Constructing Scenarios for the Iranian Health System Using Dynamic System Modeling

doi:10.21203/rs.3.rs-4004750/v1

Download PDF

Research Article

Constructing Scenarios for the Iranian Health System Using Dynamic System Modeling

https://doi.org/10.21203/rs.3.rs-4004750/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Background

Health systems (HSs) are recognized as complex adaptive systems, characterized by unforeseen interactions among their components. The prediction of such behaviors necessitates a systemic-perspective and a comprehensive identification of the dimensions and their interrelationships. In this study, dynamic system modeling was utilized to scrutinize the trends of critical components of Iran’s HS.

Methods

This study adopted a systems thinking and leveraging a system dynamics approach. The HS of Iran was modeled based on the balanced scorecard (BSC) framework, encompassing four dimensions: population health, service delivery, financing, and development. Subsequently, the parameters influencing cost reduction in the HS were modified to test policy implications over the forthcoming decade (2021–2031) under three scenarios: The data were derived from official Iranian statistics and information sources, as well as pertinent studies in the field. The modeling was executed using Vensim DSS6.4E software.

Results

By increasing the population, which is projected to reach 90 million by 2031, 35% of this population will be exposed to hazardous factors, putting approximately 32 million individuals at risk. Consequently, it is anticipated that 9 million people will require inpatient services, 43 million will necessitate outpatient services, and 52 million will need diagnostic and pharmaceutical services. In terms of human resources, the demand for physicians within the system by 2031 is projected to be 135,500, indicating a potential shortage of 20,850 physcians over the next decade. The current costs and expenses of the system are estimated at 17,000 trillion rials. Given the projected resource supply in the system in 2031 (7,807 trillion rials), the expenses are expected to exceed the supply, leading to a budget deficit.

Conclusions

As a result, the demand for medical services is expected to rise. To effectively address the escalating demands of society and improve the current situation, two primary steps must be undertaken. Firstly, strategic planning and interventions need to be enhanced to prevent and reduce the exposure of the population to risk factors. Secondly, infrastructural resources, including manpower, beds, and medical equipment, must be expanded. The model developed facilitates the consideration of changes in key-parameters and the evaluation of their impact on HS.

Iran

Complex Systems

Health System

Systems Thinking

Dynamic System Modeling

HSs display significant variations in performance. Notably, even countries with similar levels of income, education, and health expenditures exhibit differences in their ability to achieve health objectives (1). The variation in performance can be attributed to how the HS organizes four critical functions: stewardship (a concept more comprehensive than legislation), financing (encompassing revenue collection, resource pooling, and purchasing), service delivery (pertaining to both personal and non-personal health services) and resource production (including personnel, facilities, and knowledge) (1, 2). An examination of these functions and their integration not only facilitates an understanding of the determinants of HS performance but also allows for the contemplation of major policy challenges (1).

HSs serve as paradigmatic instances of human organizations, integrating diverse professional and disciplinary characteristics within a crucial functional environment. Communication failures and flawed processes within HSs have a profound societal impact, both in financial and human terms (3). Essentially, HSs are characterized as complex adaptive systems, defined as systems where numerous components interact unpredictably, often yielding unf oreseen results. Such complex adaptive systems frequently exhibit resistance to change, with interventions tending to be fragmented and isolated, thereby diminishing the likelihood of large-scale improvements (2).

Over the past two decades, systematic attention to the complex adaptive nature of HSs has gained prominence among global health stakeholders. This shift aims to better anticipate the unforeseen consequences arising from the implementation of existing and novel policies (4). Systems thinking encompasses the composition of an entire system and the interrelationships between its components. The context, conditions, and environment of a system play a pivotal role in systems thinking. This systems thinking paradigm aligns well with the notion that effective health promotion must accommodate the complexity of health and simultaneously address numerous actors and factors at different levels (5).

Simultaneously, system dynamics modeling has demonstrated substantial value across various contexts, aiding decision-makers in understanding and predicting the dynamic behavior of complex systems, thereby supporting the formulation of effective policy actions (6). This is predicated on the crucial understanding that all elements are interconnected (7). System dynamics modeling involves the creation of causal diagrams and policy-oriented computer simulation models, each tailored to its specific problem setting. This approach was pioneered by Jay W. Forrester in the mid-1950s, with its first comprehensive description found in his book, ‘Industrial Dynamics’. Subsequent works introduced further principles. The International Society for System Dynamics was established in 1983, and a dedicated subgroup focusing on health-related matters was instituted in 2003 (8).

Numerous studies have been conducted across various fields and aspects of the health sector, employing the system dynamics approach. This underscores the significance and applicability of this systemic approach. These studies include Mehrjerdi’s 2012 investigation, which aimed to explore the interconnections among human weight, dietary habits, physical activity, body fat, medication usage, and health issues. It also identified their direct and indirect impacts on healthcare costs through a system dynamics approach (9). In 2020, a study was conducted on the development and assessment of financial strategy models for the Indonesian health insurance system using a system dynamics approach (10). Another study applied system dynamics to model the interplay between production and pricing factors in the pharmaceutical industry. The objective was to forecast drug prices and production volumes, considering the manufacturer’s profit, raw material costs, and quality (11). A dynamic financing model was constructed, validated, and simulated, and an alternative budgeting model was proposed in Thailand (12). Baibordy et al.'s study aimed at modeling and presenting a human resource productivity model using a system dynamics approach in the health sector of East Azerbaijan province in Iran (13).

This study aims to identify the effective components within the HS and their interrelationships. Subsequently, stock and flow diagram for each dimension of the system are designed using the BSC framework. Based on the available information, the trends of each component and their impacts are examined over different years. Finally, through scenario writing, depictions of the future of the HS under various scenarios are provided.

1. Study Design and Participants

This study utilized a systems thinking and modeling method grounded in the system dynamics approach. System dynamics, indeed, is a mathematical modeling method that assesses the behaviors of complex systems over time, leveraging tools from systems thinking. Furthermore, system dynamics models employ differential equations to handle the modeling of variables that change over a specified time period, feedback mechanisms, interactions, various delays, and also address issues related to simultaneity or reciprocal causation of system behaviors (14).

In this context, this study was conducted in five primary stages, drawing from the system thinking and modeling method proposed by Maani (15). These stages include: problem structuring; causal loop modeling; dynamic modeling; model formulation and scenario development; and implementation and organizational learning.

This report constitutes the third phase of a research project titled “Developing HS Scenarios for Iran using a System Thinking Approach”. In the first phase, key variables within the HS were identified through a scoping review and review of upstream documents. These identified variables were then categorized based on the BSC framework (16). In the second phase, these variables were presented in the form of a questionnaire to academic experts and professionals familiar with the HS’s issues and dimensions. This was done to determine the variables’ importance and uncertainty based on the existing context. To complete the cross-impact analysis (CIA) matrix in the MicMac software, the most significant variables and uncertainties of Iran’s HS, along with their mutual relationships, were extracted (17). Finally, the researchers decided to model the HS’s dynamics based on the identified causal relationships between the variables, aiming to depict the current and ideal state of the HS.

2. Model Structure

The study “Identification of Drivers, Uncertainties, and Future Scenarios of Iran’s HS” (17) served as the foundation for the stock and flow diagrams and the system dynamics model. In the stock and flow diagram, the HS was conceptualized based on the BSC framework (18), encompassing four dimensions: population health, service delivery, financing, and growth and development/infrastructures (including beds, medical equipment, and manpower). These dimensions encapsulate factors and relationships that can facilitate the delivery of efficient and effective health services, tailored to societal needs and demands.

2.1. Dimensions of Population and Population Health

The common population model is fundamentally employed in terms of population and population health. The population section comprises the basic components driving population change, namely birth and death rates. Both births and deaths are presumed to influence the current state of the population. A high number of births lead to population growth, which subsequently results in more births. This feedback loop is referred to as an amplifier in system dynamics. Conversely, an increase in population leads to more deaths, and a high death rate results in a decrease in a country's total population. This inverse relationship between population and mortality is known as the implicit goal or balanced feedback loops (Figure 1).

In this study, the birth rate was calculated as 0.013, and the death rate as 0.0064 percent in 2021. Based on these rates, the current population was projected for the next 10 years. It is important to note that the relevant demographic information was sourced from the Iranian Statistics Center (Appendix No. 1).

In the subsequent step, the current population was categorized into two groups: a population at risk and a population not at risk. These categories were determined by multiplying the current population by the degree of exposure/non-exposure to risk factors..

Figure 1. Demographic sub-model in Iranian HS modeling

Risk factors are divided into behavioral risk factors (such as nutritional status, physical activity level, addiction and smoking, depression and psychosocial stress, violence and sexual disorders) and biological risk factors (chronic disorders such as high cholesterol, high blood pressure, diabetes and obesity). Other risk factors are considered in three categories: factors related to people’s lifestyle in terms of cultural, economic and social aspects; natural and environmental hazards; and the efficiency and effectiveness of the HS (Figure 2). According to the included studies, the influence coefficients of each of the main components on the occurrence of risk factors were obtained first. Then, the influence coefficients of the sub-components on the corresponding component were obtained. Finally, by multiplying all the available coefficients for each sub-component, its influence on the occurrence of risk factors was extracted (Appendix No. 2).

