Cost-effectiveness Analysis of Triptorelin, Goserelin, and Leuprolide in the Treatment of Patients with Metastatic Prostate Cancer: A Societal Perspective.

OBJECTIVES: Metastatic prostate cancer is the most common malignant cancer and the second leading cause of death due to various types of cancer among men after lung cancer. This study aimed to analyze the cost-effectiveness of triptorelin, goserelin, and leuprolide in the treatment of the patients with metastatic prostate cancer from the societal perspective in Iran in 2020. METHODS: This is a cost-effectiveness study in which a 20-year Markov transition modeling was applied. In this study, local cost and quality-of-life data of each health state were gathered from cohort of patients. The TreeAge pro 2020 and Microsoft Excel 2016 software were used to simulate cost-effectiveness of each treatment in the long term. The one-way and probabilistic sensitivity analyses were also performed to measure robustness of the model outputs. RESULTS: The findings indicated that the mean costs and utility gained over a 20-year horizon for goserelin, triptorelin, and leuprolide treatments were $ 13 539.13 and 6.365 quality-adjusted life-years (QALY), $ 18 124.75 and 6.658 QALY, and $ 26 006.92 and 6.856 QALY, respectively. Goserelin was considered as a superior treatment option, given the estimated incremental cost-effectiveness ratio. The one-way and probabilistic sensitivity analyses confirmed the robustness of the study outcomes. CONCLUSIONS: According to the results of the present study, goserelin was the most effective and cost-effective strategy versus 2 other options. It could be recommended to policy makers of the Iran healthcare system to prioritize it in clinical guidelines and reimbursement policies.

Nursing labor supply in Iran: a survey in Shiraz public hospitals in 2022.

BACKGROUND: The labor supply of nurses, as one of the main healthcare workers, is an important issue in health human resources planning in all health systems. Finding the factors affecting it, could help policymakers to solve the shortage of nursing work supply. The present study aimed to investigating the quantity and factors affecting the nurses' labor supply in Iran. METHOD: In this cross-sectional study, a sample of 598 nurses working in public hospitals of Shiraz (Iran) were selected via proportionate stratified random sampling method. The required data was collected using a structured questionnaire which asked working hours and other related factors. To analyze the data, descriptive statistics, univariate analysis and multivariate linear regression were performed using STATA 15. The multivariate labor supply model was estimated separately for married and single nurses.  RESULTS: The average weekly working hours of nurses was 54.65 h in all medical centers and 50.28 h in the main hospital. The regression results showed that the labor supply of nurses with work experience (ß = - 0.368, P = 0.014), satisfaction with work shift arrangement (ß = - 2.473, P = 0.001), income between 60-89 million rial (ß = - 14.046, P = 0.002), income between  90-119 million rial(ß = - 12.073, P = 0.012), and working in the emergency department (ß = - 5.043, P = 0.017) had negative and significant relationship; But there was a positive and significant relationship with satisfaction of the work environment (ß = 1.86, P = 0.011), workload at work (ß = 1.951, P = 0.023) and employment status (contractual employees) (ß = 4.704, P = 0.004). CONCLUSION: The labor supply function of nurses is affected by demographic, economic and non-economic factors. The most contributing factors were related to non-economic variables. It seems that the non-financial cost and benefits related to the job as well as internal factors have more important role on the nurses' labor supply.

Cost-effectiveness and budget impact analysis of enzalutamide in comparison to abiraterone in treatment of metastatic prostate cancer resistant to castration in Iran.

INTRODUCTION: In recent years, enzalutamide and abiraterone have been widely used as treatments for metastatic castration-resistant prostate cancer (mCRPC). However, the cost-effectiveness of these drugs in Iran is unknown. This study evaluated the cost-effectiveness of enzalutamide for the treatment of metastatic prostate cancer resistant to castration in Iran. METHODS: A 3-state Markov model was developed to evaluate the cost-effectiveness of enzalutamide and abiraterone from a social perspective over 10 years. The clinical inputs were obtained from the meta-analysis studies. The direct medical costs were obtained from the tariffs of the healthcare system, while the direct non-medical and indirect costs were collected from the patients. The data of utilities were derived from the literature. In addition, sensitivity analyses were conducted to assess the uncertainties. RESULTS: Compared with Abiraterone, enzalutamide was associated with a high incremental cost-effectiveness ratio (ICER) of $6,260 per QALY gained. According to the one-way sensitivity analysis, ICER was most heavily influenced by the prices of enzalutamide and Abiraterone, non-medical costs, and indirect costs. Regardless of the variation, enzalutamide remained cost-effective. The budget impact analysis of enzalutamide in the health system during 5 years was estimated at $6,362,127. CONCLUSIONS: At current prices, adding enzalutamide to pharmaceutical lists represents the cost-effective use of the healthcare resources in Iran for the treatment of metastatic castration-resistant prostate cancer.

