An integrated approach for economic evaluation of environmental and health costs of occupational diseases in the oil industry

Abstract

The health sector is one of the components of development, social welfare and economic growth. The purpose of this study was to develop an economic evaluation model of the environmental and health costs of occupational diseases by hybrid approach. To achieve the study goal, a taxonomy of economic evaluation model of the environmental and health costs of occupational diseases has been developed. The Delphi method was used to identify health and environmental criteria and the analytic network process (ANP) method was used to weigh the sub-criteria. Finally, health and environmental cost were estimated based on the available information. Naft Subspecialty Hospital in Tehran, Iran (NSHT), was selected as the place of case study. In this study, eight and eleven sub-criteria were identified in the health and environmental sector, respectively. The ANP results indicated that the medicine and medical equipment cost criteria with a weight of 0.312 in the Medical sector, and the special and infectious waste cost criteria with a weight of 0.085 in the environmental sector were the most significant cost criteria in NSHT. Furthermore, the parametric model findings indicated that 99.84 and 0.16% of the total costs are associated with health and environmental costs, respectively. The findings indicated that 61.3% of the costs of the health sector were associated with the two sectors of medicine and medical equipment and the cost-of-service personnel, and 91.7% of the costs of the environmental sector are associated with wastewater treatment and the cost of electricity consumption. This study tried to present a quantitative model of the health and environmental costs of NSHT. Implemention of this integrated model can be a practical and effective step in allocating resources and prioritize interventions.

Introduction

Agreement of the World Trade Organization (WTO), Generalized Special Preferences (GSP), and Global Value Chain (GVC) have promoted industrialization in selected developing countries with low-cost manpower, basic industrial structure, and structural and institutional flexibility of the labor force, which has been effective in the economic growth and progress of these countries¹. Nevertheless, the development of industries and technological progress, along with its positive and valuable effects, have unfortunate impacts and complications, such as increasing the variety and severity of occupational accidents, and occupational diseases^2,3, and increasing the quantity and quality of pollution in the working and living environment^4,5. At present, accidents caused by work are considered the third cause of death in the world, the second cause of death in Iran after traffic accidents, and one of the crucial risk factors in industrialized and developing societies, which can increase costs of health, economic and environmental impact on human societies^6,7. According to the first joint estimates of the World Health Organization (WHO) and the International Labor Organization (ILO), diseases and injuries caused by work caused the death of 1.9 million people in 2016. Based on this report, 81% of deaths are caused by chronic diseases (lung obstruction, stroke, and ischemic heart disease), and occupational injuries cause 19% of deaths⁸.

Moreover, besides human suffering, occupational accidents impose a great economic cost on society^9,10. The estimate of the International Social Security Association (ISSA) (2014) reveals that the average cost of occupational accidents and diseases, spent on visible and invisible costs caused by professional and health accidents, is approximately 4% of the world's gross domestic product per year. Furthermore, evidence suggests that occupational injuries, illnesses, and deaths cost employers and society besides the employee^11,12. A study by Safe Work Australia¹¹ indicated that workers, employers, and society bear approximately, respectively, 77%, 5%, and 18% of the cost of occupational injuries and illnesses. Shalini¹² reveals that employers incur between US$11,287 and US$132,749 in medical costs for a fatal occupational accident, whereas the employee incurs a maximum of US$185,358, which depends on the number of man-days lost from work because of occupational injuries.

As health is a state of complete physical, mental and social well-being and not merely the absence of disease⁸, it is essential to create and develop safe structures in work environments and prevent accidents and occupational illnesses, and health and environmental damage. Regarding this, identifying and examining the causes of accidents and diseases caused by work and the economic valuation of health and environmental costs can be a public motivation to deal more seriously with these problems to prevent their recurrence and to protect and protect labor and capital^13,14,15. In other words, information about the economic burden of occupational injuries and diseases helps make decisions at various levels and makes it necessary to explain the economic justification of programs, policies, and investments associated with occupational health and safety^16,17. Having a clear understanding of the costs of occupational accidents increases the motivation for improving occupational safety and health by managers¹⁷. Besides that, everyone agrees that the managers of business units in industries in the current era besides reducing operational costs should reduce health and environmental costs resulting from accidents to minimize the work due to the limited resources and the increase of contamination of industries on the welfare level of societies¹⁸. Identifying, classifying, evaluating, and estimating the economic costs of the health and environmental sectors using MCDM methods could enhance awareness of industry managers, especially large industries such as oil and gas, in a work environment^18,19.