Figure 2. Population health sub-model in Iranian HS modeling

2.2. Dimensions of Service Delivery

This dimension addresses the population’s demand for the HS. It is postulated that both the at-risk population and the non-at-risk population will contract disease and will seek both outpatient and inpatient services from the HS. In this study, the outpatient rate in the healthy population exposed to risk is 0.33, and in the healthy population without exposure to risk factors, it is 0.06. The hospitalization rate in the healthy population exposed to risk is 0.1, and in the healthy population without exposure, it is assumed to be 0.01 (Appendix Number 3). The adjustment of the current outpatients and inpatients in this dimension will be based on the deaths that occurred at a fixed rate and specific to each case (Figure 3).

Figure 3. Service delivery sub-model in the modeling of Iran's HS

2.3. Growth and Development /Infrastructures Dimension

2.3.1. Beds and Medical Equipment

Bed capacity is crucial for accommodating patients who require hospitalization as prescribed by their physicians. The annual rate of bed development and its attrition rate will regulate the number of beds in the system. Additional funding is required from public healthcare providers for the procurement and expansion of beds.

Medical equipment, a significant proportion of which is imported, is crucial for providing diagnostic services to both inpatients and outpatients. The pace of equipment development is largely contingent upon the budget allocated and the rate of inflation. The quantity of existing equipment within the HS is adjusted in accordance with the rate of attrition. This study discusses the most important medical equipment in use, including MRI machines, linear accelerators, CT scanners, angiography units, Gamma cameras, and others.

It should be noted that the index of the quantity of active medical beds/equipment within the HS is calculated using the occupancy rate and their current count. Considering the mentioned index facilitate planning and decision-making regarding service delivery, budgeting, and outsourcing of services to the private sector (as depicted in Figure 4).

In this dimension, the infrastructure costs of the health sector are calculated as a component of the total costs. This calculation is a composite of the expenditures on hospital beds, medical equipment, and the fundamental infrastructure costs in this sector for the initial year of calculation.

The coefficients considered in this dimension are derived from the country’s statistical database of 2021. The estimation of certain variables is based on the study conducted by Aghajani et al. in 2016. The annual growth rate of the bed is 0.001, the bed occupancy rate is 0.9, the growth rate of medical equipment is 0.0667, and the occupancy rate of medical equipment is assumed to be 0.6 (Appendix No. 4).

Figure 4. Sub-model of bed and medical equipment infrastructures in the modeling of Iran's HS

2.3.2. Manpower

In general, health production capital is defined as the physical and human capital invested for health status. This includes physicians, bed facilities, medical equipment, hospital buildings, and many other factors. For the sake of brevity, this study discusses the structure of the physicians’ education system and the current demand for physicians in the HS.

On the right side of the model, it is initially assumed that students will be admitted to the general professional doctorate level at a fixed rate, based on societal demand and existing educational capacities. A fee will be incurred for their education. A portion of the expenses spent on health education and research is allocated to the training of students in other medical fields.

Ultimately, some general medical students either withdraw and leave the educational system, work in the HS, or continue their education and study in one of the specialized fields. Similarly, students in specialized fields either leave the education system or engage in activities and service provision in the HS. In fact, the number of current physicians in the HS, which is the sum of general and specialist physicians, will be adjusted by their exit and retirement rates.

In the left side of the model, the working capacity of physicians is determined by taking into account the standard visit time and the time spent in outpatient and inpatient services. The demand for, and need of, physicians in the health sector is then ascertained based on the number of outpatients and inpatients in the system. In this dimension, a discrepancy has been identified between the supply of physicians in the health sector and their demand. This discrepancy has been examined over different years to identify periods of deficit or surplus (Figure 5).

In this dimension, the costs associated with medical education and health research are also considered. These costs are a combination of expenditures for general practitioners, health specialists, graduates of other medical fields, and the initial cost of education in the base year of calculation.

The coefficients used in this dimension have been extracted from news sites (for variables such as the number of candidates for the national entrance exam, the number of applicants for medical sciences, the capacity to accept fields, etc.), the statistics site of the Medical System Organization, and the 2021 statistical database of the country.

In this dimension, the current number of working physicians is 101,847; their retirement rate is 0.015; the number of employed nurses is 1.5 times the number of physicians; the number of dentists is 0.28 per physicians; and the number of pharmacists is considered equal to 0.19 times the number of physicians (Appendix No. 5).

Figure 5. Manpower sub-model in the modeling of Iran's HS

2.4. Financing Dimension

In this dimension, initially, on the right side of the model, the country’s gross domestic product (GDP) is discussed. A portion of it is allocated to healthcare costs, taking into account the annual inflation and exchange rate. On the left side of the model, in accordance with the financing process, the number of individuals requiring services, the number of inpatient and outpatient visits, the cost burden created by patients in outpatient and inpatient departments (average cost per visit), and the cost resulting from the provision of paraclinical and pharmaceutical services are considered. The sum of these costs is referred to as the medical costs incurred in the HS. Additionally, it is necessary to consider all the following costs: a) hygiene sector and the prevention and primary healthcare system; b) infrastructure development of the health service delivery system, including investment in beds and medical equipment, as well as manpower training; and c) overhead and support costs. Ultimately, the sum of these costs will form the current costs of the HS.

It should be noted that each year, the inflation rate in the health sector, which is essentially a percentage of the current cost, is added to the current price and determined as the overall cost of health. Ultimately, a discrepancy has been identified between the two aspects of the need for financial resources and the provision of the required financial resources. This discrepancy has been examined over different years to identify periods of deficit or surplus (Figure 6).

The figures included in this dimension have been extracted based on the statistical database of the Social Security and Health Insurance Organizations of Iran, the tariff for diagnostic and therapeutic services, the Statistical Center of Iran, the Central Bank, and the estimate based on the national health accounts in 2021 (Appendix No. 6)

Figure 6. Financing sub-model in the modeling of Iran's HS

3. Policy Experimentation

System dynamics simulations were conducted under three scenarios: desirable, intermediate and undesirable This study considers the change in health sector costs as the objective of these scenarios. Influential parameters such as the physician-to-population ratio, bed-to-population ratio, medical equipment-to-population ratio, health sector inflation rate, exchange rate, health’s share in GDP, GDP growth rate, management and support costs rate in the HS, level of exposure to risk factors, and population change factor were altered to test policies and demonstrate potential effects over the next decade (2021-2031) under these scenarios (refer to Table No. 1).

This study discusses the results of various simulations through desirable and undesirable interventions that determine the percentage increase or decrease compared to the base value. Changes in parameters were based on existing studies in the field or determined during the focus group discussion (FGD).

Table No. 1 - Potential Scenarios in Iran’s HS

Regarding the variable "exposure to risk factors," the current situation in 2021 was reported as 0.35. Consequently, expert opinions on the desirable and undesirable scenarios were precisely set at 0.2 and 0.45, respectively. To attain these levels, it is imperative to implement meticulous modifications in the sub-components of the variable, either through augmentation or reduction. The areas most likely to undergo transformation in the next decade were discerned and systematically incorporated into the targeting table, complete with precise change coefficients. This compilation epitomizes a sophisticated policy package (refer to Table 2).

Table No. 2- Change of parameters associated with health-related risk factors in each scenario, in order of the possibility of greater variability in the next ten years

1. Population and Population Health

In the initial model, developed based on past trends and information available in 2021, it was projected that the population would reach 90 million by 2031. Based on Focus Group Discussions (FGDs), the objective was set that under the desirable scenario, the population would increase to 110 million over the next decade. This would require a change in the birth rate from 0.013 to 0.0356. Concurrently, by reducing the risk rate from 0.35 to 0.2, the number of individuals at risk would decrease from 32 million in the base model to 22 million in the desirable scenario. Furthermore, the number of individuals not exposed to risk factors would increase from 59 million in the base model to 88 million in the desired scenario.

Diagram No. 1- Estimation of Iran's population and the population exposed to risk factors until 2031 in the initial model and various scenarios examined

In the base model for 2021, the exposure to risk factors is quantified as 0.35. Expert opinion suggests a value of 0.2 for the desired scenario and 0.45 for an undesired one. To attain these values, modifications have been implemented in the risk sub-components. These alterations predominantly transpire in areas anticipated to undergo change in the forthcoming decade, such as nutritional status, level of physical activity, obesity status, and shifts in biological factors (refer to Table No. 2). It is imperative to note that the values associated with risk variables are assumed to remain constant over a span of 10 years, as alterations in these variables necessitate approximately a decade to manifest results.

