Economic impact of government health expenditure: An application of the computable general equilibrium model to the Iran.

BACKGROUND: Considering the increase in health expenses and the government's role in health financing, this study investigated the economic impact of increases in the share of the health sector in the government budget while taxes remain unchanged and government spending is fixed. MATERIAL AND METHODS: The economic model used in this study was a macroeconomic Computable General Equilibrium (CGE) model. This model was calibrated using a 2011 Social Accounting Matrix (SAM) Of Iran. The CGE model was solved with non-linear programming using the General Algebraic Modeling System package, version 2.50. The effect of this simulation on the government budget deficit, the production of different sectors of the economy, and the employment rate was investigated. RESULTS: Based on our fundings the elasticity of substitution in the agricultural and industrial sectors is higher than in the health and service sector. Also, the biggest decrease in production occurred in the industry, agriculture, and service sectors, respectively. With the doubling of the share of government spending in the health sector, the employment rate of this sector has increased by 40.9%, but the highest decrease in the ignition rate is related to the service sectors (-2.7%), agriculture (-0.23%), and industry (-0.14%). CONCLUSION: Increasing the share of government spending in the health sector in comparison with other sectors of the economy, provided that government spending is maintained in general, leads to a decrease in production and economic welfare. It seems that the Iranian government should seek to increase the sources of health financing and the share of government expenditures in the health sector with other ways in order to improve the health level of the society and have a positive effect on other economic sectors.

Out-of-pocket pharmaceutical expenditure and its determinants among Iranian households with elderly members: a double-hurdle model.

OBJECTIVES: The population of older adults continues to grow in Iran, with pharmaceutical costs as a leading driver of household health-related costs. The present study was conducted to estimate the out-of-pocket pharmaceutical expenditure and its socioeconomic predictors among households with the elderly in Iran. METHOD: This study is a secondary analysis using 2019 national household expenditure and income survey data in Iran. The sample size was 9381 households with at least one member older than 65. The double-hurdle model in STATA 16 was used to examine the association between independent variables and households' out-of-pocket pharmaceutical expenditures. RESULTS: The mean out-of-pocket pharmaceutical expenditures for each household with elderly member was $8065 per year. There was a positive association between the (female) gender of the household head, urban residence, employment status, insurance expenditure and a higher level of education of the head of the household with the out-of-pocket pharmaceutical expenditures (P < 0.05). The income of elderly households did not affect these expenditures (P > 0.05). CONCLUSIONS: This study showed that the socioeconomic characteristics of elderly families not only influenced their decision to enter the medicine market, but also the rate of medicine purchase. It is helpful to manage and control the pharmaceutical costs among the elderly.

Years of life lost (YLL) associated with COVID-19 deaths in Khorasan-RAZAVI province, Iran.

BACKGROUND: The number of deaths among people with coronavirus disease 2019 (COVID-19) does not show the true impact of the disease on communities. Therefore, this study aimed to calculate years of life lost (YLL) due to premature death in patients with COVID-19. METHODS: We performed a descriptive cross-sectional study based on data from one of the largest provinces of Iran, in the period 13 February 2020 to 17 May 2021. We used WHO proposed guidelines for the calculation of the burden of diseases to calculate the YLL among patients with COVID-19, taking into consideration gender in different age groups. RESULTS: Findings showed that 13 628 deaths were due to COVID-19 with associated 249 309 YLL. The study reported higher mortality among men (1222 cases) in the age group over 85 years than in women (840) of the same age group. The minimum number of YLL for men was 1749 in the 5-9 years age group and that for women was 1551 years in the 14-10 years age group. CONCLUSION: The high number of deaths due to COVID-19 has led to high YLL due to premature death. The provision of adequate health care and appropriate policies will bring about a decrease in YLL due to COVID-19.

The Impact of Inflation and Its Uncertainty on Pharmaceutical Prices: Evidence from Iran.

Pharmaceutical productions are recognized as an essential commodity in the economical literature; therefore, an increase in their prices leads to an increase in the household budget. Currently, about 15-20% of the entire health expenditure in Iran is allocated to the pharmaceutical sector. This study aimed to investigate the effect of inflation and its uncertainty on inflation in pharmaceutical prices in Iran. In this study, the monthly time series of consumer price index from 2001 to 2017 was used to calculate inflation uncertainty based on a generalized autoregressive conditional heteroscedasticity model. Hylleberg-Engle-Granger-Yoo test was performed to determine the stationary of the data. Feasibility tests were also used to explore the application of Autoregressive conditional heteroscedasticity family models to these data. The causal relationship between inflation uncertainty and inflation in the pharmaceutical sector was investigated using the Granger causality test. A causal relationship was found between inflation and inflation uncertainty at the 95% confidence interval for the monthly data during the study. It was revealed that Inflation uncertainty did not affect the inflation in the pharmaceutical prices, but inflation can be a cause of pharmaceutical inflation. Although inflation uncertainty has no association with pharmaceutical inflation, it seems that it could affect pharmaceutical inflation through inflation in other sectors. Therefore, adopting appropriate monetary policies aimed at controlling liquidity and inflation can effectively control pharmaceutical prices.