Several studies have used multi-criteria decision-making (MCDM) methods recently such as DEMATEL-ANP, AHP, ANP, and DEA to assess risk factors in the oil and gas industry^20,21,23. These methods are especially useful for dealing with complex problems, complex systems, uncertain variables, and limited information. Dehdasht et al.²⁰ conducted a study on risk assessment in oil and gas industry construction projects in Iran using the DEMATEL-ANP method. The ANP method results indicated that experts are more concerned about “financial” and “technical” aspects in the risk evaluation of OGC projects because the weight of these risk groups was significantly higher than other dimensions. Li et al.²¹ analyzed the relationship between occupational accidents and five economic indicators, such as resident consumption, energy consumption, education funds, wage level and research input. The results show that there is a strong correlation between accident and economic indicators, and the comprehensive correlation coefficient among scientific research investment, education funds and accident indicators is significantly higher than that of other economic indicators. Tompa et al.¹⁶ examined the economic burden of occupational injuries and illnesses in five European Union countries (Poland, Italy, Germany, Finland, and the Netherlands). Hoque et al.¹ examined the effects of industrial processes on social, environmental, and public health degradation in Bangladesh. Dehdasht et al.²⁰ conducted a study on risk assessment in oil and gas industry construction projects in Iran using the DEMATEL-ANP method. The ANP method results indicated that experts are more concerned about “financial” and “technical” aspects in the risk evaluation of OGC projects because the weight of these risk groups was significantly higher than other dimensions. Baratchi et al.²² examined health risks based on the MCDM method. In this study, all the hazards of various units of a medical center were selected with the help of hazard identification checklists and were ranked using the ANP method. Beriha et al.²³ used an occupational health and safety performance measure in industries that used data envelopment analysis (DEA) as a robust mathematical evaluation tool on 30 Indian organizations. Leppink⁹ examined the socioeconomic costs of occupational injuries and illnesses and created synergies between occupational health and safety and productivity.

Abbaspour et al.²⁴ presented a parametric environmental cost model in oil and gas EPC contracts. The findings demonstrated that one of the most significant weighing elements for the entire project is the environmental management component. They stated that the proposed model can be considered as an innovative approach to determine environmental indicators in oil and gas projects. Omidvari et al.²⁵ presented a conceptual model for identifying and ranking environmental risks in an industrial town using the Delphi and DEMATEL technique. The results showed that the index of "low share of environmental investment" was the most important economic criterion. Shahbod et al.²⁶ in a study applied the Delphi method and the fuzzy hierarchical analysis process in the modeling of environmental performance evaluation in urban medical centers. The results showed that the sewage disinfection index is the most important index in evaluating the environmental performance. The review of the literature showed that previous research has concentrated on investigating and presenting a parametric model of environmental costs in oil and gas EPC contracts, diseases and dangers prevalent in the oil and gas sector, and variables affecting the physical and mental well-being of refinery people. In another research, modeling of environmental performance evaluation in urban medical centers has been done using the Delphi method and fuzzy hierarchical analysis process. In this study, the health and environmental risks were investigated with respect to economic aspects, environmental costs, occupational illnesses, and health and environmental concerns. An integrated approach that considers both the health and environmental impacts of these diseases can provide a more comprehensive evaluation of their costs. This approach involves assessing the direct and indirect costs associated with occupational diseases, including medical expenses, lost productivity, and environmental damage. By incorporating these factors into economic evaluations, policymakers and industry leaders can make more informed decisions about prevention and mitigation strategies. To accomplish this, we employed a hybrid method that combined the Delphi method and the Analytical Network Process (ANP). As a result, we were able to create a quantitative model to assess the costs associated with occupational diseases in the oil industry, a topic that has not been previously.