Prevalence and Determinants of Catastrophic Healthcare Expenditures in Iran From 2013 to 2019.

OBJECTIVES: Protecting people against financial hardship caused by illness stands as a fundamental obligation within healthcare systems and constitutes a pivotal component in achieving universal health coverage. The objective of this study was to analyze the prevalence and determinants of catastrophic health expenditures (CHE) in Iran, over the period of 2013 to 2019. METHODS: Data were obtained from 7 annual national surveys conducted between 2013 and 2019 on the income and expenditures of Iranian households. The prevalence of CHE was determined using a threshold of 40% of household capacity to pay for healthcare. A binary logistic regression model was used to identify the determinants influencing CHE. RESULTS: The prevalence of CHE increased from 3.60% in 2013 to 3.95% in 2019. In all the years analyzed, the extent of CHE occurrence among rural populations exceeded that of urban populations. Living in an urban area, having a higher wealth index, possessing health insurance coverage, and having employed family members, an employed household head, and a literate household head are all associated with a reduced likelihood of CHE (p<0.05). Conversely, the use of dental, outpatient, and inpatient care, and the presence of elderly members in the household, are associated with an increased probability of facing CHE (p<0.05). CONCLUSIONS: Throughout the study period, CHE consistently exceeded the 1% threshold designated in the national development plan. Continuous monitoring of CHE and its determinants at both household and health system levels is essential for the implementation of effective strategies aimed at enhancing financial protection.

Epidemiological, clinical, and economic burden of myocardial infarction patients in Iran during the COVID-19 pandemic.

Background: To define changes in AMI case rates, patient demographics, cardiovascular comorbidities, treatment approaches, in-hospital outcomes, and the economic burden of COVID-19 during the pandemic. Methods: We conducted a multicenter, observational survey with selected hospitals from three medical universities in Tehran city. A data collection tool consisting of three parts. The first part included socio-demographic information, and the second part included clinical information, major complications, and in-hospital mortality. Finally, the third part was related to the direct medical costs generated by AMI in COVID-19 and non-COVID-19 patients. The study cohort comprised 4,560 hospitalizations for AMI (2,935 for STEMI [64%] and 1,625 for NSTEMI [36%]). Results: Of those hospitalized for AMI, 1,864 (76.6 %) and 1,659 (78 %) were male before the COVID-19 outbreak and during the COVID-19 era, respectively. The length of stay (LOS), was significantly lower during the COVID-19 pandemic era (4.27 ± 3.63 vs 5.24 ± 5.17, p = 0.00). Results showed that there were no significant differences in terms of patient risk factors across periods. A total of 2,126 AMIs were registered during the COVID-19 era, with a 12.65 % reduction (95 % CI 1.5-25.1) compared with the equivalent time in 2019 (P = 0.179). The risk of in-hospital mortality rate for AMI patients increased from 4.9 % in 2019 to 7.0 % in the COVID-19 era (OR = 1.42; 95 % CI 1.11-1.82; P = 0.004). Major complications were registered in 9.7 % of cases in 2020, which is higher than the rate of 6.6 % reported in 2019 (OR = 1.46, 95 % CI 1.11-1.82; P = 0.000). Total costs in hospitalized AMI-COVID patients averaged $188 more than in AMI patients (P = 0.020). Conclusion: This cross-sectional study found important changes in AMI hospitalization rates, worse outcomes, and higher costs during the COVID-19 periods. Future studies are recommended to examine the long-term outcomes of hospitalized AMI patients during the COVID-19 era.

Congestion in multi-function parallel network DEA.

