regression (MLR) models in order to evaluate the daily total of hospital waste and the total amount of hazardous waste in Nablus City using the number of beds and inpatients 15. A number of autoregressive integrated moving average (ARIMA) models have been tested to see which model was best at estimating the amount of solid medical waste produced in India 16. In addition, Etinkaya developed a regression model to estimate the solid medical waste generated by Turkish hospitals using patient counts and GDP per capita as inputs 17. A number of variables have an impact on the prediction model for the generation of MSW. These variables consist of the beds number, the patient's number, and the hospital type. Therefore, regional factors must be taken into account when estimating the production of solid waste in developing nations. Nevertheless, Awad discovered a significant relationship with R2 values of 0.973, 0.486, and 0.937 between the medical waste quantities produced, the patient's number, the hospital kind, and the beds number, respectively 6. On the other hand, a number of studies in the literature have used surveys, questionnaires, and field investigations to estimate the generated MSW 12,18-20. These methods are reliable for estimating the MSW generation rates. It is essential to place an emphasis on the actual quantities of generated MSW in hospitals rather than data obtained from surveys or questionnaires in order to conduct a predictive study that is more accurate, healthy, and trustworthy. During several visits of each hospital, the total amount of MSW was measured.
Classification of medical waste
Hospital MSW is already divided into several categories. The research conducted by Khan 21 used ten distinct categories including pharmaceutical, chemical, pressurized containers, sharps, highly infectious, nontoxic, and radioactive waste, as well as anatomical, pathological, and infectious diseases (Table 1). MSW from hospitals can also be divided into two categories including hazardous waste and non-hazardous waste, or infectious and infectious waste. However, the following four categories were utilized in this study consisting of sharp, contagious, pathological, and all-encompassing. Hospitals and medical centers, on the other hand, generate a significant amount of medical waste. Bandages, syringes, contaminated needles, vials, and other medical equipment are all common sources of medical waste. Medical waste also includes soiled linens, used gowns and gloves, and food containers thrown away. Additionally, pharmaceuticals and hazardous chemicals are categorized as medical waste. Medical waste includes instruments, dressings, swabs, and clinical waste from medical procedures. Medical waste also includes pharmaceutical products like expired medicines. As shown in Table 2, medical waste can also come from infectious waste, hazardous waste, and laboratory waste. The easiest way to identify and encourage people to sort the various types of waste is to collect them in separate containers or plastic bags that are color-coded or marked with a symbol. Table 3 lists the international recommendations.
The associated term ‘medical waste’ is frequently used worldwide. The term ‘solid medical waste’ is utilized in China, Korea, and the United States, while the WHO and the EU uses the term ‘healthcare waste’. In addition, the term ‘infectious waste’ is used in Japan 1. Patients receive assistance from healthcare to overcome health issues brought on by pollution. Additionally, one of the largest polluters is the healthcare sector 2. Effective decontamination and waste management, including recycling options, are crucial because active waste management reduces the risk of virus transmission through litter 3. The number of hospitals and other health care facilities is rising to accommodate the expanding population 4. In hospitals, the amount of medical waste varies 5. Today, there is a greater risk of environmental contamination and disease transmission. This has resulted in the production of a significant amount of medical waste, which is exacerbated by inadequate handling and disposal procedures 6. Additionally, the healthcare industry has produced more hazardous waste because of the COVID-19 pandemic. Hand sanitizer, rubber boots and gowns, disposable gloves, and masks make up the majority of this waste. Plastic from various personal protective equipment, as well as medical supplies like syringes, test kits, plastic trays, and bandages, are also discarded 7. It has been observed that the composition of medical solid waste during the COVID-19 pandemic is roughly comparable to that of normal waste, with the exception of the production of a significant quantity of plastics. However, as a result of the pandemic, waste production has increased dramatically. 8. The first step in setting up a system for managing medical waste is gathering sufficient data about the volume and composition of the generated solid medical waste 9. According to the World Health Organization (WHO), the proportion of medical institutions, hospitals, specialties, proportional daily patient care, and medical care materials affect the amount of waste generated by hospitals 10. In order to monitor and manage the current systems for managing medical solid waste (MSW), it is necessary to classify MSW according to generation rates, waste types generated, and composition 11. By establishing a correlation between key factors that influence the rate of MSW production, such as the hospital's specialty, type, size, and percentage of patients treated per day, and the proportion of MSW produced 12, the evaluation of the various types of hospital-generated MSW looks promising. The number of hospitalized patients has the greatest impact on the amount of waste produced 13. A technique for determining the connection between these significant variables and the quantity of solid waste produced is statistical analysis 1. For current MSW management, the production rate, type of waste produced and waste composition ought to be characterized 10. Utilizing mathematical prediction models to accelerate the production of solid medical waste can improve solid medical waste management. Scientists have developed predictive models that can be used to estimate the rate at which healthcare waste is produced 14-15. The researchers have developed three distinct multiple linear regression (MLR) models in order to evaluate the daily total of hospital waste and the total amount of hazardous waste in Nablus City using the number of beds and inpatients 15. A number of autoregressive integrated moving average (ARIMA) models have been tested to see which model was best at estimating the amount of solid medical waste produced in India 16. In addition, Etinkaya developed a regression model to estimate the solid medical waste generated by Turkish hospitals using patient counts and GDP per capita as inputs 17. A number of variables have an impact on the prediction model for the generation of MSW. These variables consist of the beds number, the patient's number, and the hospital type. Therefore, regional factors must be taken into account when estimating the production of solid waste in developing nations. Nevertheless, Awad discovered a significant relationship with R2 values of 0.973, 0.486, and 0.937 between the medical waste quantities produced, the patient's number, the hospital kind, and the beds number, respectively 6. On the other hand, a number of studies in the literature have used surveys, questionnaires, and field investigations to estimate the generated MSW 12,18-20. These methods are reliable for estimating the MSW generation rates. It is essential to place an emphasis on the actual quantities of generated MSW in hospitals rather than data obtained from surveys or questionnaires in order to conduct a predictive study that is more accurate, healthy, and trustworthy. During several visits of each hospital, the total amount of MSW was measured.
