Addressing the healthcare waste management barriers: A structural equation modeling approach

Abstract

Due to the growing population and advancing economy, medical waste accumulation has come to the attention of all facets of society. Although the issue of medical waste management planning has been addressed in developed nations, it still exists in several developing nations. This paper examines the effects of barriers under the Organization action, work handling, and Human Resource Practices section on the healthcare waste management (HCWM) sector in a developing country India. In this study, three hypotheses were constructed and tested using Structural equation modeling. The questionnaire was distributed among 200 health professionals to collect their responses. Ninety-seven responses were received, and 15 barriers were identified affecting the healthcare waste management sector. The results show that all three barriers (i.e., Organizational, Waste handling, and Human resources) hinder the Healthcare waste management sector. Organizational Barriers are the most significant among other barriers. So, the hospitals have to take appropriate actions to overcome these barriers. This paper helps to complete the research gap by providing the different characteristics of barriers. The development of a model for the analysis of barriers influencing HCWM is the Author’s original contribution.

Keywords

healthcare barriers waste management hospitals structural equation modeling

Introduction

Healthcare waste is a highly growing waste globally. The amount of generated waste is also a topic of concern. A waste audit is one way to quantify the waste and determine carbon emissions in that scenario because it will lower the disposal costs.¹ Environmentally friendly methods and cost-effective pathways are needed for proper waste management in the healthcare industry. Regarding healthcare waste management, collection and segregation are the most critical steps. Many healthcare wastes are non-hazardous, so proper segregation is necessary to avoid the unnecessary cost of their treatment. Recycling and reprocessing healthcare waste is also one of the methods to reduce the amount of healthcare waste.

COVID-19 is a pandemic in the present context which affected the whole world. This disease is highly infectious, so proper healthcare waste treatment is mandatory to avoid spreading it. The entire world is facing different types of conditions regularly. If the waste generated through the patient area is not correctly disposed of, it will harm other people. In this way, healthcare waste management is a crucial topic for all developed and developing nations.² The demands placed on hospitals are rising along with the global population. Healthcare waste management is difficult to manage correctly. More than 70% of wastes are non-hazardous. Almost 15% of generated Healthcare waste is considered Biomedical Waste; the rest is general waste similar to household Waste (Biomedical Waste Management Rules, 2016).

Many countries have already imposed strict regulations on healthcare waste disposal. However, various barriers and problems still need to be solved, restricting the adequate disposal of healthcare waste. In India, there is unequal access to healthcare services because of unequal resource allocation, insufficient infrastructure, and the high cost of health services. Properly disposing of healthcare waste is challenging, so healthcare waste management is also receiving considerable attention after implementing Biomedical waste management and handling rules in 1998. The amount of waste generation in India varies from 0.5 to 2 kg per bed and per day, and it counts to 0.33 million per year; it is an enormous amount of waste to be controlled judiciously.³ India has over six lakh hospital beds, 23,000 health centers, and licensed nursing homes. Numerous hospitals and dispensaries operate illegally, and their numerous health centers operate in every nook and cranny of urban and semi-urban areas.⁴

In resource-constrained countries such as India, healthcare expenditure is insufficiently low and is less than 2% of the gross domestic product (GDP).⁵ Unplanned urbanization coupled with increased consumerism is linked to increases in the per capita generation of Waste. Furthermore, rapid urbanization and population growth create larger population centers, making the collection of all waste and procuring land for treatment and disposal more and more difficult.

It is not easy for healthcare organizations to handle healthcare waste because these organizations have varieties of barriers. As a result of this, several healthcare sectors worldwide are facing problems related to healthcare waste management. These problems and challenges are termed barriers for healthcare organizations. A significant challenge is a need for more awareness and general alertness for recycling Waste from HCFs.⁶

Various research on Health Care Waste Management complications in different countries has already been done.^7–9 However, specific research related to HCWM barriers is limited to developing countries like India. This paper’s contribution is to complete the research gap by considering the effects of organizational waste handling and human resource barriers on healthcare waste management, particularly for healthcare facilities in India, one of the world’s most highly populated countries.