2. Service delivery

In accordance with the desired scenario, which entails a 20% reduction in exposure to risk factors, there is a comparative decrease in service utilization when juxtaposed with the undesired scenario. Specifically, the number of outpatients is projected to decline from 46 million to 43 million. Similarly, the count of hospitalized patients is expected to decrease from 10 million to 8 million. Furthermore, the number of patients availing pharmaceutical and diagnostic services is anticipated to drop from 56 million to 51 million.

Diagram No. 2- Estimation of recipients of outpatient, inpatient, diagnostic and pharmaceutical services in the next ten years (2021-2031) in the basic model and different scenarios of interest

3. Beds and Medical Equipment

Given the projected population increase in the desired scenario, it becomes imperative to augment the number of beds per capita. Consequently, the globally optimal number (3/1 per 1000 population) was adopted in the desirable scenario, leading to an increase in the number of beds from 214 thousand in the base model to 341 thousand in the the desirable scenario by 2031.

In terms of medical equipment, the optimal rate per capita was estimated at 46.72 per million populations in the model. As a result, the quantity of capital medical equipment escalated from 3224 in the base model to 5138 in the desirable scenario by 2031. The distribution of equipment is as follows: PT-scan=28.26, CT-scan=1999, Angiography=719.3, Peripheral angio=149, CT-Angio=190.1, MRI=950.5, Linear accelerator=507.1, and Gamma camera=570.3.

Diagram No. 3- Estimate of the number of beds and capital medical equipment needed in the HS in the next ten years based on the basic model and different scenarios examined

4. Manpower

In the desired scenario, efforts were made to increase the number of general and specialized medical students, thereby enhancing their participation rate in the HS. This led to an increase in the number of physicians, and subsequently, the number of nurses, dentists, and pharmacists employed in the HS. These changes were implemented to the extent that the per capita number of physicians in the population reached its optimal level, i.e., 20 per 10,000 individuals. The specific increases are as follows: the number of physicians rose from 114,600 in the base model to 220,800 in the desirable scenario; the number of nurses increased from 171,900 in the base model to 331,200 in desirable scenario; the number of dentists grew from 32,090 in the base model to 61,830 in desirable scenario; and the number of pharmacists escalated from 21,770 in the base model to 41,950 in desirable scenario.

Consequently, in another section of the model, alongside population growth and the increasing number of practicing physicians, the demand for physicians in both outpatient and inpatient departments has increased. As a result, the total demand for physicians surged from 135,500 in the baseline model to 146,900 in desirable scenario. The existing gap between the supply and demand for physicians, derived from the formula ‘total demand for physicians - number of practicing physicians’, indicates that in the baseline model and the undesired scenario, we will encounter a shortage of physicians in the healthcare sector over the next decade, despite an excess demand for physicians. In the intermediate and desired scenarios, efforts have been made to bridge this gap. Over the next decade, we anticipate that the number of available physicians will meet the population’s demand. The surplus supply of physicians in these two scenarios could potentially lead to a decrease in workload and an enhancement in the quality of services provided in the future.

Diagram No. 4 - Estimate of the number of physicians working and required in the HS in the next ten years (2031-2021) in the basic model and the various scenarios examined and the gap between them

Table No. 3- Estimated demand and supply of physicians working in the system during different years

5. Health Financing

The primary objective of this study was to devise a scenario aimed at minimizing costs across various parts of the system, with a particular focus on service delivery, while ensuring the preservation of necessary efficiency and effectiveness. Naturally, due to population growth and consequently, an increased demand for the HS, there is a need for enhanced investment in system infrastructure, such as the expansion and development of beds and medical equipment. As a result, it is observed that the total cost of the health sector, which essentially comprises anticipated costs and expenses, has escalated from 18 thousand trillion Rials in the undesirable scenario to 21,000 trillion Rials in the desirable scenario. However, it is worth noting that the per capita expenditure within the service delivery system has decreased from 197 million Rials to 192 million Rials.

As indicated in Table 4, the medical expenses range from 3436 trillion Rials in the undesired scenario to 2927 trillion Rials in the desired scenario. The costs associated with the hygiene and prevention sector decrease from 275 trillion Rials in the undesired scenario to 234 trillion Rials in the desired scenario. Similarly, overhead and support costs of the HS decline from 2220 trillion Rials in the undesired scenario to 1564 trillion Rials in the desired scenario.

Given the objective to increase the number of beds, medical equipment, and physicians in the HS, the infrastructural costs have seen an increase. Specifically, the cost of constructing a bed has risen from 5881 trillion Rials in the undesired scenario to 10,000 trillion Rials in the desired scenario. The cost of medical equipment has escalated from 788 trillion Rials in the undesired scenario to 1497 trillion Rials in the desired scenario. Additionally, the cost of education has increased from 489 trillion Rials in the undesired scenario to 512 trillion Rials in the desired scenario.

Taking into account the highest growth rate of Iran's GDP in the last 15 years in the desired scenario (0.088), the GDP in 2031 has risen from 494 billion dollars in the base model to 830 billion dollars in the desired scenario. Consequently, the per capita GDP has expanded from $5,484 to $7,548.

As for the Total Health Expenditure (THE) variable, which is essentially an estimate of the resources required to cover health costs and is derived from the combination of the GDP and the share of the health sector in the GDP, it has increased from 7807 trillion Rials in the base model to 16 thousand trillion Rials in the desired scenario. Correspondingly, the per capita THE has also risen from 87 million Rials to 148 million Rials.

Diagram No. 5- Estimation of expenses and resources needed and per capita in the health sector in the next ten years in the basic model and different scenarios of interest

It is important to note that the gap in health sector costs, which is calculated by subtracting the total cost from the Total Health Expenditure (THE), has changed from -9303 trillion Rials in the base model to -4847 trillion Rials in the desired scenario in 2031. This number was as high as 12,000 trillion Rials in the undesired scenario, indicating that the health sector's costs and expenses exceeded the resources supplied, resulting in a budget deficit. Efforts were made in the desired scenario to reduce this difference as much as possible.

The aim is that, with the continuation of the desired scenario over many years, it is possible to generate a surplus of financial resources in the system. These resources can then be utilized for initiatives such as the Social Determinants of Health (SDH) approach and reducing exposure to risk factors. For instance, lifestyle modifications and changes in the population's dietary habits, family health, investment in sedentary issues, the construction of screening centers related to chronic diseases, etc., can all be planned. These initiatives, in turn, can lead to a reduction in the total cost, creating a cyclical system of cost management.

Diagram No. 6- Estimation of the gap between the required financial resources and its supply in Iran's HS in the next ten years in the basic model and different scenarios of interest

Table No. 4- Estimation of the financial expenses in the HS in different scenarios examined during the years (2021-2031)

Table No. 5- Estimation of the supply of financial resources in the HS in different scenarios examined during the years (2021-2031)

In this study, the fundamental model of Iran’s HS was initially estimated based on information available in the year 2021 and structured according to the BSC framework. The graphical results indicated that the population of Iran is projected to reach 90 million people by 2031, demonstrating a minimal rate of population growth.

In corroboration of the findings on Iran's demographic situation, a 2023 report from the Ministry of Foreign Affairs and Trade of Iran indicated that Iran currently has one of the youngest societies globally, with 60% of its population being 30 years old or younger. Conversely, only 8% of the population is over 65 years old. The increased utilization of modern contraceptive methods and the availability of government family planning services have significantly reduced the total fertility rate in Iran. Consequently, the family size is currently below the replacement rate, and it is projected that Iran's population will decrease by 2050 (69).

Given the current situation, the level of exposure to risk factors was 0.35%, translating to approximately 32 million people of the population being at risk. Furthermore, 52 million people of the population have received health services as outpatients and inpatients.

Mirzaei et al. (2020) reported that 74.6% of deaths were attributed to non-communicable diseases, indicating an increasing trend in the risk factors associated with these diseases in Iran. Generally, non-communicable diseases and injuries resulting from road traffic accidents account for a significant portion of the years lived with disability in Iran, compared to countries in the Middle East and North Africa region (MENA) and globally (70). Therefore, it is imperative to develop suitable action plans to mitigate the burden of risk factors, including unhealthy diets (particularly high salt consumption), insufficient physical activity, smoking, and blood lipid disorders. Effective management of these risk factors through multi-level prevention strategies can successfully avert the incidence and burden of non-communicable diseases in Iran (29).

In the field of infrastructure, it is crucial for the HS to respond swiftly and effectively to the population's needs. Regarding inpatient beds, the global average stands at 3.1, while the ideal ratio in Iran is 2.5 beds per thousand populations. However, the current state of the system offers 2.37 beds, slightly below the ideal ratio. Similarly, the optimal number of medical equipment is considered to be 46.7 units per one million populations. In contrast, the current state of the system has 35.8 units, indicating a shortfall in the provision of medical equipment.

In this regard, a study in 2017 stated that hospital beds are considered the most important criteria for calculating other required conditions, including physicians, nurses, and equipment; therefore, equality in the distribution of beds can implicitly equalize the distribution of other service delivery factors. Therefore, policymakers are expected to monitor the distribution of hospital beds frequently, and it is suggested that health policymakers and other key decision-makers of the Ministry of Health, Treatment and Medical Education support medical graduates, finance, establish regulations, and provide educational and professional support (71).