Classification of medical waste
Hospital MSW is already divided into several categories. The research conducted by Khan 21 used ten distinct categories including pharmaceutical, chemical, pressurized containers, sharps, highly infectious, nontoxic, and radioactive waste, as well as anatomical, pathological, and infectious diseases (Table 1). MSW from hospitals can also be divided into two categories including hazardous waste and non-hazardous waste, or infectious and infectious waste. However, the following four categories were utilized in this study consisting of sharp, contagious, pathological, and all-encompassing. Hospitals and medical centers, on the other hand, generate a significant amount of medical waste. Bandages, syringes, contaminated needles, vials, and other medical equipment are all common sources of medical waste. Medical waste also includes soiled linens, used gowns and gloves, and food containers thrown away. Additionally, pharmaceuticals and hazardous chemicals are categorized as medical waste. Medical waste includes instruments, dressings, swabs, and clinical waste from medical procedures. Medical waste also includes pharmaceutical products like expired medicines. As shown in Table 2, medical waste can also come from infectious waste, hazardous waste, and laboratory waste. The easiest way to identify and encourage people to sort the various types of waste is to collect them in separate containers or plastic bags that are color-coded or marked with a symbol. Table 3 lists the international recommendations.
Table 1: Classification of medical wastes and their brief description 21
| Waste category | Descriptions and examples | |
| Hazardous healthcare waste | ||
| Sharps waste | Used or unused sharps (e.g., hypodermic, intravenous or other needles, auto-disable syringes, syringes with attached needles, infusion sets, scalpels, pipettes, knives, blades, and broken glass) | |
| Infectious waste | Waste suspected to contain pathogens that poses a risk of disease transmission (e.g., waste contaminated with blood and other body fluids, laboratory cultures and microbiological stocks, and waste including excreta and other materials that have been in contact with patients infected with highly infectious diseases in isolation wards) | |
| Pathological waste | Human tissues, organs or fluids,body parts, fetuses, and unused blood products | |
| Pharmaceutical waste, cytotoxic waste | Pharmaceuticals that are expired or no longer needed; items contaminated by or containing pharmaceuticals. Cytotoxic waste containing substances with genotoxic properties (e.g., waste containing cytostatic drugs(often used in cancer therapy), and genotoxic chemicals) | |
| Chemical waste | Waste containing chemical substances (e.g., laboratory reagents, film developer, disinfectants that are expired or no longer needed, solvents, waste with high content of heavy metals, e.g., batteries, and broken thermometers and blood-pressure gauges) | |
| Radioactive waste | Waste containing radioactive substances (e.g., unused liquids from radiotherapy or laboratory research, contaminated glassware, packages, or absorbent paper, urine and excreta from patients treated or tested with unsealed radionuclides, and sealed sources) | |
| Nonhazardous or general healthcare waste | Waste that does not pose any particular biological, chemical, radioactive, or physical hazard | |
Table 2: Major sources of medical waste in hospitals and medical centers 21
| Location | Sharps | Infectious and pathological waste | Chemical, pharmaceutical, and cytotoxic waste | Nonhazardous or general waste |
| Medical ward | Hypodermic needles, intravenous set needles, broken vials, and ampoules | Dressings, bandages, gauze, and cotton contaminated with blood or body fluids, gloves and masks contaminated with blood or body fluids | Broken thermometers and blood-pressure gauges, spilt medicines, spent disinfectants | Packaging, food scraps, paper, flowers, empty saline bottles, nonbloody diapers, nonbloody intravenous tubing and bags |
| Operating theater | Needles, intravenous sets, scalpels, blades, Saws | Blood and other body fluids; suction canisters; gowns, gloves, masks, gauze and other waste contaminated With blood and body fluids; tissues, organs, fetuses, body parts | Spent disinfectants Waste anesthetic gases |
Packaging; uncontaminated gowns, gloves, masks, hats, and Shoe covers |
| Laboratory | Needles, broken glass, Petri dishes, slides and cover slips, and broken pipettes | Blood and body fluids, microbiological cultures and stocks, tissue, infected animal carcasses, tubes and containers contaminated with blood or body fluids | Fixatives, formalin, xylene, toluene, methanol, methylene chloride, and other solvents, broken lab thermometers | Packaging, paper, and plastic containers |
| Pharmacy store | Expired drugsand spilt drugs | Packaging, paper, and empty containers | ||
| Radiology | Silver, fixing and developing solutions, acetic acid, glutaraldehyde | Packaging, paper | ||
| Chemotherapy | Needles and syringes | Bulk chemotherapeutic waste; vials, gloves, and other material contaminated with cytotoxic agents, contaminated excreta and urine | Packaging, paper | |
| Vaccination campaigns | Needles and syringes | Bulk vaccine waste, vials, and gloves | Packaging | |
| Environmental services | Broken glass | Disinfectants (glutaraldehyde, phenols, etc.), cleaners, spilt mercury, pesticides | Packaging, flowers, newspapers, magazines, cardboard, plastic and glass containers, yard and plant waste | |
| Engineering | Cleaning solvents, oils, lubricants, thinners, asbestos, broken mercury devices, batteries | Packaging, construction or demolition waste, wood, metal | ||
| Food services | Food scraps, plastic, metal, and glass containers; packaging | |||
Table 3: Colour coding and types of container for collecting different types of wastes 21
| S. No | Types of waste | Color-coding symbol | Type of container |
| 1 | Household refuse | Black | Plastic bag |
| 2 | Sharps | Yellow | Sharps container |
| 3A | Waste entailing a risk of contamination | Yellow | Plastic bag or container |
| 3B | Anatomical waste | Yellow | Plastic bag or container |
| 3C | Infectious waste | Yellow and highly infectious | Plastic bag or container which can be autoclaved |
| 4 | Chemical and pharmaceutical waste | Brown, marked with suitable symbol | Plastic bag or container |