Congestion is an economic phenomenon of the production process in which the excessive values of inputs lead to a reduction of the outputs. As the existence of congestion makes to increase costs and decreases efficiency, this issue is not acceptable for decision makers. Hence, many methods have been proposed to detect the congestion in the Data Envelopment Analysis framework (DEA). Most of these methods are designed to deal with the decision making units (DMUs) that have no network structure. However, in most real-world applications, some units are composed of independent production subunits. Therefore, a new scheme is required to determine the congestion of such units. A multi-function parallel system is a more common case in the real world that is composed of the same number of subunits such that each subunit has specific functions. In this paper, considering the operation of individual components of each DMU, a new DEA model is proposed to identify and evaluate the congestion of the multi-function parallel systems. It is shown that the proposed method is highly economical in comparison with the existing black-box view from a computational viewpoint. Then, the proposed model is illustrated using a numerical example along with a real case study.

COVID-19 Reinfection Rate and Related Risk Factors in Fars Province, Iran: A Retrospective Cohort Study.

Background: Reinfection with Coronavirus Diseases 2019 (COVID-19) has raised remarkable public health concerns globally. Therefore, the present retrospective cohort study intended to investigate COVID-19 reinfection in registered patients of Fars province in Iran from February 2020 to April 2021. Methods: The patients' data, including the COVID-19 infection, symptoms, comorbidities, and demographics, were collected using the Health Information Systems (HISs). The patients were divided into three groups in terms of the duration between the initial infection and reinfection, including 28-44, 45-89, and more than 90 days. Following the univariate analysis, logistic regression was used to investigate the factors effective on COVID-19 reinfection. Results: A total of 213768 patients had a positive Polymerase Chain Reaction (PCR) test. The reinfection rate was 0.97% (2079 patients). Of these re-infected individuals, 14.9%, 18.5%, and 66.6% had their second positive test 28-45, 45-89, and ≥90 days later, respectively. The mean duration between the initial infection and reinfection was 130.56 days (29-370 days). The chance of reinfection was significantly higher in the youths (Odds Ratio (OR)=2.055; P<0.001), men (OR=1.283; P<0.001), urban population (OR=1.313; P<0.001), and healthcare providers (OR=4.453; P<0.001). The patients with chronic pulmonary diseases, chronic kidney diseases, and malignancy were 1.421 (P=0.036), 2.239 (P<0.001), and 3.437 (P<0.001) times, respectively, more likely prone to reinfection. Conclusion: The results of this study showed that there is a higher risk of reinfection in several vulnerable groups including healthcare providers, young individuals, residents of urban areas, men, and individuals with underlying diseases.

A novel algorithm for complete ranking of DMUs dealing with negative data using Data Envelopment Analysis and Principal Component Analysis: Pharmaceutical companies and another practical example.

When there is an extensive number of inputs and outputs compared to the number of DMUs, one of the drawbacks of Data Envelopment Analysis appears, which incorrectly classifies inefficient DMUs, as efficient ones. Accordingly, the DEA ranking power becomes further moderated. To improve the ranking power, this paper renders the details of an algorithm that presents a model combining the Principal Component Analysis and the Slacks-Based Measure (PCA-SBM) which reduces the number of the incorrectly determined efficient DMUs. Also to complete ranking of DMUs, the algorithm presents a Super-Efficiency model integrated with PCA (PCA-Super SBM) which can rank the efficient DMUs (extreme and non-extreme). Whereas the most important previous models for ranking efficient units cannot rank non-extreme ones. Additionally, in most previous studies, DEA models combined with PCA fail to handle negative data, while, the presented models can cover this data. Two case studies (pharmaceutical companies listed on the Iranian stock market and bank branches) are manipulated to demonstrate the applicability and performance of the algorithm. To show the superiority of the presented models, the SBM model without PCA and the Super SBM model without PCA have been implemented on the data of both cases. In comparing the two methods (PCA-SBM and SBM), the PCA-SBM model has higher ranking power (five efficient DMUs versus nineteen in the case of pharmaceutical companies and four efficient DMUs versus twenty-nine in the case of bank branches). Also in comparing the PCA-Super SBM and Super SBM, the PCA-Super SBM model works more powerfully in complete ranking. As the Super SBM model cannot rank non-extreme units unlike the PCA-Super SBM. Consequently, the presented algorithm works successfully in ranking the DMUs completely (inefficient, extreme, and non-extreme efficient) with low complexity.

Cost-Effectiveness of Health Literacy Enhancement Intervention on Patients with Type II Diabetes.