Materials and methods

Study area

Naft Subspecialty Hospital in Tehran, Iran (NSHT), was selected as the place of case study. The present study was approved by the Ethics Committee of the Islamic Azad University, Research and Sciences branch (ethics code: 950316001), and all methods were performed in accordance with the relevant guidelines and regulations. "All the participants gave full "informed" consent to participate in the present study, and before the start of the study, the consent form to participate in the study was completed by all the participants.". Participants were able to withdraw from the study at any stage if they were not satisfied.

Method

This study introduces a novel hybrid approach to assess the environmental and health costs of occupational diseases. It is underpinned by a comprehensive integration of the Delphi method, and the analytic network process (ANP). By combining these analytical tools, the devised approach offers a comprehensive means of evaluating the multifaceted dimensions of environmental and health costs of occupational diseases in medical settings. The Delphi method's collaborative expertise, coupled with the structured decision-making process of ANP coalesce to form a effective framework for economic evaluation. The study was conducted in eight general steps. The overall steps of the present study are given in Fig. 1.

• (1) Review of the existing situation and extensive literature review

• (2) Identification of health and environmental criteria

• (3) Determining independent and dependent sub-criteria

• (4) Screening of criteria using the Delphi method

• (5) Weighting of the sub-criteria according to ANP methodology

• (6) Developing a parametric conceptual health and environmental model

• (7) Developing a hybrid model to estimating health and environmental costs

• (8) Model validation by using linear regression model.

Figure 1

Model of economic evaluation of environmental and health costs caused by work.

First step: examining the current situation

At this step, the status of the occupational diseases department and the environmental department were studied. The information in the occupational diseases section was incidents, accidents, permanent and temporary disabilities, days lost on the side, compensations paid, types of occupational diseases, and so on, which result in permanent or partial disabilities. Furthermore, the information of the environmental department includes the identification of the environmental situation such as waste and water, soil, and air pollutants. In this study, the information associated with occupational diseases is only associated with the official personnel of the Ministry of Oil, and this information was obtained from the HSE health and treatment units of the Tehran oil industry.

Second step: identifying health and environmental criteria

In the second stage, the main criteria and independent and dependent criteria were identified in the health and environmental sector. For this purpose, using the HSE rules and guidelines of the Ministry of Oil of Iran (NIOECC, 2019), the Environmental Protection Organization of Iran (IDOE, 2001), the Ministry of Health and national standards and OSHA, standards in Iran, and the US Environmental Protection Agency (USEPA, 2016), reviewing literatures^28,29, expert opinions and data access, indicators of the work environment and diseases caused by it were identified in order to determine the relationship between indicators and harmful factors of the work environment and diseases. The determined health indices were physical, chemical, biological, ergonomic, and psychological indices. Furthermore, for the environmental department, the factors that lead to water, soil, and air pollution during the process of disease and treatment were identified at the beginning and the consequences of each like the environmental consequences of medicine consumption and the resulting waste, consumption of radioactive substances, waste imaging special and infectious and their decontamination, hoteling of patients, disinfectants and detergents, consumption of disposable devices and medical equipment, conducting clinical tests, services and cleaning, water and electricity, and so on were examined.

Third step: determining independent and dependent sub-criteria

In the third step, criteria and sub-criteria were determined in both the health and environmental sectors. In this study, two main criteria, eight independent sub-criteria, and 22 dependent sub-criteria were determined in the occupational health packages section, and two main criteria, 17 independent sub-criteria, and 17 dependent sub-criteria were determined in the environmental section, which is presented in Tables 1 and 2.

Table 1 The structure of independent and dependent health criteria and sub-criteria.

Table 2 The structure of independent and dependent environmental criteria and sub-criteria.

