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Background: Due to the legal necessity of changing the approach of universities from traditional budgeting into the operational budgeting system, it should be noted that this method of budgeting is associated with challenges. The aim of this study was to evaluate the feasibility and prioritization of operational budgeting dimensions in a military medical university.
Materials & Methods: This descriptive-analytical and cross-sectional study was conducted in 2020 in two stages. In the first stage, 68 managers, staff and experts of the deputy for Planning and Finance of a Military Medical Sciences university were enrolled by census method. In the second stage, 10 experts were purposefully included in the study. Data collection tool was two valid and reliable questionnaires. Data were analyzed using t-test and SPSS software in the first stage and using AHP approach and Expert Choice software in the second stage.
Results: The average overall score and the score for each of the dimensions of ability, authority and acceptance of operational budgeting was 2.3, 2.39, 2.38 and 2.31, respectively which was at an undesirable level (P< 0.05). Also, dimensions of the ability with a weight of 0.547, acceptance with a weight of 0.244 and authority with a weight of 0.209 had the highest weight and importance in the implementation of the operational budgeting system, respectively.
Conclusion: Based on the results, it is necessary to pay attention to the three main dimensions of ability, authority and acceptance in implementing operational budgeting in the study population.

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Background: The outlook for hospital care is changing rapidly. Supply and demand stimuli in the health service system are changing dramatically. The health department of the Social Security Administration has also been challenged by the growing number of patients. This study was conducted to help this organization with the aim of designing a conceptual causal model of the interaction between supply and demand of health care.
Materials and Methods: This research is a qualitative study that was conducted in 2020. It presented a conceptual model in two steps in the first step, semi-structured interviews were used to extract important factors in the supply and demand of health services in hospitals. In the second step, the system simulation approach was used and the feedback relationships between the patient's routes to the hospital and the provision of medical services were presented.
Results: According to the study hypothesis, the prevalence of disease and budget allocation as an indicator of medical need and expected medical demand, positively affect the number of visits to hospitals of the Social Security Organization. Accordingly, four sub-models of patient flow, health care budget, treatment staff (physician, nurse) and hospital capacity were extracted.
Conclusion: Medical budgets allocated to hospitals to improve medical facilities and increase the number of staff, have created positive expectations among social security insured regarding the use of hospital services. Paying attention to providing sufficient manpower (doctor, nurse) and bed capacity with the budget which is spent for this service are the indicators of improving the quality of services.

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Background: Covid-19 pandemic peak put additional strains on healthcare system. In this crisis, the resilience of nursing staff is critical. This study aimed to investigate the relationship between burnout and resilience in frontline nursing staff working in high-risk areas during the outbreak of Covid-19 pandemic.
Materials and Methods: The present study is a Descriptive-analytical survey, and the target group is Iranian nurses. According to the Ministry of Health statistics, 125369 people are participated in this study. information is collected from 384 people by cluster distribution using questionnaire. The statistical analysis in this study is performed by SPSS and SMART-PLS software
Results: According to the study, all the collected information is normal. Based on factor analysis, there is an inverse significant relationship between resilience and burnout, and also, the sense of success has a significant effect on resilience as part of burnout.
Conclusion: In order to increase the resilience of nursing staff in such conditions, it is necessary to pay more attention to the factors affecting their burnout and plan to minimize it. Developing educational programs and adding diversity in service delivery might be useful to enhance personal feelings and also reduce burnout.

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Background and purpose: Today, hospital care, relying on the health record system, has received more attention than before. Considering the diversity of data in these systems, the design of standard conceptual and logical models by service providers will play an important role in their success. Therefore, this research was conducted with the aim of designing a logical data model of the hospital information management system for athletes based on international standards.
Materials and methods: The design of the logical model of the hospital information system for athletes in Iran based on the main entities and components of the system was done after comparing the selected countries, the initial review of the needs of the beneficiaries, the dataset validated by the experts and the validation of the conceptual model, and the diagrams were painted. The meeting was held with the presence of experts to validate the proposed logical model. The proposed amendments were discussed and carried out in the meeting, the collective agreement on the presented logical model and the validity of the model were confirmed.
Results: login activities, password change, examination appointment booking, athlete information registration, examination registration, test results registration, vaccination information registration activity, health reminder registration,  and health information registration were determined as the main diagrams of this system.
Conclusion: Based on the findings, it seems that access to sports medicine information is the key point, and a person can see and receive health needs related to him in a patient-centered treatment.