In the field of manpower, the optimal ratio of medical personnel, including physicians and nurses, to the population is crucial for the provision of high-quality services. For every 10,000 individuals, an optimal count of 20 physicians is considered ideal in Iran. However, the current ratio stands at 12.73 physicians per 10,000 individuals, which is suboptimal. An examination of the gap between the demand for and supply of physicians reveals a growing population demand, coupled with an insufficient number of physicians to meet these needs.

In a 2023 study conducted by Moradi et al., the scarcity of specialists in remote areas, where the need for medical services is greater, was highlighted. Consequently, it is imperative for health policymakers to focus on the education and distribution of specialists, taking into account the healthcare needs and indicators across diverse geographical regions (72).

Regarding the system’s financing, the cost of service provision exceeded the allocated financial resources, resulting in a budget deficit. This situation, however, was more optimistic compared to the undesired and intermediate scenarios. A 2022 study by Negarandeh and colleagues highlighted that the per capita health costs in Iran are low. Therefore, fundamental measures should be implemented to enhance the HS’s responsiveness by increasing per capita health costs and raising public awareness (73).

Conversely, to control costs, it is necessary to intensify health policies and financing structures in Iran to ensure fairer access for the population, particularly the poorest and most vulnerable individuals. The government is anticipated to implement effective measures in areas such as inpatient and outpatient care, dental services, and pharmaceuticals and equipment. Another strategy for reform is to expand the scope and depth of insurance coverage. In the long term, various insurance plans should be integrated and coordinated. Policymakers should contemplate protective measures for disadvantaged and vulnerable patients by designing benefit packages and determining the level of cost-sharing by patients. The size of packages for outpatient treatment and impoverished populations should be increased, as well as drug benefits for patients with chronic illnesses (74).

Another aspect of healthcare costs is that they are simultaneously influenced by economic growth and budget variables (real variables), as well as the financial development index and oil revenues (nominal variables). As such, forecasting healthcare costs in Iran is a multidimensional and intricate process. This issue cannot be resolved solely by implementing monetary and financial policies (demand-side policies) that merely alter the demand side and impact nominal variables in the long term. Moreover, the high likelihood of various factors influencing healthcare costs at different times underscores that multiple factors affect healthcare costs in each period. Therefore, a systemic perspective is required to gain a more realistic understanding of the factors influencing healthcare costs (75).

Subsequently, in compliance with the standards and requirements, and taking into account the country’s context, the desirable scenario was formulated and modeled. This scenario projected a desirable population of 110 million people over the next decade. The population’s exposure rate to pathogenic agents was set at 20%, resulting in a larger population of 88 million individuals who are healthy and free from risk. In this scenario, infrastructural conditions were enhanced to cater to the population’s needs in various domains such as screening, prevention, diverse Social Determinants of Health (SDH) issues, and reduction of risk factors like lifestyle modifications, treatment, etc., all the while factoring in population growth.

Influenced by the aforementioned events, there was a decline in the service delivery and management costs. Additionally, the escalation in infrastructure costs was somewhat tempered by augmenting the financial resources allocated to the health sector. Regarding medical personnel, efforts were made to boost the number of nurses, pharmacists, and dentists in line with the surge in the number and provision of physicians to the HS, at a rate of 20 per 10,000 populations.

The scenario designed in the intermediate state aligns somewhat with the current state of Iran's HS. However, in terms of population, the population of Iran is projected to reach 100 million people in the next decade. Consequently, the number of outpatients and inpatients, as well as the expenses incurred to provide services in this scenario, have increased compared to the current situation and the desirable scenario. Despite this, due to the lack of significant changes in the supply and injection of financial resources into the system, the system has been grappling with a deficit and a lack of financial resources amounting to 10,000 trillion Rials. On a positive note, there have been more desired changes in the field of inpatient beds and the influx of physicians into the HS compared to the current situation. As a result, the elimination of the physician shortage is anticipated, and an enhanced responsiveness to the needs of the population and patients is expected from the medical staff.

In the undesired scenario, which presents a direr depiction of the current state of the system, it serves as a warning for HS planners to maintain and enhance the situation. In this scenario, similar to the base model, the population of Iran is projected to be 90 million people over the next decade. However, the crucial point is that if preventive measures and promotional and informational activities are not undertaken to reduce exposure to risk factors, a significant portion of the population will be at risk. Consequently, they will require more outpatient, inpatient, pharmaceutical, and diagnostic services (between 0.07–0.1 more than the current state of the system). Given that the share of health in the GDP has decreased by 0.008 compared to the current state, the system will face a severe shortage of financial resources.

Furthermore, in the undesired scenario, the ratio of beds per thousand populations stands at 2.17, and medical equipment is at 30 per million populations, both of which are less compared to the current state of the system. Concurrently, with the escalating demand and the need for more physicians in this scenario, we will confront a severe shortage physicians and consequently, other medical staff in the system. As a result of these issues, the necessary infrastructure, financial resources, and manpower will be lacking to provide and respond to the societal needs in terms of both quantity and quality.

In this study, the findings indicate that an increase in population, coupled with risk factors, will expose a larger segment of the population to risk. Consequently, the demand for outpatient, inpatient, diagnostic, and pharmaceutical services will escalate. Through modeling, attempts were made to enhance the system’s condition and future over the next decade by modifying key parameters.

By devising desirable and intermediate scenarios, it was projected that the population will exceed 100 million in the next ten years. Concurrently, plans to reduce the population’s exposure to risk factors and investments in prevention areas were considered. Increasing the GDP and the health share from it as much as possible, along with the improvement of management structures, resulted in a reduction in system costs and a zero or positive gap between costs and the estimated required resources.

In addition to this, the development of infrastructure is of paramount importance. By increasing investment in the growth and development of beds and medical equipment, and by attracting more manpower, the system can respond more effectively to societal demands. As the population increases, the demand for service provision will inevitably rise, and the system should provide more access to services in terms of quality and quantity in an efficient and effective manner.

Alternatively, to actualize the desired state and minimize the HS's costs and societal demand for services, it is recommended that greater emphasis be placed on social components and risk factors. This necessitates the allocation of additional resources or an increase in the share of health interventions. Such a strategy should be pursued with a comprehensive and social approach.

In summary, by scrutinizing the results of this study and the constructed model, while taking into account the country's contextual conditions, it is feasible to contemplate changes in some significant parameters and indicators of the system. This allows for an evaluation of their impact on the entire HS, which can serve as a roadmap for the formulation of policies aimed at enhancing the system's future. In this study, the researchers have put forth two policy packages, in the form of desirable and intermediate scenarios, to ameliorate the system's current state.

Health system

Balanced Scorecard

BSC

Ethics approval and consent to participate

The study received ethical approval from the Research Ethics Committees of the Kerman University of Medical Sciences (IR.KMU.REC.1397.287). All participants provided informed consent prior to taking part. All methods were performed in accordance with the relevant guidelines and regulations.

Consent for publication

Not applicable.

Availability of data and materials

All data generated or analyzed during this study are included in this published article

Competing interests

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

Funding

This article is the result of a doctoral dissertation supported by Kerman University of Medical Sciences grant. No external funding was received.

Authors’ contributions

ME and MHM initiated the study and and modeled in Vensim software. ME, MHM and MAG participated in conducting the study and guiding group meetings and consulting experts. ME led data collection and analysis, wrote and revised the manuscript. MHM provided supervision of the study and peer reviewed the analysis. The authors read and approved the final manuscript.

Acknowledgments

In this article, the authors express their gratitude to the health management and policy-making experts at Kerman University of Medical Sciences who helped to model the dynamic system of the HS and advise on possible scenarios to improve the future of the system.

