مجله بیمه سلامت ایران
سال ششم شماره 2 (پیاپی 21، تابستان 1402)

Equitable financing is an important goal of health systems and protecting the financial risks of health care. Also, equitable financing of health is important both for improving the state of health systems and for achieving universal health coverage (UHC). In this study, with an overview has introduced the indicators of justice in health and the results of the indicators in this field have been examined in the country. The search for articles in the present study is of a review type that was conducted through search engines and databases within the range of 2002-2022. In order to identify the advantages and disadvantages of indicators showing justice in health financing, including out-of-pocket payment indicators, catastrophic health expenditures index, Kakwani index, concentration index and fair financial contribution index, a review of studies was used and the limitations and advantages of each index were extracted and compared. The results of this study showed that in terms of health equity index, the index of back-breaking health costs had the highest frequency in the studies. Each of the indicators had advantages and problems. Also, according to the numerous studies on the calculation of the health justice index, the existence of a health watchdog is necessary to monitor these indicators.

Artificial Intelligence Chatbots (AIC), nowadays, are one of the most important topics in natural language processing which is able to communicate with humans using natural language. The purpose of using AIC is to facilitate user interaction with services, products or companies. The purpose of this study is to investigate the applications of AIC in Iran’s health system generally and Iran Health Insurance Organization in particular and to provide services to people in this way, including the investigation of AIC and its need in the provision of health care, the study of the significant aspects of the workflow of AIC for healthcare, the AIC features in this field, and identifying the significant applications and limitations of artificial intelligence chatbot for providing healthcare services. Purveying AIC services to individuals, such as insurance credit information as well as offering contracting party centers are some of benefits of AIC application in Iran Health Insurance Organization.

Performance evaluation is the basis of many decisions and plans that can lead to the success of the organization, and efficiency is considered a very suitable criterion for evaluating the performance of companies and organizations. Based on this, the purpose of this research is to investigate the performance of agencies and counter offices of the contracting party of the Health Insurance Organization by measuring efficiency using the technique of data envelopment analysis.

In this study, the data of the representative offices and counter branches of the contracting government of Iran Health Insurance Organization in Ilam province, Iran in the third quarter of 2021 were analyzed. For data analysis, non-radial data envelopment analysis model was used, in which evaluation indicators were selected using confirmatory factor analysis method and using Smart PLS software. The SBM model was used to determine the efficiency, and finally, the Super-SBM method was used to rank the efficient units.

The research showed that among the examined units, during the evaluation period, 4 units had efficient performance and 12 ineffective units, among the efficient units, the unit with the best performance was determined and among the inefficient units, the unit with the worst performance was determined.

In the evaluation period, the number of inefficient units was more compared to efficient units. It is recommended to measure the efficiency and productivity of the counter offices and branches of health insurance contracting parties in different cities of Iran, especially the provincial centers, on an annual basis, so that by providing practical solutions, the situation of the agencies and offices can be improved. It is also necessary for them to be fully aware of their expectations and to be more responsive to their clients.

Coronavirus disease 2019 or COVID-19, which is also called acute respiratory disease NCAV-2019 or commonly called corona, is a respiratory disease caused by acute respiratory syndrome coronavirus-2. Forecasting the number of new cases and deaths today can be a useful step in predicting the costs and facilities needed in the future. This study aims to model and predict new cases and deaths efficiently in the future.

In this article, 9 forecasting techniques were tested on the data of COVID-19 of Mehriz city, Iran as a case study from 2020/02/26 to 2021/12/19 and using the evaluation criteria of mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of the models were compared.

For cumulative cases of hospitalization, ARIMA, Exponential, Holt-Winters, and STL models performed better and autoregressive neural networks, Theta, and KNN regression showed poor performance. Also, for cumulative mortality cases, KNN regression, Exponential and Theta models have better performance in predicting cumulative mortality cases, and autoregressive neural networks, ARIMA, and cubic spline smoothing showed poor performance.

the best model according to the mentioned evaluation criteria for predicting cumulative cases of hospitalization of COVID-19 is STL model and for cumulative cases of death is the KNN regression model. Also, the autoregressive neural network model has the worst performance among other models, both for hospitalization and death cases. Also, the important point is that the data should be updated in real-time.

The novel severe acute respiratory syndrome coronavirus 2 (COVID-19) pandemic has had drastic effects on global healthcare. This study aimed to ascertain changes in the volume of neurosurgical procedures carried out before, during, and after the COVID-19 pandemic in Isfahan city hospitals, Iran.

This retrospective cohort study was conducted at the three Hospitals of Isfahan. Data of the neurosurgical patients (both urgent and nonurgent) treated from the February in 2017 to 2022 were collected. Two groups were thus created (COVID-19 (2020-2022), pre-COVID-19 (2017-2X019) and Post-COVID (2022-2023).