Fourth step: screening criteria using the Delphi method

In the fourth step, the sub-criteria (dependent and independent) of the model, health and environmental work packages, were screened using the Delphi technique. Delphi may be characterized as a method for structuring a group communication process so that the process is effective in allowing a group of individuals, as a whole, to deal with a complex problem²⁶. In this study, a questionnaire was designed according to the determined sub-criteria to screen the sub-criteria. To assess the reliability of the initial questionnaire, it was distributed among 25 experts in the field of safety, health, and environment in various departments, of which 21 questionnaires were answered, and then the reliability of the related questions was measured using Cronbach's alpha test. In this study, Cronbach's alpha of the questionnaire was calculated as 0.75, that statistically acceptable. In the next step, the questionnaire was given to 21 experts consisting of experts in the field of safety, health, and environment, specialists, academics, beneficiaries, administrative and legal officials with bachelor's degrees and more, and doctors with at least five years of work experience and a survey was conducted, of which 19 questionnaires were returned. Table 3 shows the specifications of the experts.

Table 3 Profile of experts participating in the Delphi method.

The experts were asked to rank the significance of the sub-criteria based on their opinions from 1 to 5. In this study, the Delphi technique was continued in two rounds, and criteria with an arithmetic mean of less than 3 were removed. Independent and dependent criteria were determined in each section after summarizing the opinions of the experts.

The fifth step: weighting the criteria according to the ANP method

The analytic network process (ANP) method was used to weigh the criteria in this study. This method was first introduced by Saaty³⁰. ANP is a more general form of AHP proposed to overcome the shortcomings of the AHP method and to solve complex problems with non-hierarchical structure and feedback. In this method, a network of criteria and alternatives (elements) are grouped into clusters, and all the elements in the network can be connected. This method allows to examine of interdependencies and feedback between decision analysis parameters (criteria and/or alternatives) from decision networks instead of the hierarchical mode of the AHP method. ANP provides a more detailed model of the complex settings of the influence of elements in the network on other elements in the decision-making network, represented by a Supermatrix. The ANP model includes the following steps^31,32:

• First step: Identifying and determining the components and elements of the network and their relationships

• Second step: Shaping a matrix of pairwise comparisons of criteria and sub-criteria

• Third step: Determining the relative weight of decision-making elements using the special vector technique

• Fourth step: Shaping the weightless supermatrix

• Fifth step: Shaping the weighted supermatrix

• Sixth step: Shaping the final limited supermatrix and determining the weights of the criteria

• Seventh step: Compatibility rate calculations

In this study, the Likert scale was used on a scale of 1–9 where 1 shows the least effect and 9 is the highest effect to determine the significance coefficient of each of the sub-criteria according to the network analysis model. The final weight of the parameters is calculated using the ANP method with Super Decision software and the relationship between the clusters and the elements within the clusters is assessed using the matrix of pairwise comparisons. One must note that in all comparative matrices, the rate or Consistency Ratio (CR) was calculated to be less than 0.1, which is statistically acceptable.

Sixth step: compilation of the health and environmental parametric model

As the payment of expenses is done according to mathematical calculations and models designed by financial experts, the base of the work is the coefficients of the project failure structure framework and weighting factors. Hence, it is necessary to define the coefficients associated with the failure structure to determine the independent variable values (work packages). According to this, after identifying and separating the independent variables, the health and environmental parametric model was determined separately (Eqs. (1) and (2)) and finally, the final quantitative hybrid model was obtained from the sum of these two models (Eq. (3)).

$${\text{HTC}} = \sum\nolimits_{0}^{1} {A_{1} + A_{2} + A_{3} + .... + A_{n} }$$

(1)

$${\text{ETC}} = \sum\nolimits_{0}^{1} {B_{1} + B_{2} + B_{3} + .... + B_{n} }$$

(2)

$${\text{QEHC}} = {\text{HTC}} + {\text{ETC}}$$

(3)

Here, QEHC is the quantitative model of health and environmental costs, HTC is the total health cost, and ETC is the total environmental cost. Furthermore, the values of A and B are calculated from the sum of the coefficients of health and environmental parameters at the cost of each of the sub-criteria.