Literature review

We know that international trade agreements must escalate the economic benefits, but it is not as good for health. Due to the emergence of pandemics (COVID-19), different healthcare waste types have been increasing. There are well-equipped procedures for handling healthcare waste. The usual disposal and treatment methods for waste in developing countries are open dumps and Uncontrolled landfills.

Until 2003, China paid less attention to waste management, but after the waste management Act 380, China became severe. According to this act, centralized waste removal is obligatory.¹⁰ Proper waste segregation is unavoidable, and if there is a failure in parting, it will be highlighted by the Healthcare waste pointers.¹¹ If the workers are not adequately trained, they will not understand the exercise code’s prominence, and there is always a risk of life to workers, patients, and other people.⁷ One of the South Eastern Country Indonesia’s capitals, Jakarta, faces NIMBY (Not in My Backyard) syndrome. Most prevailing and prospective landfill sites will be filled by 2020.⁹ One recent study suggests that there must be control over the quantity of waste generated to implement healthcare waste management properly. The amount of waste generated can be restricted by using innovative waste management techniques. Hospitals should decrease their disposal costs by refining their classification methods and employing suitable methods for particular types of waste.¹²

A study was performed in Ghanaian hospitals about healthcare waste management. The results show that healthcare professionals have a good level of awareness about healthcare waste and more HCW disposal materials in private than in government and semi-government hospitals. Population and fast urbanization growth make healthcare waste treatment a highly challenging municipality task. Now it has gained significant attention all over the world. The sustainability of HCW treatment systems was analyzed in environmental, financial, social, and technical criteria.

One recent study suggests there must be control over the quantity of waste generated for proper healthcare waste management implementation. The amount of waste generated can be restricted by using innovative waste management techniques. Hospitals should decrease disposal costs by refining their classification methods and employing suitable methods for particular waste types.¹² In Asian developing countries, less attention is given to it despite having such a severe issue. A serious issue is a need for waste management strategies, firm policies, adequate knowledge, awareness, strict regulation, and sufficient funds.¹³

All healthcare waste management barriers have been classified and ranked according to three dimensions or factors: organizational barriers (OB), waste handling barriers (WHB), and human resource barriers (HRB). A case study was performed on three hospitals, their Stainless-steel waste was collected, and a repair and recycling approach was performed. This increased the instrument’s life cycle and saved on waste handling costs.¹⁴ If the healthcare waste is within the range, it is a good practice for this. The staff of the hospital must be aware and trained. Green purchasing suppliers is also a good option.¹⁵

The findings demonstrate that low and middle-income countries generate less medical waste than industrialized and high-income nations. The average trash generation rate per daily bed varies from 0.3 to 8.4 kg. The two countries that produce the most medical waste are the United States and Canada (8.4 and 8.2 kg/bed/day, respectively). Asia, Kazakhstan, and Iran produce the most medical waste (4.6 kg/bed/day), whereas Spain and Italy produce the most in Europe (4.4 and 4.1 kg/bed/day, respectively). Pakistan and Greece (each 0.3 kg/bed/day) have the lowest medical waste generation rates.

Figure 1 shows the medical waste generation rate and the controlled solid waste management EPI ratings. The regulated solid waste management EPI scores in the investigated nations range widely from zero in Tanzania, Ethiopia, Libya, and Palestine to one hundred in the Netherlands. According to the findings, low- and middle-income countries had lower EPI scores than most wealthy nations. Therefore, wealthy nations have better-controlled solid waste management while significantly generating medical waste. As a result, the created medical waste is ultimately disposed of properly.

Figure 1.

EPI score of countries.³⁴

The findings indicate that, on average, 45% of employees understood how medical waste should be handled and disposed of Senegal had the most significant percentage with knowledge and awareness of medical waste disposal, while Malaysia had the lowest rate at only 12%, placing it last among the countries analyzed. Figure 2(c) displays the number of employees who attended in-service training for handling medical waste.

Figure 2.

Condition of waste management.³⁴

China has the most significant percentage of trained workers among the analyzed nations, at an average of 80%. The lowest in-service training was found in Egypt and India, where each country’s average was 20%. The amount of medical waste segregation in the analyzed nations is depicted in Figure 2(d). The findings indicate that, on average, 33% of the medical waste was separated at the point of generation. While Uganda and Ghana only sort about 7% and 17% of their total medical waste, respectively, China separates almost 75%.