Materials and Methods
Case study area
One of the provinces in the Middle Euphrates region is Hilla city (Figure 1). This is located in Iraq's sedimentary plain. In this city, there are numerous government hospitals that treat patients in a variety of medical specialties. Each facility had a very different total number of beds, especially public hospitals. As can be seen, the five hospitals are all different sizes and treat different numbers of patients. There are many different kinds of trash. Nevertheless, a single landfill now holds all of these hospitals waste. This study was conducted in Hilla city in 2022 to assess the management of hospital solid waste. The locations of the field visits were five public hospitals including Hilla General Teaching Hospital, Babel Hospital for Women and Children, Murjan Teaching Hospital, Al Noor Children's Hospital, and Imam Sadiq Hospital. Qualitative and quantitative methods were used in the form of questions, interviews, and observations. Inspections and observations of treatment and collection facilities were also carried out in order to triangulate the interview data. Each hospital total amount of MSW was measured over several visits. After that, the waste is recycled into plastic, glass, paper, textiles, and other products. After sorting waste by type, it was measured again by group. The laboratory of university received the samples from each batch to determine their moisture content. The sample was first weighed before being dried for an additional 24 hours at 105 °C to determine its moisture content. Moisture content of waste samples is important for a variety of reasons, such as determining the efficiency of waste-to-energy systems, maintaining quality control, and providing information about the composition and characteristics of the sample.
Case study area
One of the provinces in the Middle Euphrates region is Hilla city (Figure 1). This is located in Iraq's sedimentary plain. In this city, there are numerous government hospitals that treat patients in a variety of medical specialties. Each facility had a very different total number of beds, especially public hospitals. As can be seen, the five hospitals are all different sizes and treat different numbers of patients. There are many different kinds of trash. Nevertheless, a single landfill now holds all of these hospitals waste. This study was conducted in Hilla city in 2022 to assess the management of hospital solid waste. The locations of the field visits were five public hospitals including Hilla General Teaching Hospital, Babel Hospital for Women and Children, Murjan Teaching Hospital, Al Noor Children's Hospital, and Imam Sadiq Hospital. Qualitative and quantitative methods were used in the form of questions, interviews, and observations. Inspections and observations of treatment and collection facilities were also carried out in order to triangulate the interview data. Each hospital total amount of MSW was measured over several visits. After that, the waste is recycled into plastic, glass, paper, textiles, and other products. After sorting waste by type, it was measured again by group. The laboratory of university received the samples from each batch to determine their moisture content. The sample was first weighed before being dried for an additional 24 hours at 105 °C to determine its moisture content. Moisture content of waste samples is important for a variety of reasons, such as determining the efficiency of waste-to-energy systems, maintaining quality control, and providing information about the composition and characteristics of the sample.
Figure 1: Map of the city of Hilla, Iraq 22
In addition, the objective of this study is to investigate and attempt to develop specific prediction models that can predict the number of HCWs produced by a healthcare facility by taking into account a variety of factors. Morover, to determine the amount of waste produced by hospitals per bed per day, kitchen waste was added to each waste unit. Additionally, the number of overnight admissions was counted. This is the first study including HCWs' data from the hospitals in Hilla city public healthcare sector due to the limitations in Iraqi, particularly Hilla city.
Reaserch methodology
Meetings with field workers and university and administration experts were held to create a complete composition of MSW. After that, a literature review of scientific papers and reports was completed and an examination of the published data on medical waste was available. Through surveys and weighing studies, prediction models based on the patient's number, hospital type, and numbers of beds were developed to accurately predict the rates of hospital MSW. The reaserch methodology is presented in Figure 2. Five hospitals with varying capacities and specialties provided the data. There were two rounds of data collection. The first round was held in the wet season from October to December 2022, while the second round was held in the dry season from January to March 2022. Over the course of a single day, primary and secondary data collection techniques, equipment demonstrations, and procedures were taught. Infectious waste should be labeled in black, while general MSW should be labeled in yellow. The amount of waste produced was determined by collecting solid medical waste from each unit of the study hospital and measuring it with a calibrated sensitivity scale. The number of outpatients, the number of hospital beds, and the amount of daily waste were all recorded. A number of authors claim that kg/bed/day and kg/ambulatory/day are indicators of the production of solid medical waste 5. During the field visits, observations made in the field were also recorded. From the data gathered, a conclusion and a summary of the findings were compiled. The Statistical Package for the Social Sciences (SPSS) was used to process and analyze the data. Each of the five hospitals was a specific study site. A normal distribution was found after applying a normality test to data on the generation of MSW. As a result, bivariate associations were examined with the Pearson correlation test. Multivariate linear regression analysis was used to identify significant variables that influence the amount of waste produced by hospitals in order to develop a model that can accurately calculate or predict waste generation rates for the examined hospitals.