Background: Type II diabetes is considered a chronic disease that influences the affected person's quality of life and imposes a high economic burden on the patient and society. The enhancement of health literacy seems essential for self-management and disease control in patients with type II diabetes. Consequently, this study was performed to evaluate the cost-effectiveness of enhanced health literacy in type II diabetes patients. Methods: This study was of quantitative and economic evaluation type. A population of 232 patients was selected among those referred to the Tafihan Shiraz clinic based on the quality of entry and exit. The health literacy educational intervention was carried out for three months. In order to collect information, researchers used the SF36 questionnaire and the checklist of costs. The Cost Effectiveness Ratio (CER) and Incremental Cost Effectiveness Ratio (ICER) were calculated. Moreover, the costs of each unit of increasing the quality of life before and after the intervention were calculated. A decision was made to determine the cost-effectiveness of the intervention. Results: According to the results, 40% of the participants were females, and 34.5% were 30-40 years old. Examination of the quality of life in patients before the intervention indicated that the mean and standard deviation of the patients' quality of life before the intervention was 18.43±44.99, and the mean and standard deviation of the quality of life after the intervention was 49.57±16.21. Moreover, the patients' quality of life increased after the educational intervention. The total direct medical costs were $717,484 and $685,620 before and after the intervention, respectively. The total indirect medical costs were $604,122 and $493,011 before and after the intervention, respectively. Moreover, the total indirect costs were $122,535 and $122,119 before and after the intervention, respectively. The study was cost-effective with CER=0.9 and ICER= - 140,000 per increase in the quality of life. Conclusion: Improving health literacy can have a range of benefits and improve the quality of life of patients with type II diabetes and reduce their treatment costs, and thereby, this may be seen as an effective step toward the recovery of patients with type II diabetes.

The effect of Covid-19 pandemic on healthcare utilization in public vs private centers in Iran: a multiple group interrupted time-series analysis.

BACKGROUND: The outbreak of Coronavirus in late 2019 and its continuation in the following years has affected all human societies, government organizations, and health systems. Access to health services is an important issue during crises. The present study aimed to investigate the effect of the Covid-19 pandemic on the consumption of health services in the public sector compared to the private sector in Iran. METHODS: The research population consisted of all insured individuals covered by Iran Health Insurance Organization in Fars province, which amounts to approximately 2,700,000 people. The required information including the utilization of laboratory, radiology, medicine, and hospitalization services was extracted on a monthly basis from February 2019 to February 2021. The Multiple Group Interrupted Time Series Analysis (MGITSA) was used for data analysis along with STATA.15 software. RESULTS: According to the findings of MGITSA, in the short-term, the utilization of private laboratory, radiology, medication, and hospital admissions had decreased by approximately 18,066, 8210, 135,445, and 1086 times, respectively (P < 0.05). In the long-run, the use of laboratory and radiology services had increased by about 2312 and 514 times (P < 0.05), respectively. The comparison between the public and private sectors showed that in the short-term, the use of radiology services decreased by about 12,525, while the use of medication increased by about 91,471 times (P < 0.05). In the long-run, the use of laboratory services decreased by about 1514 times (P = 0.076) and no change was observed in the other services utilization (in public relative to private centers). CONCLUSIONS: Utilization of health services in the public versus private centers, except for medication and hospitalization, significantly decreased in the short-term. However the utilization of most services returned to the usual trend in the long-term. The reduction in access to health services could impose a significant burden of various diseases, at least in the short-term, and increase health costs in the coming years.

Utilization and cost of outpatient services: A cross-sectional study on the Iran Health Insurance Organization insurees in Fars province.

Background and Aims: Analyzing the utilization of health services is necessary for allocating the resources and planning the provision of health services. The present study aimed at investigating the utilization and cost of outpatient services and the factors affecting it among the insurees of the Iran Health Insurance Organization in Fars province in 2019. Methods: The study population consisted of all Iran Health Insurance Organization insurees in Fars province in 2019 (n = 2,618,973). The data on the utilization and cost of the services were extracted from the information systems of Fars Health Insurance Organization. The descriptive statistics of the utilization and cost of outpatient services were provided by gender, age, and type of insurance fund. The effects of different factors on the utilization and cost of various services were also investigated using univariate analysis as well as cross-sectional regression. The data analysis was done using EXCEL and STATA 15 software as well. Results: The average utilization rates of laboratory, drug, and radiology services were 0.940, 0.945, and 0.108 prescriptions per year, respectively. In addition, the mean costs of laboratory, drug, and radiology services were $1.13, $7.44, and $2.26 per year, respectively. The univariate and multivariate analyses showed that gender, type of insurance fund, and age had significant effects on the utilization and costs of laboratory, drug, and radiology services (p < 0.05). Conclusion: The utilization and expenditure of outpatient services were higher among the elderly and women. To control the costs of insurance organizations, it is helpful to identify the effective factors. In addition, due to the increasing trend of aging in Iran, it seems necessary to periodically monitor the pattern of the elderly people's utilization of health services and to plan to increase sustainable resources for insurance financing in the coming years.