Data description

A self-reported questionnaire was used for this purpose. Two hundred healthcare professionals were contacted, and 97 responded. All respondents who worked in the healthcare industry the responders were hospital employees, while others were medical students, doctors, and other hospital administration staff. Both public and private hospitals provided respondents.

The response rate of the questionnaire was 48.5%. All the participants were informed about the study’s scope and asked to complete the questionnaire. The responses to the questionnaire were kept anonymous. Respondents voluntarily agreed to participate in the survey.

Materials and method

Measurement of variables

The questionnaire used in the study collected data related to healthcare waste management barriers faced by healthcare professionals. For measuring the HCWM barriers in the hospitals, the hospital staff was asked to fill out the questionnaire with the help of a Likert scale (from 1 = strongly disagree to 7 = strongly agree). For the healthcare waste management barriers, 15 sub-barriers” were selected based on Exploratory factor analysis (EFA). The barriers were categorized into three dimensions or factors, shown in Table 1: Organizational Barrier, Waste Handling Barrier, and Human Resource Barrier. The organizational barrier consists of eight sub-barriers (OB1- OB 8); organizational barriers are present within the organizational policy, rules, structure, facilities, etc. Waste handling barriers include five sub-barriers (WHB1-WHB5). These include exorbitant costs and other difficulties in creating and maintaining a suitable waste collection and disposal infrastructure. There must be a training and awareness program for staff to understand the repercussions of not managing healthcare waste effectively. Human resource barriers have two subcarriers (HRB1-HRB2). The importance of these 15 sub-barriers in the healthcare waste management sector was part of the three main barriers used as the basis for the study.

Table 1.

Shows the categorical details of the barriers.

Barriers	Sub barriers	Sub barriers coding
Organizational Barrier (OB)	People do not want to change their thinking	OB1
	Lack of coordination of hospitals with other authorities	OB2
	No priority to waste management issues	OB3
	No strict implementation of control measures	OB4
	No information regarding waste quantity and compositions	OB5
	No availability of recycling centers in Hospitals	OB6
	Lack of regular monitoring of healthcare waste	OB7
	Lack of intelligent waste management techniques	OB8
Waste Handling Barrier (WHB)	No availability of segregation bins	WHB1
	Lack of support from Management	WHB2
	No place for temporary storage and segregation	WHB3
	Lack of Govt. support and policies	WHB4
	No tools and precautions to handle healthcare waste	WHB5
Human Resource Barrier (HRB)	Lack of Qualification and Awareness of Employees	HRB1
Human Resource Barrier (HRB)	Poor training of staff	HRB2

Research hypothesis

OB has a positive influence on HRB and WHB in the Indian context. The Organizational barrier profoundly influenced the healthcare waste management sector; without overcoming these barriers, appropriate Management of healthcare waste is impossible. Things become more challenging if hospital staff refuses to adjust their opinions and if hospital management does not regularly examine waste management.^4,16 Organizational barriers promote waste handling barriers because, without proper management support in the Organization, waste handling is not secure. In the Waste handling barrier, the first barrier that must be eliminated is the availability of diverse separation bins according to the obtainability of different types of waste.¹⁷