Reaserch methodology
Meetings with field workers and university and administration experts were held to create a complete composition of MSW. After that, a literature review of scientific papers and reports was completed and an examination of the published data on medical waste was available. Through surveys and weighing studies, prediction models based on the patient's number, hospital type, and numbers of beds were developed to accurately predict the rates of hospital MSW. The reaserch methodology is presented in Figure 2. Five hospitals with varying capacities and specialties provided the data. There were two rounds of data collection. The first round was held in the wet season from October to December 2022, while the second round was held in the dry season from January to March 2022. Over the course of a single day, primary and secondary data collection techniques, equipment demonstrations, and procedures were taught. Infectious waste should be labeled in black, while general MSW should be labeled in yellow. The amount of waste produced was determined by collecting solid medical waste from each unit of the study hospital and measuring it with a calibrated sensitivity scale. The number of outpatients, the number of hospital beds, and the amount of daily waste were all recorded. A number of authors claim that kg/bed/day and kg/ambulatory/day are indicators of the production of solid medical waste 5. During the field visits, observations made in the field were also recorded. From the data gathered, a conclusion and a summary of the findings were compiled. The Statistical Package for the Social Sciences (SPSS) was used to process and analyze the data. Each of the five hospitals was a specific study site. A normal distribution was found after applying a normality test to data on the generation of MSW. As a result, bivariate associations were examined with the Pearson correlation test. Multivariate linear regression analysis was used to identify significant variables that influence the amount of waste produced by hospitals in order to develop a model that can accurately calculate or predict waste generation rates for the examined hospitals.
Figure 2: Flow diagram of the research steps
A fundamental correlation matrix was constructed in order to construct a model for facilitating the nature and strength comprehension of the correlation between the variables used in the study. The F-test was used to look at the removal efficiency and find significant factors. The calibrated instruments and knowledgeable supervisors ensured the quality of the data.
Ethical issues
All participants provided written informed consent for their anonymous information to be published in this article prior to enrollment in this study, which was carried out in accordance with the principles of the Declaration of Helsinki.
Results
In order to have an effective solid waste management system, it is necessary to anticipate future rates of solid medical waste production. The generation rate has an effect on the size of storage facilities, the variety and quantity of collecting tools, and the capacity requirements for subsequent treatment and disposal. Despite the increase in the number and variety of treatment facilities in Iraq, the challenges associated with managing solid medical waste have remained constant over the past few years. The significant rise in the production of solid medical waste is primarily attributed to Iraq's expanding population and economy. Hilla city, like other cities in the country, has a lot of people and makes a lot of solid medical waste. Therefore, in order to successfully manage solid medical waste in other cities of Iraq, it is necessary to locate a suitable model to explain the data. This research aims to gather and analyze data from various sources and then come up with a method that effectively finds the mean generation rates for solid medical waste. To this end, the researcher plans to use a combination of analytical and statistical processes, such as collecting and analyzing existing data or conducting surveys with national and local organizations. The methods used to calculate the mean generation rate (kg/bed/day) are relatively straightforward by simply taking samples from a known volume of MSW and calculating the mean concentration thorough analysis. According to the data that was gathered, the mean generation rates at Hilla General Teaching Hospital, Babel Women's and Children's Hospital, Al Noor Children's Hospital, Imam Sadiq Hospital, and Murjana Teaching Hospital were 0.688, 0.47, 0.167, 0.679, and 0.278, respectively (Table 4). Hilla General Teaching Hospital and Imam Sadiq Hospital experienced the worst conditions, since they provided residential or food services to patient’s andgenerated the highest percentage of waste compared to other hospital. According to the data, 72 % of the wastes were for general, 19% for infectious, 1% for acute (acute waste is any waste material that is highly toxic or hazardous such as chemical waste and oil waste), 0% for pharmaceutical, 8% for pathological, and 0% for radioactive wastes of the hospitals. Compared to the WHO estimates of 80%, 15%, 1%, 3%, and less than 1% for general, pathological and infectious, sharp, pharmaceutical, and radioactive medical solid waste, these results are significantly higher. However, the lack of segregation policies for hospital samples may be the reason why the generation rate for hospitals in Hilla is lower than in other countries. The rates of MSW generation in various nations are presented in Table 5. Additionally, a variety of solids are typically present in clinical strong waste.
