Predicting Primary Care Physician Burnout From Electronic Health Record Use Measures.

OBJECTIVE: To evaluate the ability of routinely collected electronic health record (EHR) use measures to predict clinical work units at increased risk of burnout and potentially most in need of targeted interventions. METHODS: In this observational study of primary care physicians, we compiled clinical workload and EHR efficiency measures, then linked these measures to 2 years of well-being surveys (using the Stanford Professional Fulfillment Index) conducted from April 1, 2019, through October 16, 2020. Physicians were grouped into training and confirmation data sets to develop predictive models for burnout. We used gradient boosting classifier and other prediction modeling algorithms to quantify the predictive performance by the area under the receiver operating characteristics curve (AUC). RESULTS: Of 278 invited physicians from across 60 clinics, 233 (84%) completed 396 surveys. Physicians were 67% women with a median age category of 45 to 49 years. Aggregate burnout score was in the high range (≥3.325/10) on 111 of 396 (28%) surveys. Gradient boosting classifier of EHR use measures to predict burnout achieved an AUC of 0.59 (95% CI, 0.48 to 0.77) and an area under the precision-recall curve of 0.29 (95% CI, 0.20 to 0.66). Other models' confirmation set AUCs ranged from 0.56 (random forest) to 0.66 (penalized linear regression followed by dichotomization). Among the most predictive features were physician age, team member contributions to notes, and orders placed with user-defined preferences. Clinic-level aggregate measures identified the top quartile of clinics with 56% sensitivity and 85% specificity. CONCLUSION: In a sample of primary care physicians, routinely collected EHR use measures demonstrated limited ability to predict individual burnout and moderate ability to identify high-risk clinics.

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.

Large language models for preventing medication direction errors in online pharmacies.

Errors in pharmacy medication directions, such as incorrect instructions for dosage or frequency, can increase patient safety risk substantially by raising the chances of adverse drug events. This study explores how integrating domain knowledge with large language models (LLMs)-capable of sophisticated text interpretation and generation-can reduce these errors. We introduce MEDIC (medication direction copilot), a system that emulates the reasoning of pharmacists by prioritizing precise communication of core clinical components of a prescription, such as dosage and frequency. It fine-tunes a first-generation LLM using 1,000 expert-annotated and augmented directions from Amazon Pharmacy to extract the core components and assembles them into complete directions using pharmacy logic and safety guardrails. We compared MEDIC against two LLM-based benchmarks: one leveraging 1.5 million medication directions and the other using state-of-the-art LLMs. On 1,200 expert-reviewed prescriptions, the two benchmarks respectively recorded 1.51 (confidence interval (CI) 1.03, 2.31) and 4.38 (CI 3.13, 6.64) times more near-miss events-errors caught and corrected before reaching the patient-than MEDIC. Additionally, we tested MEDIC by deploying within the production system of an online pharmacy, and during this experimental period, it reduced near-miss events by 33% (CI 26%, 40%). This study shows that LLMs, with domain expertise and safeguards, improve the accuracy and efficiency of pharmacy operations.

Prediction of the burden of road traffic injuries in Iran by 2030: Prevalence, death, and disability-adjusted life years.