A = (Cost of the health index × weight coefficient of the health index).

B = (environmental index cost × environmental index weighting factor).

Seventh step: health and environmental cost estimation

The cost of health and environmental work packages was estimated then. In the dependent sub-criteria (internal costs), the costs that have a direct financial effect on the organization were taken into account. Calculating the costs of work packages includes bottom-up calculation methods and receiving the base price from the market, and annual inflation was also considered in the cost estimation. These costs in the health sector are the costs of pharmaceutical services (the pharmaceutical services of each patient were calculated separately), the costs of medical services (costs associated with the provision of medical and paramedical services), the costs of patient hoteling, and the cost of hospital missions. Furthermore, the costs of the environmental department include normal and special pharmaceutical waste costs, medical service waste costs, patient hoteling environmental costs, water consumption environmental costs, sewage treatment plant costs, hospital waste disposal costs and radioactive materials, costs of detergents and municipal waste, records of electricity consumption, water consumption records, gas consumption records, and other energy sources. The information associated with the necessary expenses were gained from the financial and accounting and clearance units, pharmaceutical services and medical equipment, and the finance and health support of the Tehran oil industry and the HSE units of the National Oil Company.

Model validation

Regression and correlation analysis was used in IBM SPSS (Version 25.0) to validate the computational model and evaluate the alignment of the real model with the proposed model. Regression is a statistical technique widely used by researchers in many areas to describe the nature of the relationship between variables. Regression models have been developed using many techniques like simple linear regression, multiple linear regression, non-linear regression, non-parametric regression, and multivariate regression.

Ethical approval

The present study was approved by the Ethics Committee of the Islamic Azad University, Research and Sciences branch (ethics code: 950316001). All methods were performed in accordance with the relevant guidelines and regulations. All the participants gave full "informed" consent to participate in the present study, and before the start of the study, the consent form to participate in the study was completed by all the participants. Participants were able to withdraw from the study at any stage if they were not satisfied.

Results

In this study, at first, the effective health and environmental factors resulting from work with the Delphi method were examined. The opinions of experts were used and finally, the average opinion of experts was used to confirm these factors to identify the most important factors. Tables 4 and 5 indicate the statistical description of the respondents' opinion about the criteria and sub-criteria of the work packages of the health and environment sector in the Delphi method.

Table 4 Statistical description of the respondents' ideas about the criteria and sub-criteria of the work packages of the health sector in the Delphi method.

Table 5 Statistical description of the respondents' ideas about the criteria and sub-criteria of the work packages of the environmental sector in the Delphi method.

The final table of relevant criteria and sub-criteria was presented in Table 6. Ultimately, the experts in the health sector agreed on eight sub-criteria, and in the environmental sector on eleven sub-criteria.

Table 6 The result of the Delphi method regarding the criteria and sub-criteria of the health and environment work packages.

The final weight of the parameters was calculated using the ANP method with Super Decision software and the relationship between the clusters and the elements within the clusters was determined as shown in Figs. 2 and 3.

Figure 2

ANP decision-making network model in the health sector.

Figure 3

ANP decision-making network model in the environmental sector.

The findings of the weighting of work package criteria in the health sector are given in Table 7. For the presented sub-criteria, medicine and medical equipment with a weight of 0.312 has the highest effect among the sub-criteria examined, followed by the sub-criterion of the service personnel of the support department with a weight of 0.247 and the working personnel of the treatment service with a weight of 0.234 have the second and third ranks, and the lowest effect on the cost is associated with the cost sub-criterion of hospital bed services with a coefficient of 0.0009 (Table 7).

Table 7 The coefficient of the significance of the criteria obtained from the ANP method in the health sector.