Table 4: Typical generation rates for Hilla hospitals (kilograms per bed per day)
| Hospital | Mean generation rate |
| Hilla general teaching hospital | 0.688 |
| Babel women and children hospital | 0.47 |
| Al noor children hospital | 0.167 |
| Imam sadiq hospital | 0.679 |
| Murjan teaching school | 0.278 |
Table 5: Mean rate of medical waste generation in different countries/cities hospitals 23
| Country / City |
Waste generation rate | Genera l waste % |
Hazardous waste % |
| Iraq/ Tikrit | 0.75 Kg/patient/d 0.9 Kg/bed/d |
63.04 | 36.96 |
| Taiwan | 0.88 Kg/bed/day |
64 | 92 |
| Greece | 8.4 kg/bed/day | 83.33 | 16.67 |
| South Africa | 0.6 kg/patient/day |
60.74 | 39.26 |
| Algeria | 0.7-1.22 kg/bed/day |
75-90 | 10-25 |
| Libya | 1.3 kg/patient/day |
72 | 28 |
| El- Beheria, Egypt | 2.07 kg/bed/day |
60.10 | 38.90 |
| Public hospitals, Iran | 3.16 Kg/bed/day |
56 | 42 |
As a result, a mathematical model that can predict the amount of waste generation by hospitals in Iraq is very helpful. Correlations between inpatients and outpatients, as well as the number of beds, capacity, and type of hospital, were used in this study to identify significant variables that primarily affect the rates of MSWgeneration. Linear regression analysis was also used to create models that could be predicted. The number of inpatients and outpatients at Hilla General Medical University Hospital is strongly correlated with the amount of MSW produced
(R2 = 0.934). At Babel Women's and Children's Hospital, the rate of MSW generation was
R2 = 0.885 for inpatients and R2 = 0.768 for outpatients. The rate of MSW generation at Al Noor Children's Hospital was inversely correlated with the number of outpatients at R2 = 0.887 and had a correlation with the number of inpatients at R2 = 0.870. At Imam Sadiq Hospital, there was a correlation (R2 = 0.858) between the quantity of medical waste produced and the number of inpatients and outpatients. The MSW generation rate at Al-Murjan Hospital was found to be inversely correlated with the number of outpatients and inpatients as R2 = 0.494 and 0.884, respectively. In addition, the bed occupancy rates at Al Murjan Hospital, Imam Sadiq Hospital, Hilla General Hospital, Babel Hospital for Women and Children, Al Noor Children's Hospital, and Imam Sadiq Hospital were 50 %, 92 %, 83 %, 45 %, and 50 %, respectively. Hilla General Hospital had a bed occupancy rate of 50 %. Furthermore, in order to ascertain the ways in which each independent variable affects the dependent variable, Figures 3, 4, 5, 6, and 7 show scatter plots of the daily rate of MSW generation against total patients, inpatients, and outpatients for all of the hospitals. Figures 3, 4, 5, 6, and 7 depict the linear relationship between the rate at which MSW is produced and the number of inpatients and outpatients. Equations 1, 2, 3, 4, and 5 are the subsequent linear connection-based predictive models. Equation 4 depicts the prediction model for the overall rate of inpatient and outpatient MSW generation. This study employs predictive modeling to statistically identify data patterns and the likelihood of particular outcomes.
(R2 = 0.934). At Babel Women's and Children's Hospital, the rate of MSW generation was
R2 = 0.885 for inpatients and R2 = 0.768 for outpatients. The rate of MSW generation at Al Noor Children's Hospital was inversely correlated with the number of outpatients at R2 = 0.887 and had a correlation with the number of inpatients at R2 = 0.870. At Imam Sadiq Hospital, there was a correlation (R2 = 0.858) between the quantity of medical waste produced and the number of inpatients and outpatients. The MSW generation rate at Al-Murjan Hospital was found to be inversely correlated with the number of outpatients and inpatients as R2 = 0.494 and 0.884, respectively. In addition, the bed occupancy rates at Al Murjan Hospital, Imam Sadiq Hospital, Hilla General Hospital, Babel Hospital for Women and Children, Al Noor Children's Hospital, and Imam Sadiq Hospital were 50 %, 92 %, 83 %, 45 %, and 50 %, respectively. Hilla General Hospital had a bed occupancy rate of 50 %. Furthermore, in order to ascertain the ways in which each independent variable affects the dependent variable, Figures 3, 4, 5, 6, and 7 show scatter plots of the daily rate of MSW generation against total patients, inpatients, and outpatients for all of the hospitals. Figures 3, 4, 5, 6, and 7 depict the linear relationship between the rate at which MSW is produced and the number of inpatients and outpatients. Equations 1, 2, 3, 4, and 5 are the subsequent linear connection-based predictive models. Equation 4 depicts the prediction model for the overall rate of inpatient and outpatient MSW generation. This study employs predictive modeling to statistically identify data patterns and the likelihood of particular outcomes.