PURPOSE: Road traffic accidents pose a global challenge with substantial human and economic costs globally. Iran experiences a high incidence of road traffic injuries, leading to a significant burden on society. This study aims to predict the future burden of road traffic injuries in Iran until 2030, providing valuable insights for policy-making and interventions to improve road safety and reduce the associated human and economic costs. METHODS: This analytical study utilized time series models, specifically autoregressive integrated moving average (ARIMA) and artificial neural networks (ANNs), to predict the burden of road traffic accidents by analyzing past data to identify patterns and trends in Iran until 2030. The required data related to prevalence, death, and disability-adjusted life years (DALYs) rates were collected from the Institute for Health Metrics and Evaluation database and analyzed using R software and relevant modeling and statistical analysis packages. RESULTS: Both prediction models, ARIMA and ANNs indicate that the prevalence rates (per 100,000) of all road traffic injuries, except for motorcyclist road injuries which have an almost flat trend, remaining at around 430, increase by 2030. Based on estimations of both models, the rates of death and DALYs due to motor vehicle and pedestrian road traffic injuries decrease. For motor vehicle road injuries, estimated trends decrease to approximately 520 DALYs and 10 deaths. Also, for pedestrian road injuries these rates reached approximately 300 DALYs and 6 deaths, according to the models. For cyclists and other road traffic injuries, the predicted DALY rates by the ANN model increase to almost 50 and 8, while predictions conducted by the ARIMA model show a static trend, remaining at 40 and approximately 6.5. Moreover, these rates for the prediction of death rate by the ANN model increased to 0.6 and 0.1, while predictions conducted by the ARIMA model show a static trend, remaining at 0.43 and 0.07. According to the ANN model, the predicted rates of DALY and death for motorcyclists decrease to 100 and approximately 2.7, respectively. On the other hand, predictions made by the ARIMA model show a static trend, with rates remaining at 200 and approximately 3.2, respectively. CONCLUSION: The prevalence of road traffic injuries is predicted to increase, while the death and DALY rates of road traffic injuries show different patterns. Effective intervention programs and safety measures are necessary to prevent and reduce road traffic accidents. Different interventions should be designed and implemented specifically for different groups of pedestrians, cyclists, motorcyclists, and motor vehicle drivers.

Vaccination and its impact on healthcare utilization in two groups of vaccinated and unvaccinated patients with COVID-19: A cross-sectional study in Iran between 2021 and 2022.

Background and Aims: One of the main responsibilities of health systems impacted by the global Coronavirus disease 2019 (COVID-19) pandemic, where the first case was discovered in Wuhan, China, in December 2019, is the provision of medical services. The current study looked into the impact of vaccination on the utilization of services provided to COVID-19 patients. Methods: This study was conducted in Iran between 2021 and 2022, utilizing a cross-sectional research design. The research team collected data on the utilization of provided services and the number of COVID-19 vaccines administered to 1000 patients in Iran through a random sampling approach. The data were analyzed with statistical methods, including the mean difference test, and multiple linear regression. Results: Regression estimates show that after controlling for confounding variables like age, type of admission, and comorbidities, vaccination reduces the utilization of healthcare services in the general majority of services. The study's results reveal a fall in COVID-19 patients' utilization of services, specifically in patients administered two or three doses of the vaccine. However, the reduction is not statistically significant. Regression models are in contrast to univariate analysis findings that vaccination increases the mean utilization of healthcare services for COVID-19 patients in general. Comorbidities are a crucial factor in determining the utilization of diagnostic and treatment services for COVID-19 patients. Conclusion: Full COVID-19 vaccination and other implementations, including investing in public health, cooperating globally, and vaccinating high-risk groups for future pandemics, are essential as a critical response to this pandemic as they reduce healthcare service utilization to alleviate the burden on healthcare systems and allocate resources more efficiently.

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.

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.

What is the role of institutional quality in health outcomes? A panel data analysis on 158 countries from 2001-2020.

Our study investigated the impact of institutional quality on health system outcomes, utilizing worldwide governance indicators and analyzing data from 158 countries between 2001 and 2020. We employed Principal Component Analysis (PCA) to create a composite index of institutional quality and conducted various tests to select the appropriate econometric model. The role of institutional quality, along with other variables, in health outcomes was estimated using fixed effects and generalized method of moments (GMM) models. High-income and low-income countries were analyzed separately. The results of our study revealed that institutional quality, as measured by Control of Corruption, Voice and Accountability, Political Stability, Rule of Law, Regulatory Quality, and Government Effectiveness, had a negative impact on infant mortality rates and a positive impact on life expectancy. Similarly, variables such as GDP, mean years of schooling, total health expenditure, and urbanization rate showed a negative association with infant mortality rates and a positive association with life expectancy. Conversely, the logarithm of CO2 emissions exhibited a positive effect on infant mortality rates and a negative effect on life expectancy. These findings highlight the crucial role of institutional quality in determining health outcomes. Improving institutional quality contributes to the development of democratic and meritocratic systems, infrastructure enhancement, efficient tax and subsidy systems, optimal budget allocation, improved public education, and enhanced access to primary healthcare services. The influence of institutional quality is particularly significant in high-income countries compared to low-income countries. In conclusion, our study emphasizes the importance of institutional quality in shaping health system outcomes. Enhancing institutional quality is essential for the overall advancement of healthcare systems, encompassing governance, infrastructure, education, and access to healthcare services. It is crucial to prioritize efforts to improve institutional quality, especially in high-income countries, to achieve better health outcomes for populations worldwide.