Weighting work package criteria results in the environmental sector are given in Table 8. For the presented sub-criteria, special and infectious waste with a weight of 0.085 has the highest effect among the sub-criteria examined, followed by the sub-criterion of waste from mercury consumption with a weight of 0.065 and pollutants from vehicle fuel and diesel generators with a weight of 0.085 has the highest effect with a weight of 0.055 the second and third ranks, and the least impact on the cost is associated with the electricity consumption sub-criterion with a coefficient of 0.015 (Table 8). Figure 4 shows the significance coefficient of the sub-criteria obtained from the ANP method in the health and environmental sectors.

Table 8 The significance coefficient of the criteria obtained from the ANP method in the environmental sector.

Figure 4

The coefficient of the significance of the sub-criteria obtained from the ANP method (A) health sector; (B) environmental department.

The findings of studying the costs of the health department of NSHT are in Table 9 and Fig. 5. The inflation rate of each year was included in the estimation of these costs. As is seen in Table 9, about 2773 billion rials of expenses are associated with health costs in NSHT, of which about 2544 billion rials are spent in the treatment department and about 228 billion rials in the support department. The highest costs in the medical sector are associated with the cost of medicine and medical equipment (about 1082 billion rials) and the cost-of-service personnel (about 617 billion rials) and the lowest amount is associated with the cost of technical rights of the hospital (about 26 billion rials). Furthermore, the highest costs in the support sector are associated with the cost of personnel working in the support sector (about 227 billion rials) and the lowest amount is associated with the cost of sick leave (about 311 million rials).

Table 9 Health expenses in NSHT.

Figure 5

Chart of health costs in Naft Subspecialty Hospital in Tehran.

The costs of the environmental department of NSHT are given in Tables 10, 11 and Fig. 6. The inflation rate of each year was included in the estimation of these costs. According to Table 11, about 42 billion and 800 million rials of the costs are associated with environmental costs in NSHT, of which about 695 million rials are in the treatment department and about 42 billion rials are spent in the support department. The highest costs in the medical sector are associated with the cost of disposal of waste caused by chemicals and medicines (about 465 million rials) and the lowest amount is associated with the cost of disposal of waste caused by radioactive materials (87,624 rials). In this study, given the lack of production rate of imaging waste disposal, its cost was not considered. Furthermore, the highest costs in the support sector are associated with the cost of treated wastewater in the sewage treatment plant (about 29 billion rials) and the lowest amount is associated with the cost of mercury waste disposal (about 3 million 600 thousand rials).

Table 10 Environmental parameters according to the value and production interval in NSHT.

Table 11 Environmental costs in NSHT.

Figure 6

Chart of environmental costs in Naft Subspecialty Hospital in Tehran.

After calculating the costs and weighting coefficients of the criteria, the hybrid model of health and environmental economic evaluation was gotten from the sum of the coefficients of the health and environmental sub-criteria in the cost of each of the sub-criteria, which is as follows.

Hygiene Total Cost (HTC) = (0. 232* S.f.) + (0.055*TA.f.) + (0.0009 *H.f.) + (0.089 *PS.f.) + (0.311 * DE.f.) + (0.236 *AS.f.) + (0.056 * T.f.) + (0.018* SD.f.) Environmetal Total Cost (ETC) = (0.038 *DW.c) + (0.037* RW.c) + (0.045* IW.c) + (0.085 *SIW.c) + (0.021 *NW.c) + (0.029* ReW.c) + (0.065 * MW.c) + (0.015 * EW.c) + (0.026* GW.c) + (0.022* WW.c) + (0.055 *VF.c)

$${\text{QEHC}} = {\text{HTC}} + {\text{ ETC}} = {573193329}0{9}0 + {938589496} = {574131918586}$$

Model validation

The findings indicated a significant relationship between the expert weights for the importance of variables in the evaluation of health costs and the actual data obtained from the weight of the costs of each variable (Table 12). This indicates that both models are aligned and the proposed model has an acceptable correlation with the the real data (R2: 0.519; CC: 0.721) (Table 15). Health model parameters and statistics are shown in Table 13.

Table 12 Regression analysis of variance between the expert coefficients of the health sector with the coefficients of the real model.