Figure 3: The correlation between the daily numbers of inpatients and outpatients and the amount of soild medical waste produced per kilogram per day at Hilla General Teaching Hospital
Figure 4: The correlation between the daily numbers of inpatients and outpatients and the amount of soild medical waste produced per kilogram per day at Babel Hospital for Women and Children
Figure 5: The correlation between the daily numbers of inpatients and outpatients and the amount of soild medical waste produced per kilogram per day at Al Noor Children's Hospital
Figure 6: The correlation between the daily numbers of inpatients and outpatients and the amount of soild medical waste produced per kilogram per day at Imam Sadiq Hospital
Figure 7: The correlation between the daily numbers of inpatients and outpatients and the amount of soild medical waste produced per kilogram per day at Murjan Teaching Hospital
It is essential to first define the issue and collect data in order to construct a precise predictive model. Predictive modeling also lets financial departments, medical staff, and maintenance workers know about potential risks, so they can be better prepared for the future. The impact of the patient's number treated (inpatients) and outpatients differ by hospital. Various models based on various hospital types were developed as follows:
Hilla General Teaching Hospital Generation rate (kg/day)
Y = 1.565 (NOP) + 0.747 (NP) + 136.850 (1)
Babel Hospital for Women and Children Generation rate (kg/day)
Y = 0.897(NOP) +0 613(NP) + 81.373 (2)
C. Al Noor Children's Hospital Generation rate (kg/day)
Y= -0.775(NOP) + 0. 711(NP) + 7.413 (3)
D. Imam Sadiq Hospital Generation rate (kg/day)
Y = 0.462 (NP) + 11.410 (4)
E. Murjan Teaching Hospital Generation rate (kg/day)
Y = - 0.029 (NOP) +0.081 (NP) + 5.221 (5)
Where: NP = the inpatients number, NOP = the outpatients number
In addition to the values of the selected parameters, the quantity of waste generated in these hospitals is further detailed in Table 6. The rate of bed occupancy and the capacity of the hospital (the number of beds) have been identified as the most significant factors.
In order to examine their connections, similarities, and differences, the Hilla private hospitals must be included in the study scope. The following equations were derived by analyzing the application parameters used to predict overall rates and various types of hospital waste, such as sharp, infectious, pathological, and general waste:
Total = 1.813 (HT) + 1.346 (BO) + 0.507(HC) -36.492 (6)
General = – 1.636 (HT) + 1.024 (BO) +0.012 (HC) -9.508 (7)
Sharps = -2.280 (HT) + 0.041 (BO) -0.150 (HC) + 8.806 (8)
Infectious = 1.584 (HT) +0.234 (BO) +0.364 (HC) -22.188 (9)
Pathological = -2.048 (HT) +0.064 (BO) + 0.217 (HC) -5.418 (10)
Where: HC = hospital capacity and BO = bed occupancy
Table 7 displays the generated model's statistical characteristics. Furthermore; hospital capacity and bed occupancy are significant parameters that have an effect on residuals (≤ 0.05), as determined by the model statistical characteristics. Accurate prediction of medical waste generation rate is an essential component of hospital waste management systems. The study objective was to develop a reliable model for anticipating these numbers. The MLR model was used in this study to predict five distinct kinds of hospital waste. The generation rate and the relevant active variables for the generation rate of medical waste are correlated linearly in the findings. The ability of linear rule-based models to specify the significance of each parameter, emphasizing their success in predicting the rate of the production of medical waste, is one of the most significant advantages. The findings are encouraging and may aid in the development of effective waste management practices for medical waste, including its sources, generation, collection, transportation, treatment, and disposal.
Hilla General Teaching Hospital Generation rate (kg/day)
Y = 1.565 (NOP) + 0.747 (NP) + 136.850 (1)
Babel Hospital for Women and Children Generation rate (kg/day)
Y = 0.897(NOP) +0 613(NP) + 81.373 (2)
C. Al Noor Children's Hospital Generation rate (kg/day)
Y= -0.775(NOP) + 0. 711(NP) + 7.413 (3)
D. Imam Sadiq Hospital Generation rate (kg/day)
Y = 0.462 (NP) + 11.410 (4)
E. Murjan Teaching Hospital Generation rate (kg/day)
Y = - 0.029 (NOP) +0.081 (NP) + 5.221 (5)
Where: NP = the inpatients number, NOP = the outpatients number
In addition to the values of the selected parameters, the quantity of waste generated in these hospitals is further detailed in Table 6. The rate of bed occupancy and the capacity of the hospital (the number of beds) have been identified as the most significant factors.
In order to examine their connections, similarities, and differences, the Hilla private hospitals must be included in the study scope. The following equations were derived by analyzing the application parameters used to predict overall rates and various types of hospital waste, such as sharp, infectious, pathological, and general waste:
Total = 1.813 (HT) + 1.346 (BO) + 0.507(HC) -36.492 (6)
General = – 1.636 (HT) + 1.024 (BO) +0.012 (HC) -9.508 (7)
Sharps = -2.280 (HT) + 0.041 (BO) -0.150 (HC) + 8.806 (8)
Infectious = 1.584 (HT) +0.234 (BO) +0.364 (HC) -22.188 (9)
Pathological = -2.048 (HT) +0.064 (BO) + 0.217 (HC) -5.418 (10)
Where: HC = hospital capacity and BO = bed occupancy
Table 7 displays the generated model's statistical characteristics. Furthermore; hospital capacity and bed occupancy are significant parameters that have an effect on residuals (≤ 0.05), as determined by the model statistical characteristics. Accurate prediction of medical waste generation rate is an essential component of hospital waste management systems. The study objective was to develop a reliable model for anticipating these numbers. The MLR model was used in this study to predict five distinct kinds of hospital waste. The generation rate and the relevant active variables for the generation rate of medical waste are correlated linearly in the findings. The ability of linear rule-based models to specify the significance of each parameter, emphasizing their success in predicting the rate of the production of medical waste, is one of the most significant advantages. The findings are encouraging and may aid in the development of effective waste management practices for medical waste, including its sources, generation, collection, transportation, treatment, and disposal.