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.

Contributions of avoidable mortality to the sex gap in life expectancy and life disparity in Iran.

BACKGROUND: Public health policies and healthcare quality play a pivotal role on the health outcome level and disparities across sociodemographic groups. However, there is little evidence on their role on disparities in life expectancy (LE) and life disparity (LD) in low and middle income countries. The present study aimed to assess the contributions of avoidable mortality, as a measure of inter-sectoral public health policies and healthcare quality, into the sex gap in LE (SGLE) and LD (SGLD) in Iran. METHODS: Latest available data of death causes, according to the ICD codes, for Iran was obtained from the WHO mortality database for the period 2015-2016. An upper age limit of 75 years was applied to define avoidable causes of death. LD was measured as the average years of life lost at birth. The SGLE and SGLD (both females minus males) were decomposed by age and cause of death using a continuous-change model. RESULTS: Females, on average, outlived males for 3.8 years (80.0 vs. 76.2 years) with 1.9 lower life years lost (12.6 vs. 14.4 years). Avoidable causes accounted for 2.5 (67%) and 1.5 (79%) years of the SGLE and SGLD, respectively. Among avoidable causes, injury-related deaths followed by ischaemic heart disease had the greatest contributions to both SGLE and SGLD. Across age groups, the age groups 55-59 and 60-64 accounted for the greatest contributions of avoidable causes to SGLE (0.3 years each), while age groups 20-24 and 55-59 had the greatest contributions to SGLD (0.15 years each). Lower mortality rates for females than males in age groups 50-74 years accounted for about half of the SGLE, while age groups 20-29 and 50-64 years accounted for around half of SGLD. CONCLUSION: More than two third of the SGLE and SGLD in Iran were attributed to the avoidable mortality, particularly preventable causes. Our results suggest the need for public health policies targeting injuries in young males as well as lifestyle risk factors including smoking in middle aged males in Iran.

Pharmacies' income and its effective factors in Iran: A cross-sectional study.

Purpose: Financial assessment of pharmacies and the factors affecting it is an important issue in health system and pharmaceutical industry. The present study aimed to analyze the revenue of pharmacies in Iran and the factors affecting it. Methods: In the present study revenue data of all active pharmacies in Shiraz in 2018 (n = 298) were gathered using a checklist. Descriptive statistics, mean difference test, correlation, and regression analysis were performed for statistical evaluation. Heteroskedasticity and multicollinearity also were checked. Stata 15 was used for statistical analysis. Results: Average monthly income of the pharmacies was $82,879 USD (SD = 30,635). The monthly revenue of 24 h pharmacies was about $6560 higher than that of the daily pharmacies. The pharmacies founded by non-pharmacists made about $44,038 more than others, and the pharmacies located on main streets earned over $84,247 more than the ones located on side streets. Besides, the pharmacies inside or near hospitals, clinics, or physician buildings made more money than others. Correlation analysis also showed that the pharmacies' working years, the number of adjacent pharmacies, the number of OTC prescriptions, and the number of staff working at the cosmetics counters had a positive relationship with the pharmacies' income. Conclusions: Final findings indicated that 24 h pharmacies, pharmacies located on main streets, the ones located in hospitals or private clinics and physician buildings, pharmacies with more OTC prescriptions, and the ones with a larger number of employees in the cosmetics departments had higher monthly revenues.