Similarly, if hospitals are not synchronized with the pollution control board and municipal corporation, collection, handling, and shipping will not be accessible.^18,19 Hospitals must give special attention to healthcare and disinfectant techniques (Including incineration, chemical disinfection, and physical disinfection). Incineration is one of the most popular disposal methods since it is risk-free, easy to use, and efficient, especially in underdeveloped nations.²⁰ The exit temperature of the incinerator is about 800°C. Most organic materials might be burned and incinerated at this high temperature, turning them into inorganic dust and entirely killing all microbes. The volume of solid wastes could be reduced by 85–90% after incineration.²¹ Chemical disinfection technology has a long history and a wide range of applications. Chemical treatment of hospital wastes is usually used in combined crushing treatment.²² Generally, crushed hospital wastes are mixed with chemical disinfectants (such as sodium hypochlorite, calcium hypochlorite, chlorine dioxide, etc.) and stay for a sufficient time. During the disinfection, organic substances decompose microorganisms are killed or inactivated. In the physical disinfection technique, microwave disinfection technology is used; energy-saving, low action temperature, slow heat loss, quick response, light damage, minimal environmental pollution, and no residues or toxic waste after disinfection are some of the characteristics of microwave disinfection technology.²³ There must be appropriate disinfectant techniques to reduce the waste’s harmful effects.¹⁷ For proper handling of the waste, the accessibility of the handling tools and the handler in the Organization must be adequately trained to operate handling tools.^19,24 The waste that is easy to recycle wastes centers inside the hospitals, reducing the amount of waste to be burned up. The recycled product can be easily useable.^25,26 The hypothesis relating to these variables are developed. H1:

Organizational barriers profoundly influence the waste handling barrier.

Organizational barriers profoundly influence Human resource barriers. Human resource barriers were found as essential barriers to implementing healthcare waste management. If the waste-handling person is unaware of the waste’s adverse impacts, it is a crucial barrier.^18,25 Healthcare waste management consists of collecting, handling, and transporting, so top authorities' dedication is required to operate correctly. There must be some arrangement for the temporary storage of waste. When the incineration plant is not available, storage of the waste in the collection center occurs. The hospitals must organize training sessions for the staff regarding healthcare waste management. H2:

Organizational barriers profoundly influence the human resource barrier.

Awareness and qualification are both necessary for the handler because if the driver is unaware of adverse impacts, it will be hard to remove this barrier. If the workers are not appropriately trained, they will not handle the waste with assigned precautions. So, there must be proper training of workers regularly. Training will improve awareness of new techniques and measures to take healthcare waste.^4,19 Government support and policies always place a critical role as a barrier to healthcare waste management implementation. H3:

Human resource barriers profoundly influence the waste handling barrier.

The first hypothesis is that the OB influences the Waste handling barrier, and the second is that it will enhance the Human resource barrier. The study wants to determine whether OB has direct or indirect effects on WHB and HRB, and it examines a third hypothesis for these two dependent constructs: that there is an immediate effect of HRB on WHB. For this, it looks at the relationships among OB, WHB, and HRB within the context of the Healthcare waste management sector. The model is shown in Figure 3, based on three primary constructs: OB, WHB, and HRB.

Figure 3.

Path analysis model.

Data analysis

IBM SPSS, version 21.0, was used to analyze the collected data. Exploratory Factor Analysis was run using the maximum likelihood method for the data. Factor loadings were determined for each item of the questionnaire item in Table 2. A factor loading above 0.45 suggests that the item loads sufficiently on the respective factor.²⁷ It is clear from Table 2 that all items load significantly on their respective factors.

Table 2.

Internal consistency and convergent validity of theoretical model.

Barriers	Sub barriers	Sub barriers coding	Cronbach α	Factor loading	Eigen value	Percent of variance explained	Cum percent
Organizational Barrier	People do not want to change their thinking	OB1	0.909	0.788	4.798	31.986	31.986
	Lack of coordination of hospitals with other authorities	OB2		0.759
	No priority to waste management issues	OB3		0.757
	No strict implementation of control measures	OB4		0.754
	No information regarding waste quantity and compositions	OB5		0.722
	No availability of recycling centers in Hospitals	OB6		0.721
	Lack of regular monitoring of healthcare waste	OB7		0.705
	Lack of intelligent waste management techniques	OB8		0.705
Waste Handling Barrier	No availability of segregation bins	WHB1	0.824	0.857	3.007	20.047	52.033
	Lack of support from Management	WHB2		0.818
	No place for temporary storage and segregation	WHB3		0.763
	Lack of Govt. support and policies	WHB4		0.531
	No tools and precautions to handle healthcare waste	WHB5		0.510
Human Resource Barrier	Lack of Qualification and Awareness of Employees	HRB1	0.689	0.881	1.872	12.480	64.513
Human Resource Barrier	Poor training of staff	HRB2	0.689	0.752	1.872	12.480	64.513

After the EFA and reliability analysis, a path analysis model using structural equation modeling (SEM) was prepared. IBM AMOS was used for this purpose. This path analysis model was used to determine the effect of OB, HRB, and WHB on Healthcare Waste Management.