Table 6: Waste generation rate for all hospitals in Hilla of city
| Name of hospital | Capacity (beds) | Bed occupancy (%) | Waste generation rates (kg/day) | |||
| General | Sharp | Infectious | Pathological | |||
| General Teaching Hospital | 499.00 | 92.00 | 495.00 | 8.18 | 128.00 | 33.00 |
| Women and Children Hospital | 295.00 | 83.00 | 285.00 | 5.80 | 85.00 | 41.00 |
| Al Hussein Children hospital | 65.00 | 45.00 | 55.00 | 1.50 | 8.16 | 0.01 |
| Al-Furat Al-Awsat Hospital | 35.00 | 35.00 | 25.00 | 6.84 | 0.18 | 11.80 |
| AL-Shifa Hospital | 25.00 | 70.00 | 15.00 | 0.11 | 5.87 | 8.50 |
| AL-Diwaniya Hospital | 22.00 | 50.00 | 18.00 | 0.45 | 2.83 | 3.50 |
Table 7: The developed MLR models statistical characteristics
| Type of hospital waste |
Parameter | Parameter estimate |
Standard error |
T-value | a-Level | R2 |
| Total | Intercept HT BO HC |
-36.452 1.813 1.436 0.787 |
11.223 7.241 0.031 0.218 |
-3.159 0.237 43.492 2.234 |
0.013 0.825 0.001 0.043 |
0.998 |
| General | Intercept HT BO HC |
-9.408 -1.676 1.014 0.013 |
1.418 0.915 0.004 0.028 |
-6.633 -1.831 261.283 0.484 |
0.000 0.076 0.000 0.631 |
0.997 |
| Sharp | Intercept HT BO HC |
8.856 -2.280 0.031 -0.140 |
1.149 0.741 0.003 0.022 |
7.709 -3.077 9.878 -6.256 |
0.000 0.004 0.000 0.000 |
0.816 |
| Infectious | Intercept HT BO HC |
-22.188 1.584 0.238 0.364 |
2.903 1.873 0.008 0.056 |
-7.643 0.846 29.937 6.449 |
0.000 0.404 0.000 0.000 |
0.996 |
| Pathological | Intercept HT BO HC |
-5.215 -2.038 0.054 0.227 |
6.241 4.027 0.017 0.121 |
-0.836 -0.506 3.149 1.869 |
0.409 0.616 0.004 0.71 |
0.745 |
Discussion
The composition of MSW is influenced by the size and type of healthcare services, solid waste management practices like handling, segregation, and disposal, and solid waste regulations. On the other hand, it depends on how busy it is, the department type (surgical theatre or office), its location (rural or urban area), and the development of the country's infrastructure 14-15. On the other hand, this could be due to the fact that solid waste is not separated in a way that makes sense. MSW pollutes materials with blood when it is not sorted, resulting in an excessive amount of infectious solid waste 15. The value of the waste decreased due to the rising cost of handling MSW 12,24. Solid waste management relies on segregation, which must be carried out at the source of biomedical solid waste generation in order to prevent contamination of the entire quantity of residuals 18,25. In terms of the individual factors effect, with the increase of each bed occupancy unit (%), the annual production of MSW increased. Furthermore, comparing to the hospitals in other cities of Iraq, such as Baghdad and Tikrit, there are some variations as a result of different hospital systems. These could be due to variations in the infrastructure of public health, a higher rate of urbanization, or a greater availability of resources. Due to the larger population and higher rates of poverty in Tikrit, the quality and accessibility of medical care may also differ. The present study at the Hilla hospital in Iraq reveals the need for more effective infection control measures. In addition, the findings of the survey suggest that not everyone is aware of or has access to medical care. In developing nations, however, the issue of medical waste has not received enough attention. When medical waste is still disposed of as normal waste, public health, the health of municipal workers, and the environment are at risk 26. Moreover, no comprehensive investigation has been conducted on the waste management practices of healthcare facilities like hospitals and clinics. Waste management is typically handled by untrained workers, who carry out the majority of tasks with little supervision 27. Therefore, there is no accurate information about the amount of waste generated by hospitals and waste management. This issue has a negative impact on the collection, interim storage, transportation, and disposal phases of their management 28.
The study shows that a variety of factors, including the number of beds, the type of hospital or healthcare facility, services, the number of annual inpatients, the number of days spent there, the number of scheduled surgeries, the presence of specialized units (like the intensive care unit), and the overall workforce, all have an effect on the volume of solid medical waste generated at Hilla public hospital. Some of these criteria, like the type of hospital and the ratio of inpatients to outpatients, have also been identified and supported by studies from Taiwan, Jordan, Kuwait, India, Nigeria, and Greece 29-34.
Conclusion
In order to regulate and improve the current situation in Hilla, a crowded city, it is essential to provide adequate solid medical waste management. Complete management of solid medical waste necessitates precise waste assessment. The development of a reliable model for predicting the amount of solid medical waste produced is the goal of this study. Long-term data on the composition and generation rate of solid healthcare waste as well as the development of predictive models were obtained through the use of a longitudinal study design. The majority of medical waste is general and infectious. To accurately estimate the rate of the generation of MSW, this study demonstrated that two units of measurement-kg/inpatient/day and kg/outpatient/day-should be utilized simultaneously. The number and type of hospitals may also have an impact on the generation of MSW. The results demonstrated that there was a clear linear relationship between the actual rate of generation of medical waste and the rate of generation. In addition, the effectiveness of linear rule-based models in predicting medical waste was demonstrated by their capacity to precisely determine the weights of each parameter. The field study of some Hilla hospitals solid waste management systems revealed that the implementation of the solid medical waste management system lacks a methodical and practical approach. Additionally, the majority of Hilla's hospitals' employees are unaware of the requirements for safety, worker protection, and medical waste. Medical waste bags are also not used to treat infectious tissue waste or bacterial culture dishes in the majority of hospitals. They also suffer from improperly handling chemical drug remnants used to treat cancer patients and treating them like any other medical waste. Such waste contains substances that can harm or kill human cells, posing a risk to workers. The study findings will be beneficial to Hilla, since they may help develop a reliable model for predicting MSW. Additionally, the quantity of MSW produced in the past could be used in facility design and planning. A strategy plan for building a suitable MSW management system can be created using the research model.