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.

Forecasting blood demand for different blood groups in Shiraz using auto regressive integrated moving average (ARIMA) and artificial neural network (ANN) and a hybrid approaches.

Providing fresh blood to keep people in need of blood alive, has always been a main issues of health systems. Right policy-making in this area requires accurate forecasting of blood demand. The current study aimed at predicting demand for different blood groups in Shiraz using Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN) and a hybrid approaches. In the current time series analysis, monthly data of the Shiraz hospitals and medical centers demand for 8 blood groups during 2012-2019 were gathered from Shiraz branch of Iranian Blood Transfusion Organization. ARIMA, ANN and a hybrid model of them was used for prediction. To validate and comprise ARIMA and ANN models, Mean Square Error (MSE) and Mean Absolute Error (MAE) criteria were used. Finally, ARIMA, ANN and hybrid model estimates were compared to actual data for the last 12 months. R3.6.3 were used for statistical analysis. Based on the MSE and MAE of models, ARIMA had the best prediction for demand of all blood groups except O+ and O-. Moreover, for most blood groups, ARIMA had closer prediction to actual data. The demand for four blood groups (mostly negative groups) was increasing and the demand for other four blood groups (mostly positive ones) was decreasing. All three approaches including ARIMA, ANN and the hybrid of them predicted an almost downward trend for the total blood demand. Differences in the performance of various models could be due to the reasons such as different forecast horizons, daily/month/annual data, different sample sizes, types of demand variables and the transformation applied on them, and finally different blood demand behaviors in communities. Advances in surgical techniques, fetal screening, reduction of accidents leading to heavy bleeding, and the modified pattern of blood request for surgeries appeared to have been effective in reducing the demand trend in the current study. However, a longer time period would certainly provide more accurate estimates.

Evaluation of the Costs and Outcomes of COVID-19 Therapeutic Regimens in Hospitalized Patients in Shiraz.

COVID-19 patients in critical conditions are hospitalized and treated with various protocols including antiviral drugs, which have been updated repeatedly. This study was aimed to analyze the demographics, costs, and outcomes of drug regimens in COVID-19 patients hospitalized in "Ali Asghar" hospital, affiliated with Shiraz University of Medical Sciences, from March 2019 to December 2020 as a retrospective study, approved by the ethics committee of Shiraz University of Medical Sciences (IR.SUMS.REC.1399.1003) on Dec. 28, 2020. Using hospital information system (HIS) data, 2174 patients receiving favipiravir, remdesivir, interferon-ß, and Kaletra® were analyzed. Descriptive, univariate, and regression analyses were used. The costs and consequences of different drug regimens were significantly different (P value < 0.05); the highest and lowest costs belonged to remdesivir and Kaletra®, respectively. The highest and lowest mean length of stay and mortality were related to remdesivir and favipiravir, respectively. Mortality did not differ significantly with various regimens. Length of stay was significantly shorter with favipiravir and Kaletra® than interferon-ß. Remdesivir had significantly the highest cost. Age presented a significantly positive relationship with mortality and length of stay. Besides, ICU admission significantly increased mortality, length of stay, and costs. Underlying diseases and low blood oxygen saturation contributed to mortality. COVID-19 correlation with age and underlying diseases is accordant with the published data. Given the highest costs and broad usage of remdesivir, besides controversies regarding its outcomes and side effects, a stricter evaluation of remdesivir benefits seems essential. Totally, COVID-19 therapeutic protocols should be selected carefully to optimize costs and outcomes.

The Effect of Prospective Payment Systems on Health Care Providers' Behavior: A Case Study of Global Surgeries Payment System in Iran.