Murray CJ, Frenk J. A framework for assessing the performance of health systems. Bull World Health Organ. 2000;78:717-31.
Kruk ME, Gage AD, Arsenault C, Jordan K, Leslie HH, Roder-DeWan S, et al. High-quality health systems in the Sustainable Development Goals era: time for a revolution. Lancet Glob Health. 2018 Nov 1;6(11):e1196-252.
Martínez-García M, Hernández-Lemus E. Health systems as complex systems. Am. J. Oper. Res. 2013;3:113-126. doi:10.4236/ajor.2013.31A011.
Adam T. Advancing the application of systems thinking in health. Health Res Policy Syst. 2014 Dec;12(1):1-5.
Naaldenberg J, Vaandrager L, Koelen M, Wagemakers AM, Saan H, de Hoog K. Elaborating on systems thinking in health promotion practice. Glob Health Promot. 2009 Mar;16(1):39-47.
Currie DJ, Smith C, Jagals P. The application of system dynamics modelling to environmental health decision-making and policy-a scoping review. BMC Public Health. 2018 Dec;18(1):1-11.
Koelling P, Schwandt MJ. Health systems: A dynamic system-benefits from system dynamics. InProceedings of the Winter Simulation Conference; 2005 Dec 4: 7. IEEE.
Homer JB, Hirsch GB. System dynamics modeling for public health: background and opportunities. Am J Public Health. 2006 Mar;96(3):452-8. doi: 10.2105/AJPH.2005.062059. Epub 2006 Jan 31. PMID: 16449591; PMCID: PMC1470525.
Zare Mehrjerdi Y. A system dynamics approach to healthcare cost control. International Journal of Industrial Engineering & Production Research. 2012 Sep 10;23(3):175-85.
Kurnianingtyas D, Santosa B, Siswanto N. A System Dynamics for Financial Strategy Model Assessment in National Health Insurance System. InProceedings of the 2020 2nd International Conference on Management Science and Industrial Engineering; 2020 Apr 7: 44-48.
Zare Mehrjerdi Y, Khani R, Hajimoradi A. System Dynamics Approach to Model the Interaction Between Production and Pricing Factors in Pharmaceutical Industry. J. qual. eng. prod. optim. 2020 Dec 29;5(2):163-88.
Srijariya W, Riewpaiboon A, Chaikledkaew U. System dynamic modeling: an alternative method for budgeting. Value Health. 2008 Mar 1;11:S115-23.
Baibordy L, Bafandeh Zendeh A, Aali S. Designing a human resource productivity model with a system dynamics approach in the health sector. Int. J. Nonlinear Anal. Appl. 2023 Jan 1;14(1):557-73.
Forrester JWF. Principles of systems. 2nd ed. Waltham: Pegasus Communications; 1968.
Maani KE, Cavana RY. Systems thinking and modelling: understanding change and complexity. Auckland: Prentice Hall; 2007.
Emami M, Haghdoost AA, Yazdi-Feyzabadi V, Mehrolhassani MH. Identification of key components in health system using system thinking approach: A scoping review. Med J Islam Repub Iran. 2023 (3 May);37.47. https://doi.org/10.47176/mjiri.37.47.
Emami M, Haghdoost AA, Yazdi-Feyzabadi V, Mehrolhassani MH. Drivers, uncertainties, and future scenarios of the Iranian health system. BMC Health Serv Res. 2022;22(1402). https://doi.org/10.1186/s12913-022-08774-w.
Rahimi H, Kavosi Z, Shojaei P, Kharazmi E. Key performance indicators in hospital based on balanced scorecard model. J Heal Manag Informatics. 2016;4(1):17–24.
Iran Statistics Center, Office of the Presidency, Public Relations and International Cooperation. National Statistical database 2021. https://www.amar.org.ir/Portals/0/News/1402/salnameh00.pdf?ver=Q03pext2XCq79k7VDpCeww%3d%3d (2023). Accessed 1 September 2023. [In persian]
GBD 2019 Iran Collaborators. Health system performance in Iran: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2022 Apr 23;399(10335):1625-1645. doi: 10.1016/S0140-6736(21)02751-3. Epub 2022 Apr 6. PMID: 35397236; PMCID: PMC9023870.
Changizi M, Nazari M, Kaveh MH, Karimi M, Ghahremani L. The association between health-promoting lifestyle profile and chronic diseases with self-efficacy in performing health behaviors among Iranian elderly: A cross-sectional study. Health and Medical Research Journal. 2022 Jul 1;1(1):29-35.
Alborzi S, Movahhed M, Mozafari R. A Study of Healthy Behaviors with emphasize on Social and Cultural Capitals among the Youth in the City of Shiraz, Iran. Journal of Social Continuity and Change. 2022;1(1):113-129. https://doi.org/10.22034/jscc.2022.2866. [In Persian]
Tajbakhsh GhR, Ahmadi B. Socio-Cultural Factors Influencing the Health-Oriented Lifestyle of Young People. Journal of Islamic Life Style. 2023:7(1):45-57. [In Persian]
Nouraei Motlagh S, Asadi Piri Z, Asadi H, Bajoulvand R, Rezaei S. Socioeconomic status and self-rated health in Iran: findings from a general population study. Cost Eff Resour Alloc. 2022 Dec;20(1):1-10. https://doi.org/10.1186/s12962-022-00364-1.
World Health Organization, Regional Office for the Eastern Mediterranean. Environmental and occupational health. https://www.emro.who.int/iran/priority-areas/environmental-and-occupational-health.html. Accessed 6 Sept 2023.
Safavi R, Bakhshi F, Kasmaei P, Omidi S. Social determinants of health and lifestyle in the elderly. Iran J Health Educ Health Promot. 2022;9(4):372-382. [In Persian]
Sedighi arfaee F, Rashidi A, Tabesh R. Predicting the Occurrence of High-Risk Behaviors based on Behavioral-Psychological Control and Helicopter Parenting in Emerging Adulthood. Research in Clinical Psychology and Counseling. 2022;11(2):77-94. doi:10.22067/tpccp.2022.67725.1005. [In Persian]
Ebrahimi B, Doosti-Irani A, Rezapur-Shahkolai F, Poorolajal J. High-Risk Behaviors and Associated Factors among Iranian Adult Population: A National Survey. Iran J Public Health. 2022 May;51(5):1107-1117. doi: 10.18502/ijph.v51i5.9426. PMID: 36407734; PMCID: PMC9643248.
Azadnajafabad S, Mohammadi E, Aminorroaya A, Fattahi N, Rezaei S, Haghshenas R, et al. Non-communicable diseases' risk factors in Iran; a review of the present status and action plans. J Diabetes Metab Disord. 2021 Jan 22:1-9. doi: 10.1007/s40200-020-00709-8. Epub ahead of print. PMID: 33500879; PMCID: PMC7821170.
Health System Monitoring Secretariat, Vice-Chancellor of Health (Non-Communicable Diseases Unit), Ministry of Health, Treatment and Medical Education. Atlas of risk factors of non-communicable diseases in Iran (year 2021). https://nih.tums.ac.ir/UpFiles/Documents/3bc71b22-a5dc-4849-9d07-beede6b045e1.pdf. Accessed 2 September 2023. [In persian]
Farmanfarma K, Ansari-Moghaddam A, Kaykhaei M, Mohammadi M, Adineh H, Aliabd H. Incidence of and factors associated with metabolic syndrome, south-east Islamic Republic of Iran. East Mediterr Health J. 2021 Nov 1;27(11):1084-91.
General Department of Statistics and Information Engineering, Deputy of Statistics, Information and Communication Technology. Statistical database of Iran Health Insurance Organization for the year 2021. https://hibox.ihio.gov.ir/s/7qk2oyReeg8AuqT#pdfviewer (2022). Accessed 2 September 2023. [In persian]
Management of statistics, information and calculations. Statistical database of the Social Security Organization for the year 2021. https://www.tamin.ir/file/file/423878 (2022). Accessed 2 September 2023. [In persian]
Haghdoost AA, Hassan Hashemi H, Noori Hekmat S, Haji Aghajani M, Janbabaee GH, Maher A, et al. The Geographical Distribution of Hospital Beds in Iran in 2016 and the Estimation of 2026. Iranian Journal of Epidemiology. 2018;13(5), Special Issue (Foundations, Approaches and Performance of Iran's Health System):1-13. [In Persian]
Iranian newspaper (Magiran). The Ministry of Health's Deputy Minister of Medicine announced: The entry of 220 hospitals in the country into the field of health tourism. 2022. https://www.magiran.com/article/4362233. Accessed 3 October 2023. [In Persian]
Statistical Center of Iran. Statistical database of the year 2021: Health and treatment part. https://www.amar.org.ir/Portals/0/PropertyAgent/3909/Files/26736/400-99-18.pdf. Accessed 4 September 2023. [In Persian]
Production medicine Guide to buying a hospital bed for home. https://tebtolid.com/module/ybc_blog/blog?id_post=296&url_alias=-hospital-bed. Accessed: 3 October 2023. [In Persian]
Haji Aghajani M, Hashemi H, Haghdoost AA, Noori Hekmat S, Janbabaee GH, Maher A, et al. Distribution of Major Medical Equipment in Iran in 2016 and the Estimation of Needs in 2026. Iranian Journal of Epidemiology. 2018;13(5), Special Issue (Foundations, Approaches and Performance of Iran's Health System):37-47. [In Persian]
the Vice-Chancellor of Support and Resource Management of Academic Jihad. Depreciation tables. https://srm.acecr.ac.ir/fa/page/907/. Accessed 4 September 2023. [In Persian]
