Summary Introduction Back pain is a common global disorder and magnetic resonance imaging (MRI) is one method of assessing its cause. The lack of official and general clinical guidelines is the cause of inadequate supervision of lumbar MRI prescriptions. The goal of this research was to analyze inappropriate lumbar MRI prescriptions and the resulting economic burden on individuals. Method This is a descriptive‐analytical study carried out on a sample of 614 patients who visited four hospitals in Tehran. The appropriateness or inappropriateness of the MRI prescriptions was determined using clinical guidelines and a questionnaire based on previous studies. The economic burden created by inappropriate prescriptions for MRIs was determined after calculating the total direct and indirect costs. Findings The total MRI prescription cost paid by the study sample was $26 071, and the cost of inappropriate prescriptions was $10 310. The MRI prescription rate had a significant relationship with gender, age, education, employment, primary insurance type, and supplemental health insurance. Conclusion The research findings revealed relatively high rates of inappropriate MRI prescriptions in the private and public sectors. Hence, policymakers should design, create, and develop clinical guidelines and enforce the policies and rules to decrease inappropriate MRI prescriptions.

Background: The projection of levels and composition of financial resources for the Healthcare expenditure (HCE) and relevant trends can provide a basis for future health financing reforms. This study aimed to project Iran’s healthcare expenditures by the sources of funds until 2030. Methods: The structural macro-econometric modeling in the Eviews 9 software was employed to simulate and project Iran’s (HCE) by the sources of funds (Government (GHCE), Social Security Organization (SOHCE), Out-of-Pocket Payments (OOP), and Prepaid Private Health Spending (PPHCE)). The behavioral equations were estimated by Autoregressive Distributed Lag (ARDL) approach. Results: If there is a 5%-increase in Iran’s oil revenues, the mean growth rate of GDP is about 2% until 2030. By this scenario, the Total HCE(THCE), GHCE, SOHCE, OOP, and PPHCE increases about 30.5%, 25.9%, 34.4%, 31.2%, and 33.9%, respectively. Therefore, the THCE as a percentage of the GDP(Gross Domestic Product)) will increase from 9.6% in 2016 to 10.7% in 2030. It is predicted that Iran’s THCE will cover 22.2%, 23.3%, 40%, and 14.5% by the government, Social Security Organization, households OOP, and other private sources, respectively, in 2030. Conclusion: Until 2030, Iran’s health expenditures will grow faster than the GDP, government revenues, and non-health spending. Despite the increase in GHCE and total government expenditure, the share of the GHCE from THCE has a decreasing trend. OOP payments remain among the major sources of financing for Iran’s HCE.

Background The present study has been undertaken with the aim to evaluate performance and ranking of various universities of medical sciences that are responsible for providing public health services and primary health care in Iran. Methods Four models; Weighted Factor Analysis (WFA), Equal Weighting (EW), Stochastic Frontier Analysis (SFA), and Data Envelopment Analysis (DEA) have been applied for evaluating the performance of universities of medical sciences. This study was commenced based on the statistical reports of the Ministry of Health and Medical Education (MOHME), census data from the Statistical Center of Iran, indicators of Vital Statistics, results of Multiple Indicator of Demographic and Health Survey 2010, and results of the National Survey of Risk Factors of non-communicable diseases. Results The average performance scores in WFA, EW, SFA, and DEA methods for the universities were 0.611, 0.663, 0.736 and 0.838, respectively. In all 4 models, the performance scores of universities were different (range from 0.56–1, 0.53–1, 0.73–1 and 0.83–1 in WFA, EW, SFA and DEA models, respectively). Gilan and Rafsanjan universities with the average ranking score of 4.75 and 41 had the highest and lowest rank among universities, respectively. The universities of Gilan, Ardabil and Bojnourd in all four models had the highest performance among the top 15 universities, while the universities of Rafsanjan, Ahvaz, Kerman and Jiroft showed poor performance in all models. Conclusions The average performance scores have varied based on different measurement methods, so judging the performance of universities based solely on the results of a model can be misleading. In all models, the performance of universities has been different, which indicates the need for planning to balance the performance improvement of universities based on learning from the experiences of well-performing universities.

Background Understanding the Spatio-temporal distribution and interpersonal comparisons are important tools in etiological studies. This study was conducted to investigate the temporal and geographical distribution of COVID-19 hospitalized patients in the Iran Health Insurance Organization (IHIO) insured population (the second largest social health insurance organization) and the factors affecting their case fatality rate (CFR). Methods In this descriptive-analytical cross-sectional study, the demographic and clinical data of all insured of the IHIO who were hospitalized with COVID-19 in hospitals across the country until March 2021 was extracted from the comprehensive system of handling the inpatient documents of this organization. The Excel 2019 and GeoDA software were used for descriptive reporting and geographical distribution of variables. A multiple logistic regression model was used to estimate the Odds Ratio (OR) of death in patients with COVID-19 using STATA 14 software. Results During the first 14 months of the COVID-19 outbreak in Iran, 0.72% of the IHIO insured (303,887 individuals) were hospitalized with COVID-19. Hospitalization per 100,000 people varied from 192.51 in East Azerbaijan to 1,277.49 in Yazd province. The overall CFR in hospitalized patients was 14%. Tehran and Kohgiluyeh & BoyerAhmad provinces had the highest and lowest CFR with 19.39% and 5.19%, respectively. The highest odds of death were in those over 80 years old people (OR = 9.65), ICU-admitted (OR = 7.49), Hospitalized in governmental hospitals (OR = 2.08), Being a foreign national (OR = 1.45), hospitalized in November (OR = 1.47) and Residence in provinces such as Sistan & Baluchestan (OR = 1.47) and Razavi Khorasan (OR = 1.66) respectively. Furthermore, the odds of death were lower in females (OR = 0.81) than in males. Conclusions A sound understanding of the primary causes of COVID-19 death and severity in different groups can be the basis for developing programs focused on more vulnerable groups in order to manage the crisis more effectively and benefit from resources more efficiently.

Background: Universities of medical sciences (UMSs) in Iran have geographic catchment areas (normally a province) in which they are responsible for public health services as well as provision of care by public providers. The present study strived to analyze and rank the performance of the medical sciences universities in improving the public health and primary healthcare. Methods: Data on 41 indicators on the output (16 indicators), outcome (16 indicators), and impact (9 indicators) levels were extracted from various data sources. Principal component analysis (PCA) was used to calculate the weight for each of the indicators. The score range for each level of performance is between 0 and 1. A score of 1 indicates the highest and a score of 0 indicates the lowest level of performance. Finally, the UMSs were ranked by their scores. Results: The national mean performance scores of the UMSs on the output, outcome, impact, and the composite indicator levels were 0.756, 0.641, 0.561, and 0.563, respectively. The results show that the changes in performance scores at different levels of the results chain are remarkable. Conclusion: The national mean performance of the UMSs of Iran is not satisfactory. However, there is considerable dispersion in their performance. Designing effective interventions in proportion to the conditions of universities on different levels of the results chain, developing a robust information system, conducting continuous monitoring and evaluation of public health are recommended for balanced improvements in public health and primary healthcare indicators in the country.