In the SEM, an endogenous variable is one whose value is determined or influenced by one or more exogenous variables taken to be independent. Thus, an exogenous variable is defined as one whose value is not affected by other variables in the model. The significance of direct, indirect, and the total effect of exogenous variables on endogenous variables was determined using this model. The direct effect is the effect that an exogenous variable directly has on an endogenous variable. An indirect effect is an exogenous variable’s effect on an endogenous variable through some mediating variables. For example, the OB effect on HRB directly is the direct effect, but the effect of OB on WHB through HRB is indirect. The addition of direct and indirect effects is the total effect.

To perform path analysis, knowing the distributional characteristics of the data is essential. Since the data needed to follow the univariate normal distribution, a univariate normality test was conducted, and the results are shown in Table 3. Since the skewness for the variables ranged between −1.008 and 1.2, and kurtosis ranged between −1.006 and 5.32, the conditions for univariate normal distribution²⁸ were satisfied as the respective absolute values of skewness and kurtosis did not exceed 2 and 7. The values for asymmetry and kurtosis between −2 and +2 are considered acceptable to prove normal univariate distribution.²⁹ Hair et al.³⁰ argued that data is normal if skewness is between -2 to +2 and kurtosis is between -7 to +7.

Table 3.

Normality test of measured variables.

Variable	Skew	Kurtosis
OB1	−0.560	−0.426
OB2	−0.860	0.008
OB3	−0.460	−0.660
OB4	−0.710	−0.567
OB5	−0.452	−0.755
OB6	−0.707	−0.173
OB7	−0.420	−0.805
OB8	−0.931	−0.35
HRB1	0.108	−1.350
HRB2	0.005	−1.234
WHB1	−0.281	−1.066
WHB2	−0.560	−0.635
WHB3	−0.208	−1.225
WHB4	−0.028	−1.106
WHB5	−0.102	−1.090

A confirmatory factor analysis (CFA) was performed using the software AMOS to find the reliability and validity of the scales of barriers to the Healthcare waste management sector. The reliability of scales was found using Cronbach’s alpha and the Composite Reliability Index (CRI). Two of the three constructs have Cronbach’s alpha of more than 0.7. The third construct has Cronbach’s very close to 0.7 due to the smaller number of variables; the scales' values crossed the proposed level.³¹

The CFA results show that scales have a proper adjustment (S-Bχ2 = 181.510; df = 88; p = 0.000; NFI = 0.784; CFI = 0.873; RMSEA = 0.105), and all items of the factors related significantly. The extracted variance index (EVI) had a value above 0.5 for the theoretical model.

The extracted variance test was more than their corresponding EVI in Table 2 for convergent and discriminant validity. These criteria confirm that the research’s different measurements provided enough evidence of reliability with convergent and discriminant validity (Table 4).

Table 4.

Discriminant validity of measurement of theoretical model.

Latent variables	Organizational barrier	Waste handling barrier	Human resource barrier
Organizational Barrier	0.748012
Waste handling Barrier	0.681	0.7031
Human resource barrier	0.401	0.405	0.734972

Results and discussion

The SEM analysis results are in Table 5 and illustrated in Figure 4.

Table 5.

Results of SEM of the barriers.

Hypothesis	Structural relationship	Standardized coefficient	Robust t value	Hypothesis status after the test
H1: Organizational barriers profoundly influence the Waste handling barrier.	OB WHB	0.62	4.695	Supported
H2: Organizational barriers profoundly influence the Human Resource barrier.	OB HRB	0.40	3.194	Supported
H3: Human Resource barriers profoundly influence the Waste handling barrier.	HRB WHB	0.16	1.314	Supported

Figure 4.

Final path model.