Iran Analytical News Agency. 60% of medical equipment in the country is unusable. 2023. https://www.khabaronline.ir/news/1812132/. Accessed 8 September 2023. [In Persian]
Vice-Chancellor of Management and Resources Development of the Ministry of Health. Inauguration of more than 2000 health projects by the end of the year. https://mrd.behdasht.gov.ir/mrd_news/%D8%A7%D9%81%D8%AA%D8%AA%D8%A7%D8%AD-%D8%A8%DB%8C%D8%B4-%D8%A7%D8%B2-2000-%D9%BE%D8%B1%D9%88%DA%98%D9%87-%D8%A8%D9%87%D8%AF%D8%A7%D8%B4%D8%AA%DB%8C-%D8%AA%D8%A7-%D9%BE%D8%A7%DB%8C%D8%A7%D9%86-%D8%B3%D8%A7%D9%84 (2023). Accessed 8 September 2023. [In Persian]
Hamidi M, Azimzadeh H, Yousefi L. Disposal of medical equipment in diagnostic and treatment centers. https://vitaip.ir/%D8%A7%D8%B3%D9%82%D8%A7%D8%B7-%D8%AA%D8%AC%D9%87%DB%8C%D8%B2%D8%A7%D8%AA-%D9%BE%D8%B2%D8%B4%DA%A9%DB%8C/. Accessed 19 November 2023. [In Persian]
National Statistics Portal, Iran Statistics Center. Satellite accounts of the health sector in 2019. https://www.amar.org.ir/HesabAghmari. Accessed 2 September 2023. [In persian]
Jahanmehr N, Noferesti M, Damiri S, Abdi Z, Goudarzi R. The projection of Iran’s healthcare expenditures by 2030: evidence of a time-series analysis. Int J Health Policy Manag. 2022;11(11):2563–2573. doi:10.34172/ijhpm.2022.5405.
Hiva's academic advice. The statistics of the participants of the national entrance exam. 2021. https://www.heyvagroup.com/shownews2/3430/%D8%A2%D9%85%D8%A7%D8%B1-%D8%B4%D8%B1%DA%A9 %D8%AA-%DA%A9%D9%86%D9%86%D8%AF%DA%AF%D8%A7%D9%86-%DA%A9%D9%86%DA%A9%D9%88 %D8%B1-%D8%B3%D8%B1%D8%A7%D8%B3%D8%B1%DB%8C-%D8%B3%D8%A7%D9%84.html. Accessed 6 September 2023. [In Persian]
Contemporary strategy. Admission capacity of the medical field in 2021. 2021. https://rahbordemoaser.ir/fa/news/98755/%D8%B8%D8%B1% D9%81%DB%8C%D8%AA-%D9%BE%D8%B0%DB%8C%D8%B1%D8%B4-%D8%B1%D8%B4%D8%AA%D9%87- %D9%BE%D8%B2%D8%B4%DA%A9%DB%8C-1400. Accessed 8 September 2023. [In Persian]
Faros Taha The admission capacity of the medical field and the required percentages in the experimental exam. 2022. https://farostaha.net/%D8%B8%D8%B1%D9%81%DB%8C%D8%AA-%D9%BE%D8%B0%DB%8C%D8%B1%D8%B4-%D8%B1%D8%B4%D8%AA%D9%87-%D9%BE%D8%B2%D8%B4%DA%A9%DB%8C-%D9%88-%D8%AF%D8%B1%D8%B5%D8%AF%D9%87%D8%A7%DB%8C-%D9%84%D8%A7%D8%B2%D9%85-%D8%AF%D8%B1-%DA%A9%D9%86%DA%A9%D9%88%D8%B1-%D8%AA%D8%AC%D8%B1%D8%A8%DB%8C-1401. Accessed 29 September 2023. [In Persian]
Young newspaper. Reduction of one million student population in 4 years. 2022. https://www.pishkhan.com/news/278784. Accessed 23 September 2023. [In Persian]
Islamic Republic of Iran Medical System Organization. Increase or Logistics. https://irimc.org/news/id/42196 (2019). Accessed 23 September 2023. [In Persian]
The statistics system of the Medical Organization of the Islamic Republic of Iran. The number of members of the medical system organization based on group, city and year. https://stats.irimc.org/Members/ActiveMembersByRegistrationDate. Accessed 8 September 2023. [In Persian]
Rasa News Agency. What is the number of physicians per capita in Iran? 2021. https://rasanews.ir/fa/news/692087/. Accessed 3 October 3 2023. [In Persian]
Tasnim News Agency. Employment of 226,000 nurses in the country's hospitals. 2023. https://www.tasnimnews.com/fa/news/1402/03/09/2904073/. Accessed 30 September 2023. [In Persian]
Iran's student news agency (ISNA). How much time should each physician spend on a patient visit? 2016. https://www.isna.ir/news/95050103440/. Accessed 8 September 8 2023. [In Persian]
Tasnim News Agency. 70% reduction in patient visits to medical centers with the implementation of the family physician/ What are the challenges of thr "family physician" in Iran? 2021. https://www.tasnimnews. com/fa/news/1400/08/24/2607468/. Accessed 8 November 2023. [In persian]
Tasnim News Agency. Argument of supporters and opponents of increasing medical capacity/How much is the cost of education for each medical student? 2021. https://www.tasnimnews.com/fa/news/1400/09/22/2624441/. Accessed 9 September 2023. [In Persian]
Nikjoo S, Rezapour A, Mojarad TB, Jahangiri R, Kemak AR, Vahedi S, et al. Cost analysis of educational courses of medical students in Iran. J Curr Biomed Rep. 2022 Mar 30;3(1):43-5.
Mehr News Agency. Details of medical sciences campus tuition fees for the academic year 2021. 2021. https://www.mehrnews.com/news/5314639/. Accessed 9 September 9 2023. [In Persian]
Presidential Council of Ministers approval. Tariff for diagnostic and therapeutic services in the public sector in 2021. https://irimc.org/Portals/0/Images/News/140002.pdf. Accessed 2 September 2023. [In persian]
Research Center of the Islamic Council: Council of Ministers' approvals. Approval of the letter regarding the determination of diagnostic and treatment service tariffs in the private sector in 2021. https://rc.majlis.ir/fa/law/show/1653353 (2022). Accessed 24 September 2023. [In persian]
Iran Statistics Center. Consumer price index. https://media.farsnews.ir/Uploaded/Files/Documents/1400/08/01/14000801000678_Test.pdf (2021). Accessed 2 September 2023. [In persian].
THE WORLD BANK. GDP growth (annual %) - Iran, Islamic Rep. https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG?locations=IR. Accessed 2 Sept 2023.
THE WORLD BANK. GDP (current US$) - Iran, Islamic Rep. https://data.worldbank.org/indicator/NY.GDP.MKTP.CD?locations=IR. Accessed 2 Sept 2023.
Economic Deputy of the Central Bank of the Islamic Republic of Iran. Report on developments in the real sector of Iran's economy in 2021. https://digim4u.com/images/news/eco-indicators/iran/1400/iran-eco-report-1400.pdf. Accessed 2 September 2023. [In persian].
Central bank of Islamic Republic of Iran. Exchange rate of 2021. https://www.cbi.ir/exrates/rates_fa.aspx. Accessed 2 September 2023. [In persian].
Analytical news society A. The mirage of desirable physician per capita in 2025/ waiting for more than 30 years if the "capacity of medical fields" does not increase. 2019. https://www.alef.ir/news/3980605064.html. Accessed 3 October 2023. [In Persian]
Kian Teb Salamat. Hospital beds per capita in Iran and the world (number of hospital beds in Iran). https://ktsalamat.com/%D8%B3%D8%B1%D8%A7%D9%86%D9%87-%D8%AA%D8%AE%D8%AA-%D8%A8%DB%8C%D9%85%D8%A7%D8%B1%D8%B3%D8%AA%D8%A7%D9%86%DB%8C-%D8%AF%D8%B1-%D8%A7%DB%8C%D8%B1%D8%A7%D9%86-%D9%86%D8%B3%D8%A8%D8%AA-%D8%A8%D9%87-%D8%AF/. Accessed 3 October 2023. [In Persian]
Mosadeghrad AM, Janbabaei Gh, Behzad Kalantari B, Darrudi AR, Dehnavi H. Equity in distribution of hospital beds in Iran. SJKU. 2020;24 (6):12-36. [In persian]
Momayez: contracting and financial accounting software. What is contract management? How is the percentage and fee calculated? 2022. http://www.momayezit.ir/blog/136/%D9%85%D8%AF%DB%8C%D8%B1%DB%8C%D8%AA-%D9%BE%DB%8C%D9%85%D8%A7%D9%86-%DA%86%DB%8C%D8%B3%D8%AA-%D9%85%D8%AD%D8%A7%D8%B3%D8%A8%D9%87-%D8%AF%D8%B1%D8%B5%D8%AF-%D9%88-%DA%A9%D8%A7%D8%B1%D9%85%D8%B2%D8%AF-%D8%A2%D9%86-%DA%86%DA%AF%D9%88%D9%86%D9%87-%D8%A7%D8%B3%D8%AA/. Accessed 12 October 2023. [In persian]
Australian Government: Department of Freign Affairs and Trade. DFAT COUNTRY INFORMATION REPORT IRAN. https://www.dfat.gov.au/sites/default/files/country-information-report-iran.pdf (2023). Accessed 18 October 2023.
Mirzaei H, Zhaleh AB, Ahmadnezhad E, Gohrimehr M, Abdalmaleki E, Alvandi R, et al. Health status in the Islamic Republic of Iran, Middle East and North Africa countries: Implications for global health. Iran. J. Public Health. 2020 Jan;49(1):86.
Rezaee R, Alimohammadzadeh K, Hosseini SM. Inequality in distribution of burn facilities in Iran. Med J Islam Repub Iran. 2019 Nov 4;33:117. doi: 10.34171/mjiri.33.117. PMID: 31934576; PMCID: PMC6946933.
Moradi R, Olyaeemanesh A, Mosadeghrad AM, Harirchi I, Larijni B. Measuring equity of geographical distribution of specialist physicians in Iran's health system. Int J Prev Med. 2023;14(60). DOI:10.4103/ijpvm.ijpvm_542_21.
Negarandeh R, Kamran A, Heydari H. Iran’s Health System Performance in Achieving Goals Based on the World Health Organization’s Framework: A Scoping Review. J. Health Res. 2022; 12(2):65-74. http://dx.doi.org/10.32598/JRH.12.2.1932.1.
Hedayati M, Masoudi Asl I, Maleki MR, Fazaeli AA, Goharinezhad S. The Variations in Catastrophic and Impoverishing Health Expenditures, and Its Determinants in Iran: A Scoping Review. Med J Islam Repub Iran. 2023 (26 Apr);37:44. https://doi.org/10.47176/mjiri.37.44.
Masoodi M, Sahabi B, Sadeghi H, Agheli L. Predicting the health expenditures in Iran using TVP models. Int. J. Nonlinear Anal. Appl. 2023 Aug 1;14(8):137-48.