Development, Implementation, and User Evaluation of COVID-19 Dashboard in a Third-Level Hospital in Iran.

INTRODUCTION: The implementation of a dashboard enables managers to make informed and evidence-based decisions through data visualization and graphical presentation of information. This study aimed to design and implement a COVID-19 management dashboard in a third-level hospital in Mashhad, Iran. MATERIALS AND METHODS: This descriptive developmental applied study was conducted in the second half of 2020 in three stages, using user-centered design methodology in four phases: (1) specification of the application context, (2) specification of requirements, (3) creation of design solutions, and (4) evaluation of designs. Data collection in each phase was performed through holding group discussions with the main users, nominal group techniques, interviews, and questioners. The dashboard prototype for the data display was designed using the Power BI Desktop software. Subsequently, users' comments were obtained using the focus group method and included in the dashboard. RESULTS: In total, 25 indicators related to input, process, and output areas were identified based on the findings of the first stage. Moreover, eight items were introduced by participants as dashboard requirements. The dashboard was developed based on users' feedback and suggestions, such as the use of colors, reception of periodic and specific reports based on key performance indicators, and rearrangement of the components visible on the page. The result of the user satisfaction survey indicated their satisfaction with the developed dashboard. CONCLUSION: The selection of proper criteria for the implementation of an effective dashboard is critical for the health care organization since they are designed with a high-tech and content-based environment. The dashboard in the present study was a successful combination of clinical and managerial indicators. Future studies should focus on the design and development of dashboards, as well as benchmarking by using data from several hospitals.

Technical efficiency and its affecting factors in Tehran's public hospitals: DEA approach and Tobit regression.

Background: Measuring hospital efficiency is one of the tools for determining how to use resources. Considering the necessity of measuring the efficiency in hospitals, the current study was conducted to evaluate the efficiency and its determining factors in the Hospitals affiliated to medical universities in Tehran. Methods: This was a descriptive-analytical and longitudinal study. In the first stage of the research, the variables affecting the efficiency of hospitals were extracted using the Delphi method. In the second stage, th. Efficiency of 29 public hospitals in Tehran from 2012 to 2016 was calculated using data envelopment analysis techniques. We performed a sensitivity analysis of the efficiency scores by running the DEA model several times using different combinations of input variables. At last, applying the Tobit regression, factors explaining the inefficiencies of hospitals were determined. Data analysis was done by STATA 12 and SPSS 16 software. Significance level of all the tests was set at .05. Results: In the first stage, 10 input variables and 10 output variables necessary from the mangers' point of view were identified to test efficiency. In the second stage, the mean of hospital efficiency was ascending from 2012 to 2015, and then it descending after 2015. According to the results of sensitivity analysis, despite the variability of technical efficiency during the study period (p<0.0001), the difference between the mean performance scores among different scenarios was not significant (p=0.066). Based on the third stage results, the average length of stay (Beta=-1.60E-12, p=0.030) and educational status (Beta=-2.89E+00, p=0.001) had a significant negative effect on hospitals' efficiency. Conclusion: The study results indicated that the efficiency changes during the years investigated were significant among Tehran public hospitals. The optimal use of inputs to produce hospital services should be on the agenda of health managers and policymakers.

Identification of the most appropriate variables for measuring the efficiency of Iranian public hospitals: Using Delphi technique.

CONTEXT: Selecting variables is a fundamental step in evaluating comparative efficiency because the results of measuring efficiency depend on the used variables. AIMS: The aim of this study is to provide a comprehensive set of input and output variables for measuring efficiency with an emphasis on application in general hospitals in Iran. MATERIALS AND METHODS: This study comprised a literature review followed by a Delphi survey process. After extracting the variables from the literature review in order to reach consensus on them and identify the native variables, the researchers used the Delphi technique in three rounds. Thirty Iranian hospital managers, in Alborz, Saveh, Qazvin, Qom, and Hamadan universities, participated in this study. For analysis, the interquartile range (IQR) and median were used. IQR was used to assess the agreement of Delphi panel members. RESULTS: After literature review, nine indicators were identified as input variables and 11 indicators were identified as output variables. After the proposed changes by Delphi members, 24 input variables and 24 output variables were identified to measure hospital efficacy. Finally, ten variables were selected as inputs and ten variables were selected as outputs to measure the performance of public hospitals in Iran by using the consensus of the members in the Delphi panel. CONCLUSIONS: This study proposes a framework for selecting the most appropriate variables for measuring the hospital efficiency with an emphasis on nonparametric methods. Choosing variables to measure hospital efficiency requires infrastructure such as an intelligent information system.