Acknowledgement
The authors would like to thank Babylon Health Directorate for for giving permission to conduct this research.
Funding
The author(s) received no financial support for the research.
Conflict of interest
The authors declare that there is no conflict of interest.
This is an Open -Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt, and build upon this work for commercial use.
References
The composition of MSW is influenced by the size and type of healthcare services, solid waste management practices like handling, segregation, and disposal, and solid waste regulations. On the other hand, it depends on how busy it is, the department type (surgical theatre or office), its location (rural or urban area), and the development of the country's infrastructure 14-15. On the other hand, this could be due to the fact that solid waste is not separated in a way that makes sense. MSW pollutes materials with blood when it is not sorted, resulting in an excessive amount of infectious solid waste 15. The value of the waste decreased due to the rising cost of handling MSW 12,24. Solid waste management relies on segregation, which must be carried out at the source of biomedical solid waste generation in order to prevent contamination of the entire quantity of residuals 18,25. In terms of the individual factors effect, with the increase of each bed occupancy unit (%), the annual production of MSW increased. Furthermore, comparing to the hospitals in other cities of Iraq, such as Baghdad and Tikrit, there are some variations as a result of different hospital systems. These could be due to variations in the infrastructure of public health, a higher rate of urbanization, or a greater availability of resources. Due to the larger population and higher rates of poverty in Tikrit, the quality and accessibility of medical care may also differ. The present study at the Hilla hospital in Iraq reveals the need for more effective infection control measures. In addition, the findings of the survey suggest that not everyone is aware of or has access to medical care. In developing nations, however, the issue of medical waste has not received enough attention. When medical waste is still disposed of as normal waste, public health, the health of municipal workers, and the environment are at risk 26. Moreover, no comprehensive investigation has been conducted on the waste management practices of healthcare facilities like hospitals and clinics. Waste management is typically handled by untrained workers, who carry out the majority of tasks with little supervision 27. Therefore, there is no accurate information about the amount of waste generated by hospitals and waste management. This issue has a negative impact on the collection, interim storage, transportation, and disposal phases of their management 28.
The study shows that a variety of factors, including the number of beds, the type of hospital or healthcare facility, services, the number of annual inpatients, the number of days spent there, the number of scheduled surgeries, the presence of specialized units (like the intensive care unit), and the overall workforce, all have an effect on the volume of solid medical waste generated at Hilla public hospital. Some of these criteria, like the type of hospital and the ratio of inpatients to outpatients, have also been identified and supported by studies from Taiwan, Jordan, Kuwait, India, Nigeria, and Greece 29-34.
Conclusion
In order to regulate and improve the current situation in Hilla, a crowded city, it is essential to provide adequate solid medical waste management. Complete management of solid medical waste necessitates precise waste assessment. The development of a reliable model for predicting the amount of solid medical waste produced is the goal of this study. Long-term data on the composition and generation rate of solid healthcare waste as well as the development of predictive models were obtained through the use of a longitudinal study design. The majority of medical waste is general and infectious. To accurately estimate the rate of the generation of MSW, this study demonstrated that two units of measurement-kg/inpatient/day and kg/outpatient/day-should be utilized simultaneously. The number and type of hospitals may also have an impact on the generation of MSW. The results demonstrated that there was a clear linear relationship between the actual rate of generation of medical waste and the rate of generation. In addition, the effectiveness of linear rule-based models in predicting medical waste was demonstrated by their capacity to precisely determine the weights of each parameter. The field study of some Hilla hospitals solid waste management systems revealed that the implementation of the solid medical waste management system lacks a methodical and practical approach. Additionally, the majority of Hilla's hospitals' employees are unaware of the requirements for safety, worker protection, and medical waste. Medical waste bags are also not used to treat infectious tissue waste or bacterial culture dishes in the majority of hospitals. They also suffer from improperly handling chemical drug remnants used to treat cancer patients and treating them like any other medical waste. Such waste contains substances that can harm or kill human cells, posing a risk to workers. The study findings will be beneficial to Hilla, since they may help develop a reliable model for predicting MSW. Additionally, the quantity of MSW produced in the past could be used in facility design and planning. A strategy plan for building a suitable MSW management system can be created using the research model.
Acknowledgement
The authors would like to thank Babylon Health Directorate for for giving permission to conduct this research.
Funding
The author(s) received no financial support for the research.
Conflict of interest
The authors declare that there is no conflict of interest.
This is an Open -Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt, and build upon this work for commercial use.
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Type of Study: Original articles |
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Environmental Health, Sciences, and Engineering
Received: 2022/11/12 | Accepted: 2023/01/20 | Published: 2023/03/27
Received: 2022/11/12 | Accepted: 2023/01/20 | Published: 2023/03/27
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