Table 1. Potential Scenarios in Iran’s HS

Scenario builders	Coefficients of change in each scenario	Desirable scenario	Intermediate scenario	Undesirable scenario
The ratio of physicians to the population per 10,000 people	-	20.08 (220800)	16.01 (160100)	12.03 (108300)
	1.1 Admission rate of medical students (Med.St.Rate)	0.04	0.035	0.012
	1.2 Admission rate of general physician students in specialized fields (Spe.St.Rate)	0.08	0.078	0.047
	1.3 The entry rate of specialists into the HS (Spe.Enter.Heath Sys.Rate)	0.10	0.064	0.030
	1.4 The rate of entry of graduated general practitioners into the HS (G.P.Enter.Heath.Sys.Rate)	0.145	0.071	0.030
The ratio of beds to population per thousand people	-	3.104 (341400)	2.513 (251300)	2.177 (196000) (34)
The ratio of beds to population per thousand people	The rate of growth and development of the bed (Bed.Dev.Rate)	0.1079	0.071	0.042
The ratio of medical equipment to the population per million people	-	46.72 (5138)	35.03 (3503)	30.04 (2705)
	The rate of growth and development of medical equipment (M.E.R.rate)	0.1308	0.084	0.0535
Health inflation rate	-	0.25	0.35	0.4
Exchange rate	-	280000	298280	400000
The share of the HS in the GDP	-	0.07	0.06	0.045
GDP growth rate		0.088	0.017	-0.037
Exposure to risk factors	-	0.20	0.35	0.45
Population change coefficient	-	110000000	100000000	90000000
Population change coefficient	Birth Rate	0.0356	0.0248	0.013
Management and support costs rate in the HS	-	0.1	0.15 (68)	0.2

^{Desirable per capita physician in Iran: 20 per 10,000 populations (65)}

^{In terms of hospital beds, the global average stands at 3.1 beds per thousand individuals (66). The number 2.19 is derived from an article by Haghdoost et al. (34).}

^{In 2021, the desirable per capita hospital bed ratio in Iran was reported to be 2.5 (67).}

^{Regarding the GDP growth rate, the rate published by the World Bank (61) was utilized as the baseline for calculating its 15-year period rate in three scenarios:}^{desirable, intermediate and undesirable}^{. The highest percentage of GDP was attributed to the desirable scenario, the average percentage values from the last 15 years were included as a percentage of GDP in the intermediate scenario, and the lowest percentage was assigned to the undesirable scenario.}

^{Regarding the ratio of medical equipment to the population, the study by Aghajani et al. (38) used a base ratio of 13.8 in 2015 and 23.67 in 2014. By calculating the annual growth rate and obtaining a factor of 1.097, the growth rate for 2031 was determined to be 16.455 (calculated as 15 × 1.097). Adding this growth to the initial ratio of 13.8 resulted in the projected ratio for the year 2031, which is 46.72.}

Table 2. Change of parameters associated with health-related risk factors in each scenario, in order of the possibility of greater variability in the next ten years

Scenario builders	Desirable scenario while considering the risk factors related to health = 0.2	Intermediate scenario while considering the risk factors related to health=0.35	Undesirable scenario while considering health-related risk factors=0.45
Community nutrition status	0.0046	0.0196	0.0326
Physical activity level of people	0.0008	0.0098	0.0198
The state of obesity among people	0.0039	0.0189	0.0279
The rate of high blood pressure in the community	0.01335	0.02835	0.03785
High blood sugar levels in the community	0.004175	0.014175	0.023375
High blood cholesterol levels in the community	0.020075	0.033075	0.041075
Depression rate of society	0.0125	0.0245	0.0316
The rate of violence among individuals	0.0008	0.0098	0.0148
The rate of high-risk sexual behaviors	0.0047	0.0147	0.0214
Drug addiction rate	0.0096	0.0196	0.0246
Natural and environmental hazards	0.0305	0.0385	0.0425
Social factors related to lifestyle	0.02996	0.03696	0.03996
Economic factors related to lifestyle	0.01888	0.02688	0.03088
Cultural factors related to lifestyle	0.01616	0.02016	0.02166
HS inefficiency	0.03	0.035	0.040

Table 3. Estimated demand and supply of physicians working in the system during different years

	Time (Year)
Selected Variables Runs:	1	2	3	4	5	6	7	8	9	10
G.P.St
Undesirable scenario	68,510	69,860	71,140	72,370	73,550	74,680	75,770	76,830	77,840	78,830
Intermediate scenario	68,510	77,610	85,710	92,970	99,510	105,500	110,900	115,900	120,600	125,000
Desirable scenario	68,510	75,160	80,960	86,120	90,800	95,130	99,210	103,100	106,900	110,600
Baseline	68,510	69,310	70,080	70,830	71,560	72,280	72,970	73,660	74,330	74,990
Specialist Students
Undesirable scenario	19,930	22,550	25,160	27,750	30,320	32,860	35,390	37,890	40,360	42,810
Intermediate scenario	19,930	24,000	28,520	33,380	38,490	43,790	49,210	54,710	60,250	65,800
Desirable scenario	19,930	23,420	27,090	30,860	34,660	38,460	42,220	45,940	49,590	53,190
Baseline	19,930	22,390	24,800	27,150	29,450	31,690	33,890	36,030	38,120	40,170
Other.Med.St
Undesirable scenario	180,600	227,200	273,900	320,900	368,100	415,500	463,100	510,900	559,000	607,300
Intermediate scenario	180,600	227,200	274,500	322,500	371,400	421,100	471,600	523,000	575,200	628,400
Desirable scenario	180,600	227,200	275,000	324,100	374,600	426,400	479,700	534,500	590,800	648,600
Baseline	180,600	227,200	273,900	320,900	368,100	415,500	463,100	510,900	559,000	607,300
Per capita physician to population
Undesirable scenario	12	11.97	11.95	11.94	11.93	11.94	11.95	11.97	11.99	12.03
Intermediate scenario	12	12.23	12.54	12.91	13.33	13.8	14.31	14.85	15.42	16.01
Desirable scenario	12	12.77	13.61	14.49	15.4	16.34	17.28	18.22	19.15	20.08
Baseline	12	12.05	12.11	12.18	12.26	12.34	12.43	12.52	12.62	12.73
Nurse
Undesirable scenario	152,800	153,400	154,100	155,000	156,000	157,100	158,300	159,600	161,000	162,400
Intermediate scenario	152,800	158,600	165,600	173,600	182,600	192,500	203,200	214,800	227,100	240,200
Desirable scenario	152,800	167,300	183,500	201,100	220,000	240,200	261,400	283,700	307,000	331,200
Baseline	152,800	154,500	156,300	158,200	160,200	162,400	164,600	167,000	169,400	171,900
Dentist
Undesirable scenario	28,520	28,630	28,770	28,940	29,120	29,320	29,540	29,790	30,050	30,320
Intermediate scenario	28,520	29,610	30,910	32,410	34,080	35,930	37,940	40,100	42,400	44,840
Desirable scenario	28,520	31,230	34,250	37,540	41,070	44,830	48,800	52,960	57,310	61,830
Baseline	28,520	28,830	29,170	29,530	29,910	30,310	30,730	31,160	31,620	32,090
Pharmacologist
Undesirable scenario	19,350	19,430	19,530	19,630	19,760	19,900	20,050	20,210	20,390	20,580
Intermediate scenario	19,350	20,090	20,980	21,990	23,130	24,380	25,740	27,210	28,770	30,420
Desirable scenario	19,350	21,190	23,240	25,470	27,870	30,420	33,120	35,940	38,890	41,950
Baseline	19,350	19,560	19,790	20,040	20,300	20,570	20,850	21,150	21,460	21,770