We treated 30456 admissions under neurosurgery during the COVID-19 (2020-2022) compared with 42300 admissions in pre-COVID-19 (2017-2019). Pre-COVID-19, the median number of referrals was 46 per 24 hour. During COVID-19, this decreased to 33 per day. During the post-COVID era, there was an admission of 17,341 patients, which escalated to 37 cases within a 24-hour timeframe during the post-COVID period. A noteworthy disparity was evident in the overall count of admitted patients, the aggregate of surgical procedures executed, and the elective surgical procedures performed during the post-COVID phase when juxtaposed with the pre-COVID and the COVID-19 pandemic periods (P<0.05). Additionally, there was a marked contrast in spinal column issues between the post-COVID period and the pandemic period (P<0.05).

The capacity to safely treat patients requiring urgent or emergency neurosurgical care was maintained at COVID-19 pandemic. Moreover, following the conclusion of the pandemic, there was a decline in the number of surgical procedures in contrast to the pre-pandemic period.

Financing in the health system will be fair when the costs related to health care for households are distributed according to their ability to pay and not according to the risk of disease. The aim of the present study was to investigate the inequality situation in households’ out-of-pocket payments for oral and dental health care in the Ahvaz, Iran households.

The present study is a cross-sectional study in which 715 households living in Ahvaz city in 2022-2023 were studied with stratified-cluster sampling. The required data was collected through a questionnaire to calculate the reliability, the questionnaire was implemented on a group of 10 households in a seven-day period, and their correlation coefficient was 0.89. Stata and Excel software were used to analyze the data.

According to this study, the proportion of oral and dental health expenses from the income of households in quintiles 1 to 5 is 69.41, 45.29, 27.77, 25.38 and 17.7 percent, respectively. Also, the Gini coefficient is equal to 0.384, the concentration index is equal to 0.174, and the Kakwani index is equal to -0.21. Also, the average percentage of out-of-pocket payments for dental services was 93.62%.

The out-of-pocket payments share of income for dental care was higher in the poorest quintile and it can be said that there is a downward trend in financing through out-of-pocket payments for oral and dental care. Therefore, health managers and policymakers should reduce the severity of the downward in financing by expanding insurance coverage and protecting the poor against unwanted oral and dental health expenses.

What helps to improve the performance of the supply chain of hospital medical equipment is having a suitable model to evaluate your collection in line with strategic goals. The purpose of this research is to provide a performance evaluation model for the sustainable supply chain of hospital medical equipment.

This research is exploratory and survey. In this research, using existing literature and backgrounds as well as experts' opinions, effective elements (dimensions, components and indicators) on the performance of sustainable supply chain were identified; Then these elements were finalized using the Delphi method and asking for opinions from experts. The experts reached a consensus on 4 dimensions, 8 components and 54 indicators, that 8 indicators did not receive the necessary points in this review and were removed, and the rest were used to design the final model. Interpretive Structural Equations (ISM) method was used to investigate the relationships between dimensions and components.

The final performance evaluation model included 4 dimensions, 8 components and 54 indicators, which is used to evaluate the performance of the sustainable supply chain of hospital medical equipment from an internal and external perspective, and can be used with changes in other organizations. The obtained dimensions (views) include sustainability, key stakeholders, processes, and growth and learning. The components are economic-financial, integration, people capabilities, lean-agility, organizational culture, upstream/supply chain actors, social-environmental and downstream/customers.

The use of Balanced and Sustainable Score Card (BSSC) monitors and evaluates organizational goals in the supply chain of hospital equipment, and the extent to which goals are achieved is determined. The use of this model leads the organization towards balance and sustainability in the macro goals and will bring a guarantee to pay attention to various important aspects inside and around the organization.

Daroyar project was implemented with the aim of regulating fair and sustainable access of people to medicines and increasing insurance coverage. This study investigated the effect of the plan on the number of prescriptions and the cost of the health insurance organization.

This study is a cross-sectional retrospective study. The research community is the outpatient electronic prescription of drugs of Iranian health insurance organization in the second 6 months of 1400 and 1401. In this study, the number of drug prescriptions, the cost paid by the insurance organization, and the number of service-providing pharmacies were extracted from the prescription dashboards of the Health Insurance Organization's electronic system. Data analysis was done using Excel 2019 software.

The number of prescriptions increased by 71% and costs by 251% in 1401. The average cost increased by 105%, but the average number of prescriptions, excluding preferred currency, decreased by 12%. The preferred currency share of the total cost paid by the organization for electronic drug prescription was 57%. The highest cost paid by the organization was to Tehran province (13%). The amount of preferred currency has been increasing from October to March.

The Daroyar project has led to the improvement of people's access to pharmaceutical services. The decrease in the average net share of the organization per prescription is a sign of the coverage of cheap drugs. The significant share of the preferred currency indicates the success of the project in providing domestically produced drugs.