Background: Global payment system is a kind of case-based payment system which pays for 60 commonly surgical operations by the average cost for each specified surgery case in Iran. The aim of the study was to determine the effect of this payment system on the number of services provided for each global surgical case versus fee-for-service (FFS) for the same operation. Methods: This is a retrospective study based on data from a large referral teaching hospital in Iran in the period of 2012-2015. Information related to 46 surgeries was performed which both global and FFS documents were gathered (N=7672). Statistical analysis was done on variables including Length of stay (LOS), Blood test (BT), Radiology (RA) and a mixed variable named VC (visit and consult number). Data were analyzed by a zero-inflated negative binomial regression model using STATA 11. Results: Descriptive analysis showed the mean of each service was significantly (p<0.001) higher in the FFS document's group rather than the global payment group. Regression estimates showed the amounts of each service including LOS, BT, RA and VC were significantly (p<0.001) higher in FFS surgery than global documents for the 15 selected surgery. LOS and BT have shown a significantly higher amount in 100% of surgeries for FFS above global document. Same as for Radiology test and VC variables, there were significantly higher amounts in 93% of surgeries for FFS above global hospital documents. Conclusion: The findings can reinforce the presence of a relationship between providing more clinical services in FFS document form and providers' incentives to adjust profits against their Costs. The significantly higher service provision in FFS documents can be controlled with a prospective global payment mechanism.

Inequality in the distribution of Covid-19 vaccine: a systematic review.

BACKGROUND: The equality in the distribution of vaccines between and within countries along with follow sanitation tips and observe social distance, are effective strategies to rid the world of COVID-19 pandemic. Inequality in the distribution of COVID-19 vaccine, in addition to causing inequity to the population health, has a significant impact on the process of economic recovery. METHODS: All published original papers on the inequality of Covid-19 vaccine distribution and the factors affecting it were searched in PubMed, Web of Science, Scopus and ProQuest databases between December 2020 to 30 May 2022. Selection of articles, extraction of their data and qualitative assessment (by STROBE) were performed by two researchers separately. Data graphing form was used to extract detailed data from each study and then, the collected data were classified. RESULTS: A total of 4623 articles were evaluated. After removing duplicates and screening the title, abstract and full text of articles, 22 articles were selected and entered into the study. Fifteen (68.17%) studies were conducted in the United States, three (13.64%) in Europe, three (13.64%) in Asia and one (6.66%) in Oceania. Factors affecting the inequality in the distribution of COVID-19 vaccine were classified into macro and micro levels determinants. CONCLUSION: Macro determinants of inequality in the Covid-19 vaccine distribution were consisted of economic (stability and country's economic status, Gross Domestic Product (GDP) per capita, financial support and human development index), infrastructure and health system (appropriate information system, functional cold chains in vaccine transport, transport infrastructure, medical and non-medical facilities per capita, healthcare access and quality), legal and politics (vaccination allocation rules, health policies, political ideology and racial bias), and epidemiologic and demographic factors (Covid-19 incidence and deaths rate, life expectancy, vulnerability to Covid-19, working in medical setting, comorbidities, social vulnerability, incarceration and education index). Moreover, micro/ individual level factors were included in economic (household's income, home ownership, employment, poverty, access to healthy food and residency in the deprived areas) and demographic and social characteristics (sex, age, race, ethnic, religion, disability, location (urban/rural) and insurance coverage).

Influencing factors on the tendency of general practitioners to join in urban family physician program: a cross-sectional survey on Iranian physicians.

BACKGROUND: Urban family physician program (UFPP) is initiated as pilot by policy makers as a main reform in future of primary health care in Iran. Despite an ongoing pilot implementation of this program from 2012, it remains a main question about providing sufficient number of general practitioners (GPs). This study aimed to investigate the factors which affect GPs' decision to join in the UFPP. METHODS: In this national cross-sectional study a sample of 666 GPs, using convenience sampling, filled a self-report questionnaire. The multivariate logistic regression was applied to explore the demographic, practice and views determinants of the tendency of GPs to join in the UFPP. RESULTS: More than half of GPs (58.6%) participated in the study had a positive tendency to join in the UFPP. Older GPs (adjusted OR = 3.72; 95%CI 1.05-13.09), working in public sector (adjusted OR = 2.26; 95%CI 1.43-3.58), lower income level (adjusted OR = 6.69; 95%CI 2.95-15.16), higher economic expectations (adjusted OR = 2.08; 95%CI 1.19-3.63), and higher satisfaction from medicine profession (adjusted OR = 2.00; 95%CI 1.14-3.51) were the main factors which increased the GPs tendency to enter in UFPP. CONCLUSIONS: Decision for joining in the program is mainly affected by GPs' economic status. This clarifies that if the program can make them closer to their target income, they would be more likely to decide for joining in the program.