Economic burden of cervical cancer and premalignant lesions associated with human papilloma virus: a societal perspective.

BACKGROUND: Cervical cancer is one of the most common cancers in women, the cause of which is mostly human papilloma virus (HPV). The aim of this study was to determine the economic burden of cervical cancer and premalignant lesions associated with HPV infection from a societal perspective. METHODS: The study is a partial economic evaluation (cost of illness), which was conducted cross-sectionally in the referral university clinic in Fars province in 2021. The prevalence-based and bottom-up approaches used to calculate the costs, the indirect costs were calculated by human capital approach. RESULTS: The mean cost of premalignant lesions associated with HPV infection was USD 2,853 per patient, which 68.57% was direct medical costs. In addition, the mean cost of cervical cancer was USD 39,327 per patient, the largest share of which (57.9%) was related to indirect costs. The mean annual cost of cervical cancer patients in the country was estimated at USD 40,884,609 as well. CONCLUSION: Cervical cancer and premalignant lesions associated with HPV infection imposed a significant economic burden on the health system and patients. The results of the present study can help health policymakers with efficient and equitable prioritization and allocation of resources.

Modeling land use/cover change based on LCM model for a semi-arid area in the Latian Dam Watershed (Iran).

The monitoring and modeling of changes, based on a time-series LULC approach, is fundamental for planning and managing regional environments. The current study analyzed the LULC changes as well as estimated future scenarios for 2027 and 2037. To achieve accuracy in predicting LULC changes, the Land Change Modeler (LCM) was used for the Latian Dam Watershed, which is located approximately in the northeast of Tehran. The LULC time-series technique was specified utilizing four atmospherically endorsed surface reflectance Landsat images for the years t1 (1987), t2 (1998), t3 (2007), and t4 (2017) to authenticate the LULC predictions, so to obtain estimates for t5 (2027) and t6 (2037). The LULC classes identified in the watershed were water bodies, build-up areas, vegetated areas, and bare lands. The dynamic modeling of the LULC was based on a multi-layer perceptron (MLP), the neural network in LCM, which presented good results with an average accuracy rate equivalent to 84.89 percent. The results of the LULC change analysis showed an increase in the build-up area and a decrease in bare lands and vegetated areas within the duration of the study period. The results of this research could help in the formulation of public policies designed to conserve environmental resources in the Latian Dam Watershed and, consequently, minimize the risks of the fragmentation of orchards and vegetated areas. Also, careful regional planning ensuring the preservation of natural landscapes and open spaces is critical to creating a resilient regional environment and sustainable development.

Development of a model for predicting hospital beds shortage and optimal policies using system dynamics approach.

BACKGROUND: Policymakers use simulation-based models to improve system feedback and model the reality of the problems in the system. This study uses the system dynamics approach to provide a model for predicting hospital bed shortages and determine the optimal policy in Shiraz, Southern Iran. METHODS: This study was designed based on Sterman's system dynamic modeling (SDM) process. Firstly, we determined the main variables affecting bed distribution using a mixed qualitative and quantitative study which includes scoping review, expert panel, Delphi, and DANP. Then, dynamic hypotheses were designed. Subsequently, we held several expert panels for designing the causal and stock-flow models, formulating and testing a simulation model, as well as developing various scenarios and policies. RESULTS: Dynamic modeling process resulted in four scenarios. All of the scenarios predicted a shortage of national hospital beds over a 20-year time horizon. Then, four policies were developed based on the changes in the number of beds and capacity of home care services; finally, the optimal policy was determined. CONCLUSIONS: Due to the high cost of setting up hospital beds, developing and supporting cost-effective home care services, strengthening the insurance coverage of these services, and improving the quantity and quality of community care, considering the real needs of the community could be considered as an optimal option for the future of the city.