For H1, (β = 0.82) shows that the Organizational barrier had an essential effect on the Healthcare waste management sector. This suggests that the more Organizational barriers have available, the higher the impact on the Healthcare waste management sector. About H2, the results found in Table 3 (β = 0.83) indicated that the Waste handling barriers also had a significant effect on the Healthcare waste management sector; as an outcome, H2 was also accepted. At last, for H3, the results obtained (β = 0.49) showed that human resource barriers had a magnificent impact on the Healthcare waste management sector. Due to this reason, H3 was accepted. Finally, this proposed that all three studied factors of barriers to the Healthcare waste management sector significantly affect. The waste handling barrier is the most notable of the three.

From the results obtained, it is possible to conclude the three investigated barriers. First, the organization created the main barrier to waste management experienced by the healthcare sector in India. Organizational barriers to the healthcare waste management sector have been considered one of the most hindering factors and one of the most challenging barriers to remove and overcome. In an organizational barrier, the most important thing is changing the current state of mind and prioritizing waste management issues. The regulatory barriers can be overcome with the help of the Organization itself. The study has suggested understanding the organizational inhibitors to create effective collaboration strategies with the Healthcare sector and appropriate policies for their elimination.

Secondly, it will conclude that the lack of waste-handling sources is the second most significant barrier to healthcare waste management.

Therefore, top Management must be considered that it is essential to have waste-handling sources for the healthcare sector. Healthcare employees’ perception is similar to Bdour¹⁷ and Tripathy,³² who consider that waste handling resources must be in the hospitals to implement healthcare waste management properly. The results are consistent with the previous, which found a positive correlation between the availability of waste handling resources and the healthcare waste management ability.

Third, this study concludes that human resources are also a barrier to the Healthcare waste management sector. Hospital staff and personnel can act as potential barriers if there is no proper training to handle healthcare waste and waste handling tools—the results regarding human resources as a barrier to the Healthcare waste management sector in the Indian context. Slackness of training in waste handling activities plays an important role. From the obtained results, it is possible to conclude that the Healthcare waste management sector will significantly depend on eliminating barriers.

Conclusion

The paper finds the effects of organizational, waste handling, and human resource barriers on the healthcare waste management sector. This paper covers the research gap in the Healthcare waste management literature by showing the relationship and effects of HCWM barriers in the Indian context.

After covering all three found barriers that have the most decisive influence on HCWM, further improvement, and control measures were promoted to change the system and processes. Organizations must provide new mechanisms offered by the government to remove barriers.

Limitations and future research

Our study’s critical findings are the first of their kind to rank the challenges facing healthcare waste management. Proactive managers can now implement solutions more quickly due to managing organizational practices and the technologies that track, manage, and report on these actions. The results can also be used to compare and contrast outcomes, obtain new insights, and broaden this study in subsequent work. They can also be improved upon and expanded into various MCDM models. Total Interpretive structural modeling (TISM), Decision-making trial, and evaluation laboratory (DEMATEL) create a hierarchy and determine links between HCWM barriers. TISM is a collaborative learning method that organizes closely related parts into a thorough, systematic model. The quality function deployment (QFD) method is used in the next section to plan services that systematically address customer requirements. In this part, the QFD tool and its use are discussed. A fuzzy logic approach is practical for judgments involving ambiguous and imprecise phenomena. The Analytic Hierarchy Process (AHP) is employed as part of a multi-criteria decision-making (MCDM) process to assign weight to barriers.

Some new factors have to be covered in future studies. One factor is the regional factor which may be included in further studies. So other regions or even different Asian countries can be had for comparing research. Additional barriers might be found by research and expert opinions, and more extraction might be made possible, for example, technical barriers, which might be one of the subgroups. The first and possibly major drawback of structural equation modeling is the issue of causal interpretation. Applications for SEM are typically based on non-experimental data. However, many SEM applications interpret the final model as a causal model. Although this may be true, correlational data cannot be magically converted into causative conclusions using structural equation modeling. The model becomes more prone to mistakes due to researchers’ need to exercise greater caution when interpreting SEM results.³³

Managerial implications

The management needs to understand the characteristics and interrelationships among factors. With the help of this study, top management can better understand the interaction of factors (internal and external), be aware of the hierarchy of factors, and use them one by one as per organization requirements. This research will help managers and decision-makers to utilize their resources effectively and save costs.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Abhishek Raj

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