Table 13 Health Model parameters.

In environmental variables, a significant correlation was seen between expert coefficients and the real model (Table 14). The regression analysis of variance between these two variables was significant too (R²: 0.750; CC: 0.866) (Table 15).

Table 14 Regression analysis of variance between expert coefficients of the environmental department with real model coefficients.

Table15 The goodness of fit statistics for two models.

Environmental model parameters and statistics are shown in Table 16.

Table 16 Environmental Model parameters (weight).

Discussion

The purpose of this study was to develop an economic evaluation model of the environmental and health costs of occupational diseases by combination of Delphi study and ANP approach. So far, many studies have been conducted using analytic network process (ANP), analytic hierarchy process (AHP), fuzzy analytic hierarchy process (FAHP), and etc., in various industries to assess safety risk^33,34. Baratchi et al.²² examined health risks based on the MCDM method. In this study, all the hazards of various units of a medical center were selected with the help of hazard identification checklists and were ranked using the ANP method. Regarding the economic evaluation of accidents caused by work, different studies have been carried out at the world level. Tompa et al.¹⁶ examined the economic burden of occupational injuries and illnesses in five European Union countries (Poland, Italy, Germany, Finland, and the Netherlands). Hoque et al.¹ examined the effects of industrial processes on social, environmental, and public health degradation in Bangladesh.

This study identified 19 criteria in the health and environmental sector, and with the help of experts and the Delphi method, a consensus was reached on eight sub-criteria in the health sector and eleven sub-criteria in the environmental sector. Thus, 5 and 3 sub-criteria were selected in the medical and support criteria in the health sector, and 4 and 7 sub-criteria in the medical and support criteria in the environmental sector, respectively. The estimation of the total environmental and health costs shows that 98.5% of the total costs are associated with medical costs and 1.5% with environmental costs. Overall, in the health sector, of 2,773 billion rials, the most expenses are associated with the cost of medicine and medical equipment and the cost of personnel with 39.05 and 22.27 percentages, and 38.7% are for the other expenses in this sector of the total expenses. Furthermore, ANP method results indicated that according to the experts, the medicine and medical equipment cost was considered the first and most important factor affecting the increase in the Medical costs of NSHT with a weight of 0.312 and the support service personnel with a weight of 0.247 and the cost of treatment service personnel with a weight of 0.234 were ranked second and third. Furthermore, the cost of hospital bed services (0.0009) ranked last.

According to the cost analysis, a total of 42 billion and 800 million rials were created in the environmental sector, the highest costs are associated with the cost of wastewater treatment in the treatment plant and the cost of electricity consumption with 67.5 and 24.17%, respectively, which weight 0.022 and 0.015 respectively in the relative weight of the total costs. Furthermore, other costs in this sector account for only 8.3% of the total costs. Additionally, the results of the ANP method showed that according to the experts, the special and infectious waste cost factor with a weight of 0.085 was considered the first and most important factor affecting the increase in the environmental costs of NSHT, and the waste cost factors caused by the consumption of mercury with a weight 0.065 and the cost of pollutants caused by vehicle fuel and diesel generators with a weight of 0.055 ranked second and third. Additionally, electricity consumption cost (0.015) ranked last according to the experts. Moreover, the results of the parametric model revealed that the total health and environmental costs are 574,131,918,586 rials, of which 99.84% are associated with health costs and 0.16% with environmental costs.

As the findings revealed, 61.3% of the costs are only associated with the medicine and medical equipment sectors and the cost of personnel working in the health sector, and 91.7% of the costs of the environmental sector are associated with wastewater treatment and the cost of electricity consumption. Thus, it is necessary to take managerial measures in this direction to increase productivity and reduce economic costs. In working environments where the lack of budget could affect the performance of organizations, organizations must implement cost control strategies and reduce these costs not only in the short term but also in the long term.