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.

Cost-effectiveness analysis of hearing screening program for primary school children in southern Iran, Shiraz.

BACKGROUND: Hearing loss is the second most common chronic disease, the diagnosis and treatment of which can be faster through screening. In addition, early interventions will save significant costs for the education and health systems. Therefore, the present study aimed to evaluate the cost-effectiveness of hearing screening for primary school children in Shiraz. METHODS: This cross-sectional economic evaluation of cost-effectiveness was conducted from the perspective of the health system. The study population comprised all seven-year-old children participating in the screening program in Shiraz. The present study dealt only with direct costs. The expected costs and outcomes, as well as the ICER index were estimated using the decision tree model. The study outcomes included averted disability-adjusted life years (DALY) and true identification of hearing loss cases. The robustness of the results was evaluated using the one-way sensitivity analysis. The TreeAge 2020 and Excel 2016 software were also used to analyze the collected data. RESULTS: The hearing screening data obtained during 6 years (2015-2020) showed that every year, an average of 22,853 children in Shiraz were examined for hearing, of which 260 were true positive (%1.1). The costs of screening and lack of screening were estimated at $30.32 Purchasing Power Parity (PPP) and $13.75 PPP per child, respectively. The averted DALY due to performing hearing screening was estimated at 7 years for each child. The ICER was positive and equal to $ 0.06 PPP for the identified cases and $ 2.37 PPP per averted DALY. The sensitivity analysis confirmed the robustness of the results. CONCLUSIONS: According to the results, although hearing screening for primary school children had more costs and effectiveness, it was considered cost-effective. Therefore, universal screening with high quality and accuracy is recommended.

Health literacy and health promoting behaviors among inpatient women during COVID-19 pandemic.

BACKGROUND: One of the leading health indicators during the COVID-19 crisis is health literacy and health-promoting behaviors. The present study aimed to investigate health literacy and health-promoting behaviors among women hospitalized during the COVID-19 pandemic in the southern part of Iran in 2020. METHODS: This descriptive-analytical study encompassed 465 women hospitalized and treated in none teaching hospitals affiliated with the Shiraz University of Medical Sciences. Data collection tools were the Health Literacy for Iranian Adults (HELIA) and Health Promoting Lifestyle Profile II (HPLP-II). The collected data were analyzed using descriptive and inferential statistical methods. RESULTS: The mean scores of the participants' "health literacy" and "health-promoting behaviors" were 64.41 ± 11.31 and 112.23 ± 16.09, respectively, indicating the poor level of health literacy and the average level of health-promoting behaviors. Moreover, there was a significant direct correlation between health literacy and health-promoting behaviors (P < 0.001, r = 0.471). Furthermore, all health literacy dimensions of comprehension (P < 0.001), accessibility (P < 0.001), reading skills (P < 0.001), evaluation (P = 0.002), and decision making and behavior (P = 0.003) were detected as the predictors of health-promoting behaviors. Further, statistically significant relationships were noticed between the mean score of health literacy with age (r = - 0.327, P = 0.007), level of education (F = 3.119, P = 0.002), and place of residence (t = 2.416, P = 0.004) and between health-promoting behaviors with level of education (F = 3.341, P = 0.001) and marital status (F = 2.868, P = 0.02). CONCLUSION: According to the findings, health policymakers should adopt national measures for educational planning to promote health literacy and support health-promoting behaviors to encourage women to adopt a healthy lifestyle.