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Background and Objectives
In recent years, medicine supply chain management has become more significant, especially after the Covid-19 pandemic. The most important issue is supply chain cost control. If the drug inventory is not properly managed, it will lead to issues such as the lack of inventory of certain drugs, provision of excess inventory, increased costs, and, finally, patient dissatisfaction.
Materials and Methods
In this study, an attempt has been made to predict and manage the pharmaceutical needs of hospitals using an efficient deep-learning algorithm. The drug consumption data for ten years of Besat General Hospital in Hamedan are extracted from the HIS database. As a case study, the accuracy of the predictive model is evaluated, especially for cefazolin. We use a deep model to analyze the medical time-series data efficiently. This model consists of a Long Short-Term Memory network, which can sufficiently recognize the change history in time-series prediction applications. The proposed model with many adjustable parameters in the deep architecture will bring good performance to overcome the complexities of the learning problem.
Results
Using the deep learning method can increase robustness by reducing the effects of complexity and uncertainty in medical data. The average forecasting error for the proposed method is 0.043, and the measured values for RMSE, MAE, and R2  are 0.335, 0.260, and 0.851, respectively.
Conclusion
A comprehensive comparison between some other predictive methods and the implemented model shows the outperformance of the proposed approach. Additionally, the evaluation results indicate the efficiency of the proposed approach.

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Background and objective: As a critical factor for hospital effectiveness, agility uncovers the way such organizations react to internal and external changes. From this perspective, the present study was to design an agent-based model to simulate organizational agility development in the hospitals of Ardabil Province, Iran, in view of the effective factors.
Materials & Methods: Utilizing an exploratory, mixed-methods research design, this study was performed in accordance with inductive-deductive reasoning. For this purpose, the samples included 10 theoretical and experimental experts, selected by purposive sampling of the non-probability type. As well, the data collection tools were interviews and questionnaires. During the qualitative phase, the main factors affecting organizational agility were initially isolated using thematic analysis. Afterward, the given factors were prioritized with the fuzzy Delphi method in the quantitative phase. Ultimately, the model for organizational agility development was simulated through the agent-based approach.
Results: With reference to the study results, 50 primary codes, 15 sub-themes, and 5 main themes were identified, and then “influence in management” was acknowledged as the most significant one shaping organizational agility. Besides, the simulation outputs demonstrated that the proposed model could provide the right estimate of the future of organizational agility development in the hospitals of Ardabil Province, Iran.
Conclusion: Along with the study results, hospital managers are suggested to reflect on the effective factors identified here to better fulfill organizational agility development.

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Background: Cancer is often stigmatized in many societies and this has unfortunate consequences for sufferers. The aim of this research was to know the factors related to the social stigma of cancer.
Materials and Methods: The research method was correlation-analytical, and the sampling method was multi-stage cluster. Data were collected using CSI and CAM standard questionnaires.The statistical population included three categories of ordinary citizens, medical staff, and companions of patients in Tehran; Using Cochran's formula, the sample size was 384, 201, 384 people, respectively. In order to fit the model and measure the relationships between the variables, the method of structural equation modeling was used in the form of AMOS software.
Findings: Goodness of fit indices (chi-square/df=2.851, Rmsea=0.08, Cfi=0.945) all indicated the appropriate fit of the model. Except for the variable of inequality in treatment, other independent variables had a significant relationship with stigma. The r² explanatory coefficient showed that the variables of habitus, optimism, cancer awareness, religiosity, social support, and social capital together predicted 48% of stigma changes. Habitus and social support with standard coefficients (beta) of 0.48 and -0.28 had the highest and lowest contribution in explaining stigma, respectively. Based on the mean difference test, the amount of stigma among ordinary people was more than the other two groups.
Conclusion: Awareness of different aspects of cancer disease (such as symptoms, causative factors), removing false stereotypes about cancer (such as cancer means death), constant communication with cancer patients, and receiving the necessary social support from various sources, were the most important tools necessary to reduce the stigma of cancer.