Stability analysis with general fuzzy measure: An application to social security organizations.

An effective method for evaluating the efficiency of peer decision-making units (DMUs) is data envelope analysis (DEA). In engineering sciences and real-world management problems, uncertainty in input and output data always exists. To achieve reliable results, uncertainties must be taken into account. In this research, a General Fuzzy (GF) approach is designed to cope with uncertainty in the presence of fuzzy observations for categorizing and specifying stability radius and alterations ranges of efficient and inefficient DMUs, which is applicable to real-world decision-making problems. For this purpose, a DEA sensitivity analysis model is presented, which will be modeled by fuzzy sets. Then, by applying the General Fuzzy (GF) approach, the fuzzy DEA sensitivity analysis model is transformed into the equivalent crisp form of fuzzy chance constraints according to specific confidence levels. Finally, a numerical example and a case study of branches of the social security organization are presented to illustrate sensitivity and stability analysis in the presence of fuzzy data. The obtained results provide the input and output changes of the evaluated units according to the attitude and preference of the decision maker with different confidence levels so that the data changes in the fuzzy environment do not change the units' classification from efficient to inefficient and vice versa.

Determining Factors Influencing Specialty Preferences of Iranian Medical Doctors: A Qualitative Study.

Background: The medical specialty choice of physicians directly affects the healthcare system, community wellbeing, and their own professional life. It is therefore important to identify its underlying factors to predict such medical career choices and to draw up a comprehensive evidence-based public health policy and health human resources planning. The present qualitative study aimed to identify these determinants of career choices through semi-structured interviews with medical doctors in the context of country-specific social and cultural characteristics. Methods: The present qualitative study was carried out in 2019-2020 at Shiraz University of Medical Sciences (Shiraz, Iran). The target population was medical students, junior doctors, and medical residents. The purposive sampling method was used to recruit the participants and sampling continued until data saturation, i.e., no new information could be extracted. Data were collected through individual, face-to-face, semi-structured interviews and analyzed using the conventional content analysis method. Inductive thematic analysis was used to interpret the data based on which a thematic map was developed illustrating the factors influencing medical specialty preferences in Iran. Data trustworthiness was assessed according to the criteria proposed by Guba and Lincoln. Results: Analysis of the interview data resulted in three main themes and fourteen sub-themes. The main themes were "Personal determinants", "Career-related factors", and "Interpersonal influences". The most important sub-themes were personal interests, income, and prestige. Conclusion: The determinants influencing the specialty preferences of Iranian medical doctors are identified. Our findings will facilitate the development of a comprehensive evidence-based public health policy, health human resources planning, and appropriate medical education policy.

Economic burden of major depressive disorder: a case study in Southern Iran.

BACKGROUND: Depression disorders are a leading cause of disability in the world which imposes a significant economic burden on patients and societies The present study aimed to determine the economic burden of Major Depressive Disorder (MDD) on the patients referred to the reference psychiatric single-specialty hospitals in southern Iran in 2020. METHODS: This cross-sectional research is a partial economic evaluation and a cost-of-illness study conducted in southern Iran in 2020. A total of 563 patients were enrolled through the census method, and a researcher-made data collection form was used to gather the required information. The prevalence-based and the bottom-up approaches were also used to collect the cost information and calculate the costs, respectively. The data on direct medical, direct non-medical, and indirect costs were obtained using the information in the patients' medical records and insurance bills as well as their self-reports or those of their companions. To calculate the indirect costs, the human capital approach was used as well. RESULTS: The results showed that the annual cost of MDD was $ 2717.41 Purchasing Power Parity (PPP) (USD 2026.13) per patient in 2020. Direct medical costs accounted for the largest share of the costs (73.68%), of which hoteling and regular beds expenses were the highest (57.70% of the total direct medical costs). The shares of direct non-medical and indirect costs were 7.52 and 18.80%, respectively, and the economic burden of the disease in the country was estimated at $7,120,456,596 PPP (USD 5,309,088,699). CONCLUSION: In general, due to the high prevalence of MDD and the chronicity of the disease, the costs of its treatment can impose a heavy economic burden on the society, healthcare system, insurance system, and the patients themselves. Therefore, it is suggested that health policymakers and managers should take appropriate measures to increase the basic and supplemental insurance coverage of these patients. In addition, in order to reduce the costs, proper and equitable distribution of psychiatrists and psychiatric beds, expansion of home care services, and use of Internet-based technologies and the cyberspace to follow up the treatment of these patients are recommended.

