Background Primary healthcare with the right structure is the base for any highly efficient healthcare system to achieve better health outcomes at the lowest cost. Challenges of this system, including structural weaknesses, are one of the factors of inefficiency. Therefore, the purpose of this study was to identify challenges of the organizational structure of county health network in Iran. Methods An exploratory qualitative face-to-face semi-structured interviews were carried out with 21 key informants including experts and managers in Ahvaz-Iran. Purposive sampling method with maximum diversity were used. Interviews were recorded digitally and transcribed verbatim. Interview transcripts were analyzed based on a thematic analysis approach via NVivo-11. Results In analysis of the interviews, after removing the duplicate codes and merging similar items, finally 6 main challenges and 56 sub-themes were obtained. The themes of structural challenges included formalization, complexity, centralization, culture, environment, and resources. Conclusions Based on the present situation, the challenges in the current organizational structure and a change in the goals and strategies of the healthcare system in Iran, the appropriate structure needs to be designed and implemented at different levels in accordance with the goals and strategies. The separation and independence of health centers management and hospitals (treatment) in the county can provide a basis for understanding the challenges to the provision of health services.

Background It is necessary to evaluate COVID-19 data on Knowledge, Attitudes and Practices (KAP) to confirm effective protective practice and to reduce risk in society. Hence, the study was carried out to determine KAP towards COVID-19 and the factors associated with knowledge and practices among patients with type 2 diabetes (T2D). Methods In this cross-sectional (descriptive-analytical) study, 357 patients with diabetes in Izeh participated in the study. The sampling method used was convenience sampling method. Data collection tool was a researcher-made questionnaire of demographic information and KAP of patients with T2D in relation to the new coronavirus. The validity and reliability of the research tool was confirmed using the content validity and test–retest. Data analysis was done in Stata.14.2 and Smartpls 3.2.8 using descriptive and analytical statistical tests. Results The mean score of participants' KAP towards Covid-19 was 74.22 (16.30), 72.88 (14.87), and 70.51 (19.70), respectively. The lowest and the highest score of the patients' knowledge was in the field of transmission (56.60 (20.96)) and care and prevention of the COVID-19 (88.58 (21.88)), respectively. Residence was the most important factor predicting the practice of diabetic patients with an explanatory coefficient ([SMD 1.08 (95% CI 0.85 to 1.30), P < 0.001] and R2 = 0.87%). Conclusion Despite the good level of KAP of people towards the COVID-19 disease, there were answers showing poor knowledge, incorrect beliefs and attitudes, and insufficient practice regarding different aspects of the COVID-19 in some cases in our study. Residence was a strong predictor of type 2 diabetes mellitus (T2DM) patients’ practice in terms of protective behaviors against Covid-19. Hence, educational needs evaluation based on residence is recommended, especially in rural T2DM patients.

Fair distribution of physicians is a determining factor in health system policies. The present study aimed to investigate the equity in the distribution of general and specialist physicians in the affiliated cities of Ahvaz Jundishapur University of Medical Sciences. This descriptive cross-sectional study was performed in 2019. Population data were collected through the Statistics Center of Iran and The number of physicians was collected through the relevant departments of the university and the organizations of the medical and planning system of Khuzestan province in 2019. Then, using ratio indices, Gini coefficient, and Lorenz curve, the status of physicians distribution was investigated. Excel software was used to analyze the data. Hendijan (0.5) and Haftkel (0.49) had the highest ratio of general practitioners to the population and Mahshahr port (0.11) had the lowest. The highest ratio of specialized physicians to the population was in Karun with 0.75 and the lowest ratio was in Bavi (0.04). The Gini coefficient of distribution of general practitioners, specialists, and all the physicians in the study population was 0.16, 0.31, and 0.19, respectively. The Lorenz curve showed the distribution of physicians and confirmed the Gini coefficients. The ratio of general practitioners and specialists to the population in the study population is low, but the distribution of general practitioners and all the physicians are fair and specialist physicians are unfair. Policymakers and university administrators should pay special attention to increasing the ratio of general practitioners and specialists to the population and the fair distribution of specialist physicians.