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Background and purpose: A fearless organization fosters psychological safety, ensuring that every member feels secure to express concerns, ask questions, or share mistakes without fear of humiliation, ridicule, or punishment. This research aims to introduce the Fearless Organization Model in Iran's healthcare sector, with a focus on the Ta’amin Ejtemaie hospitals.
Methods: This research employs a mixed-methods approach. In the qualitative phase, methods such as meta-synthesis, expert Delphi, and Shannon’s entropy were used to identify the components of a fearless organization. The quantitative phase involved structural equation modeling (using surveys distributed among the staff of Ta’amin Ejtemaie hospitals in Tehran) to validate the research model.
Results: The Fearless Organization Model consists of two main dimensions: “Behavioral” and “Structural.” The behavioral dimension includes "managers' behavioral components" and "employees' behavioral components." The structural dimension includes "organizational components," "human resource components," and "environmental components." Key characteristics of a fearless organization include: creating psychological security, openness, transparency, accountability, humble listening, quick employee feedback, learning from mistakes, encouraging knowledge sharing, avoiding silence, and promoting open communication. Effective response systems and coherent organizational structures for extracting ideas and concerns, as well as fostering a supportive culture, are essential.
Conclusion: The findings of this study emphasize the importance of addressing both behavioral and structural dimensions in creating a fearless organization. However, the behavioral dimension plays a more significant role than the structural one. Within the behavioral dimensions, "employee behavior" is the most crucial factor. Managers should focus on cultivating behaviors that promote security and openness within the organization. This research can serve as a foundation for further studies on the drivers and barriers to establishing fearless organizations in different contexts.

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Background and purpose: The integration of digital technologies—computer-based systems, devices, and methods—is transforming organizational activities within the healthcare sector. However, research on the adoption of these technologies in healthcare remains limited, with a predominant focus on structural rather than behavioral factors. As the successful implementation of technology ultimately depends on the workforce, behavioral aspects play a decisive role. Therefore, this study aims to identify the principal behavioral barriers to the adoption of digital technologies in the healthcare sector.
Methods: This applied research utilized a three-stage survey methodology. The stages included: (1) identifying the most significant behavioral barriers to digital technology adoption through a literature review and expert opinions; (2) developing a hierarchical model of these barriers using Interpretive Structural Modeling (ISM); and (3) testing the hypotheses derived from the model with a sample of 302 healthcare professionals.
Results: The ISM model identified a hierarchy of six key behavioral barriers: lack of digital literacy, low perceived value, high perceived risk, negative attitude, resistance to change, and ultimately, non-adoption of digital technology. Based on this model, six research hypotheses were formulated. Regression analysis was conducted to test these hypotheses, and the results indicated that all six were statistically supported.
Conclusion: The findings establish that a lack of digital literacy is the most fundamental barrier to digital technology adoption in the healthcare sector. To address this primary obstacle, the study recommends targeted interventions, such as conducting national assessments of digital literacy levels among healthcare staff and implementing tailored training programs to enhance their technological competencies.

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Background and purpose: Early Maladaptive Schemas (EMSs) are pervasive cognitive patterns that can detrimentally affect the well-being of individuals with chronic illnesses. This study aimed to investigate the structural relationship between EMSs and Health-Related Quality of Life (HRQoL) in cancer patients, with a specific focus on the mediating role of health literacy.
Methods: This descriptive-analytical study utilized a correlational design based on Structural Equation Modeling (SEM). The statistical population comprised all cancer patients aged 20 to 60 years referring to private oncology centers in [City Name] in 2025. A total of 665 participants were recruited using convenience sampling. Data were collected using the Young Schema Questionnaire (YSQ), the Health Literacy for Iranian Adults (HELIA) questionnaire, and the Health-Related Quality of Life questionnaire. Data analysis was performed using SPSS (v.25) and AMOS (v.24) software, with the significance level set at 0.05.
Results: The path analysis revealed that EMSs had a significant direct negative effect on both health literacy (β =-0.85, P< 0.001) and HRQoL (β= -0.56, P<0.001). Conversely, health literacy showed a significant positive effect on HRQoL (β=0.51, P<0.001). Furthermore, health literacy significantly mediated the relationship between EMSs and HRQoL (β=0.26,P<0.001). The goodness-of-fit indices confirmed the model's optimal fit (X²/Df = 3.94, GFI = 0.913, IFI = 0.903, CFI = 0.901, RMSEA = 0.067)
Conclusion: The findings suggest that Early Maladaptive Schemas significantly compromise the quality of life in cancer patients. However, health literacy acts as a protective buffer, mediating this negative impact. Therefore, interventions aimed at enhancing health literacy could be an effective strategy to mitigate the adverse effects of maladaptive schemas and improve the HRQoL of cancer patients.