The impact of Health Transformation Plan on natural vaginal delivery and cesarean section frequency in Iran: an interrupted time series analysis.

OBJECTIVE: This study was conducted to evaluate the effect of the Iran's Health Transformation Plan on the frequency of natural vaginal deliveries (NVDs), cesarean sections (CSs), and total deliveries in the Fars province of Iran. RESULTS: Average number of total deliveries before and after the reform were 3946 and 3810, respectively (p = 0.164). The ratio of CS to total deliveries in the first study month was 54%. This rate reached 47% in the last month (p < 0.01). However, it had much fluctuation trend. The ITSA results showed that in the short-run, the NVD rate increased (ß = 492.79, p < 0.01), the rate of CS decreased (ß = - 407.09, p < 0.01), and total deliveries increased (ß = 85.75, p < 0.724). However, in the long-run, the NVD (ß = 5.74, p < 0.423), CS (ß = 10.21, p < 0.189), and total deliveries (ß = 15.96, p < 0.256) had no significant changes after the reform. Encouraging the NVD package was influential in the short-run but not in the longrun in Iran. Pricing and supply-side policies could not reduce the rate of non-clinical CS on their own. Therefore, paying attention to demand-side policies and changes in consumer behaviors, such as educating the women at the age of pregnancy about the advantages and disadvantages of CS and NVD and correcting misconceptions, could be helpful.

The inappropriateness of brain MRI prescriptions: a study from Iran.

BACKGROUND: Inappropriate prescriptions can lead to adverse consequences for patients. It also imposes excessive cost on the patients, payers and health systems. The current study aimed at estimating the rate of inappropriate brain Magnetic Resonance Imaging (MRI) prescriptions and their financial burden in Iran. METHODS: Using systematic stratified sampling method, this cross-sectional study recruited 385 participants from three public teaching hospitals in Shiraz, Iran. Demographic information, questions related to brain MRI prescription and its indications checklist were collected using study-specific data collection tools. The completed indications checklist was compared to the appropriateness status table of indications and scenarios to detect the percent of the appropriateness of prescriptions. RESULTS: About 21 percentage of total brain MRI prescriptions are inappropriate. Previous treatment, number of referrals to physician, having other diagnostic tests and the applicant of MRI (P < 0.01) had significant relationships with prescription appropriateness. The estimated financial burden of inappropriate brain MRIs in Shiraz teaching hospitals was 99,988 US dollar in 2017. CONCLUSIONS: More than one-fifth of brains MRIs were inappropriate (i.e. prescriptions without medical indications). It caused 99,988 United States Dollar (USD) financial burden which is 17 times that of Iran's Gross Domestic Product (GDP) per capita. To better allocate resources for the provision of MRI services to health system, rationing policies for controlling moral hazard and reducing provider induced demand can be helpful.

A thematic network for factors affecting the choice of specialty education by medical students: a scoping study in low-and middle-income countries.

BACKGROUND: Medical specialty selection is a complex phenomenon that can affect the performance of health systems, community health, and physicians' lives. It is essential to identify the key factors influencing the choice of specialty for evidence-based policymaking. This scoping review aimed to provide a comprehensive map of evidence regarding the factors influencing the choice of specialty by medical students (MS) in low-and middle-income countries (LMICs) and also to determine knowledge gaps. METHODS: We carried out a systematic search on six online databases from January 2000 to May 2020. We used a five-step scoping review method proposed by Arksey and O'Malley. We synthesized the data using a quantitative content analysis approach. Then, we developed a thematic network as a conceptual map for a better understanding of the concept. RESULTS: The analysis led to the development of five main themes, including personal determinants, life fulfillment aspects, influential career aspects, educational determinants, and interpersonal effects. Moreover, the most frequent sub-themes were specific personal factors, controllable lifestyle, quality of working life, and future working conditions. CONCLUSION: This review provided evidence on the factors influencing the choice of specialties. In order to support physician workforce policy with more precise evidence, it is necessary to explore the weight and ranking of these factors based on the socioeconomic contexts of the countries. This study also indicated that factors such as ethical values, various aspects of medical philosophy, and immigration tendencies are areas for further investigations.