Olukoga³⁵ conducted a study in South Africa regarding the estimation of the cost of hospitalization days in South African public hospitals revealed that personnel costs are the most important cost components and between 73 and 82% of the unit costs. It was determined that it is in line with the findings of the present study. Hadian et al.³⁶ stated that among the three major operational departments in Fatemieh Semnan Hospital, personnel costs and the cost of construction and permanent buildings accounted for the largest amount of costs in most of the operational departments. They have considered the need to pay special attention to the category of human resources management and maintenance management and proper use of existing buildings and spaces as one of the basic solutions for reducing costs. In another study, Nakhaei and Motahari³⁷ suggested that package costs of improving hotel quality with an average weight of 0.089 were considered the first and most important factor affecting the increase of hospital costs, and not using technology in providing services with 0.078 and the cost of medicine and consumables with 0.065 weights ranked second and third. After that, the bed occupancy cost factor (0.035) ranked last according to the subjects examined.

However, one must state that the managerial performance of managers in controlling environmental issues could be much higher. They could reduce the economic cost of this sector by taking effective measures to reduce pollution, increase the efficiency of using water and energy resources, and waste management. Curkovic and Sroufe³⁸ stated the implementation of environmental management systems usually enhances efficiency and cost, higher credibility of the organization, and the involvement of personnel and managers at its highest level. Amores-Salvado et al.³⁹ considered the implementation of environmental solutions as important in achieving positive economic returns.

Henri et al.¹⁸ have stated the significance of identifying environmental costs not only at the operational level but also at the strategic level. Mazaheri et al.⁴⁰ stated that using environmental evaluation models along with management support in Trita Hospital of Tehran, besides bettering the environment and improving public health also reduces economic costs. Furthermore, implementing environmental measures reduces ecological effects⁴¹ and environmental costs, and thus enhances the organization financial performance⁴².

Strengths and limitations of the study

As strength point, it should be noted that The present study was conducted for the first time with the aim of economic evaluation in the field of health and environment in a work environment using real data and a hybrid approach. In addition, The results of the present study can create a new perspective in the field of implementing control measures using the optimal point of cost–benefit parameters.

This model also emphasizes the importance of prevention and mitigation strategies in reducing the economic and environmental costs of occupational diseases in the oil industry. By incorporating the costs associated with these strategies into economic evaluations, policymakers and industry leaders can make more informed decisions about how to allocate resources and prioritize interventions. Another strength of this study is apply the mathematical method that increase the reliability of the results and reducing uncertainties.

Overall, this hybrid model highlights the need for a more comprehensive approach to evaluating the economic and environmental costs of occupational diseases in the oil industry. By considering both direct and indirect costs and incorporating prevention and mitigation strategies into economic evaluations, policymakers and industry leaders can better understand the true impact of these diseases and make more informed decisions about how to address them.

Among the limitations of the present study, we can point out the impossibility of examining other economic variables and risk factors affecting the causal relationships between benefits and costs in the economic evaluation of occupational health and environment.

Another obstacle in this study is the lack of other modeling and mathematical methods. Beside, the lack of an intervention study due to time and economic limitations is another obstacle of the present study.

Also, considering that the current model has been developed for a medical setting,it is suggested that researchers develop similar models in other industries in the future and report the effectiveness of using the models. Furthermore, the method suggested in this paper could be implemented in other decision-making cases. In the future, this method can be used for other multi-criteria decision-making problems, and research can be done in fuzzy mode or other mathematical methods to increase the credibility of the results. Additionally, it is recommended that external and social costs be taken into account in the estimation of health-environmental costs in future studies.

Conclusion

This study tried to present a quantitative model of the health and environmental costs of NSHT. The study findings indicated that 61.3% of the costs of the health sector are associated with the two sectors of medicine and medical equipment and the cost-of-service personnel, and 91.7% of the costs of the environmental sector are associated with wastewater treatment and the cost of electricity consumption. The results of the present study can create a novel scientific perspective in the field of implementing control measures using the optimal point of cost–benefit parameters. Implemention of this integrated model can be a practical and effective step in allocating resources and prioritize interventions.