Table 4. Estimation of the financial expenses in the HS in different scenarios examined during the years (2021-2031)

	Time (Year)
Selected Variables Runs:	1	2	3	4	5	6	7	8	9	10
Total inpatient cost
Undesirable scenario	1390	1624	1763	1851	1910	1953	1986	2012	2033	2052
Intermediate scenario	1390	1470	1545	1616	1682	1743	1799	1852	1902	1949
Desirable scenario	1390	1238	1209	1238	1295	1363	1435	1508	1579	1648
Baseline	1390	1470	1537	1594	1644	1686	1723	1755	1783	1807
Total outpatient cost
Undesirable scenario	500	605.2	678.4	733.4	777.4	814.3	846.3	874.8	900.4	923.8
Intermediate scenario	500	559.4	615.2	667.5	716.2	761.8	804.5	844.8	882.9	919.1
Desirable scenario	500	490.6	517.1	560	609.7	661.5	713.1	763.7	812.9	860.7
Baseline	500	559.4	612.1	659.3	701.6	739.7	774.2	805.5	833.9	859.9
Total pharma-diag cost
Undesirable scenario	260.5	312.9	348.5	374.5	394.8	411.7	426.1	438.7	450.1	460.4
Intermediate scenario	260.5	288	313.8	338	360.6	381.7	401.4	420	437.6	454.3
Desirable scenario	260.5	250.5	260.1	278.8	301.4	325.4	349.4	373	395.9	418.3
Baseline	260.5	288	312.2	333.8	353.1	370.4	386	400	412.8	424.4
Total cost of medical care
Undesirable scenario	2151	2542	2790	2959	3083	3179	3258	3325	3384	3436
Intermediate scenario	2151	2317	2474	2622	2759	2886	3005	3117	3222	3322
Desirable scenario	2151	1980	1986	2077	2206	2350	2498	2644	2788	2927
Baseline	2151	2317	2461	2588	2699	2796	2883	2960	3029	3091
Health cost
Undesirable scenario	172	203.3	223.2	236.7	246.6	254.3	260.7	266	270.7	274.9
Intermediate scenario	172	185.3	197.9	209.7	220.7	230.9	240.4	249.3	257.8	265.8
Desirable scenario	172	158.4	158.9	166.2	176.5	188	199.8	211.6	223	234.2
Baseline	172	185.3	196.9	207	215.9	223.7	230.7	236.8	242.3	247.3
Administrative & logistic cost
Undesirable scenario	1543	1666	1759	1837	1906	1971	2034	2096	2158	2220
Intermediate scenario	1157	1234	1313	1394	1476	1561	1649	1740	1835	1934
Desirable scenario	771.6	804.5	861.9	934.3	1017	1109	1209	1318	1436	1564
Baseline	1157	1221	1283	1344	1404	1464	1524	1585	1648	1711
Cost GPs
Undesirable scenario	20.55	20.96	21.34	21.71	22.07	22.41	22.73	23.05	23.35	23.65
Intermediate scenario	20.55	23.28	25.71	27.89	29.85	31.64	33.27	34.77	36.17	37.49
Desirable scenario	20.55	22.55	24.29	25.84	27.24	28.54	29.76	30.93	32.07	33.19
Baseline	20.55	20.79	21.02	21.25	21.47	21.68	21.89	22.1	22.3	22.5
Cost specialists
Undesirable scenario	9.965	11.28	12.58	13.87	15.16	16.43	17.69	18.94	20.18	21.4
Intermediate scenario	9.965	12	14.26	16.69	19.25	21.9	24.61	27.36	30.13	32.9
Desirable scenario	9.965	11.71	13.54	15.43	17.33	19.23	21.11	22.97	24.8	26.59
Baseline	9.965	11.2	12.4	13.58	14.72	15.85	16.94	18.01	19.06	20.08
Cost other.st
Undesirable scenario	36.12	45.43	54.78	64.17	73.61	83.09	92.62	102.2	111.8	121.5
Intermediate scenario	36.12	45.43	54.89	64.51	74.28	84.22	94.33	104.6	115	125.7
Desirable scenario	36.12	45.43	54.99	64.82	74.91	85.28	95.94	106.9	118.2	129.7
Baseline	36.12	45.43	54.78	64.17	73.61	83.09	92.62	102.2	111.8	121.5
Training costs
Undesirable scenario	389.1	400.1	411.2	422.2	433.3	444.4	455.5	466.7	477.8	489
Intermediate scenario	389.1	403.2	417.3	431.6	445.9	460.2	474.7	489.2	503.8	518.5
Desirable scenario	389.1	402.2	415.3	428.6	442	455.5	469.3	483.3	497.5	512
Baseline	389.1	399.9	410.7	421.5	432.3	443.1	453.9	464.8	475.6	486.5
Beds cost
Undesirable scenario	4248	4405	4567	4735	4909	5090	5277	5471	5672	5881
Intermediate scenario	4248	4528	4826	5143	5482	5842	6227	6636	7073	7539
Desirable scenario	4248	4685	5166	5696	6281	6926	7637	8422	9287	1.0e+16
Baseline	4248	4447	4655	4873	5101	5340	5590	5851	6125	6412
Medical equipment cost
Undesirable scenario	525.4	549.7	575	601.5	629.2	658.2	688.6	720.3	753.5	788.2
Intermediate scenario	525.4	565.7	609	655.7	705.9	759.9	818.2	880.8	948.3	1021
Desirable scenario	525.4	590.3	663.1	744.9	836.9	940.1	1056	1186	1333	1497
Baseline	525.4	560.5	597.9	637.7	680.3	725.6	774	825.7	880.7	939.5
infrastucture investing
Undesirable scenario	5004	5185	5372	5567	5769	5978	6196	6422	6656	6900
Intermediate scenario	5004	5324	5665	6029	6418	6833	7275	7748	8252	8790
Desirable scenario	5004	5505	6059	6672	7349	8097	8924	9839	1.1e+16	1.2e+16
Baseline	5004	5238	5484	5741	6012	6296	6594	6907	7236	7582

Table 5. Estimation of the supply of financial resources in the HS in different scenarios examined during the years (2021-2031)

	Time (Year)
Selected Variables Runs:	1	2	3	4	5	6	7	8	9	10
Total GDP
Undesirable scenario	388.5	374.2	360.3	347	334.2	321.8	309.9	298.4	287.4	276.7
Intermediate scenario	388.5	395.1	401.9	408.7	415.6	422.7	429.9	437.2	444.6	452.2
Desirable scenario	388.5	422.7	459.9	500.4	544.4	592.4	644.5	701.2	762.9	830
Baseline	388.5	399	409.8	420.9	432.2	443.9	455.9	468.2	480.8	493.8
GDP per capita
Undesirable scenario	4578	4380	4190	4008	3835	3669	3510	3358	3212	3073
Intermediate scenario	4578	4572	4565	4559	4553	4547	4540	4534	4528	4522
Desirable scenario	4578	4839	5116	5408	5717	6044	6389	6754	7140	7548
Baseline	4578	4671	4765	4862	4960	5061	5164	5268	5375	5484

^{The cost values presented in Table 4 are denominated in trillion Rials, with the exception of the Total Gross Domestic Product (Total GDP), which is expressed in billions of dollars, and the per capita Gross Domestic Product, which is calculated in dollars and included in Table 5. The rationale for using the dollar in GDP calculations is due to the fluctuations in the domestic and global market caused by inflation and sanctions. These fluctuations result in a constantly changing conversion rate from the dollar to the country's currency, which significantly impacts the supply of resources to various sectors, including the HS. At present, one US dollar is equivalent to 504,000 Rials, and in Iran's domestic market, one dollar is equivalent to 424,349 Rials.}

Diagrams 1 to 6 are available in the Supplementary Files section

No competing interests reported.

Download PDF

Reviews received at journal
28 Oct, 2024
Reviewers agreed at journal
19 Oct, 2024
Reviewers agreed at journal
27 Jul, 2024
Reviewers agreed at journal
24 Jul, 2024
Reviewers agreed at journal
22 Jul, 2024
Reviewers invited by journal
22 Jul, 2024
Editor assigned by journal
13 Mar, 2024
Submission checks completed at journal
04 Mar, 2024
First submitted to journal
01 Mar, 2024

You are reading this latest preprint version

Constructing Scenarios for the Iranian Health System Using Dynamic System Modeling

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Results

Discussion

Conclusions

List Of Abbreviations

Declarations

References

Tables

Diagrams

Additional Declarations

Supplementary Files

Status:

Version 1