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Showing 48 results for Model
Mohammad Reza Mehregan, Shahrokh Yousefzadeh, Ali Reza Hatam Siahkal Mahalle,
Volume 15, Issue 2 (5-2021)
Volume 15, Issue 2 (5-2021)
Abstract
Background and Aim: The overall goal of the medical department is to develop and manage an efficient and effective supply chain. Intrinsic instability and unpredictability of treatment needs to require a flexible supply chain. Agility reflects the hospital's response to environmental changes, and agile hospitals are able to provide appropriate services to the patients. Hospital supply chain management agility needs to find the main aspects affecting the relationship and communication between them and to analyze the dimensions together. The purpose of this study was interpretive-structural modeling and analysis of dimensions of agile hospital supply chain management.
Materials and Methods: The research design combined descriptive - survey exploratory approach to the future. The population study were doctors, nurses and staff at the University of Medical Sciences. The Delphi technique was used to determine the dimensions of agility and the interpretive-structural modeling approach was used for analysis and modeling. Mick Mac software was used to analyze the dimensions of agility.
Results: The final model of agile hospital supply chain management with 16 dimensions had 8 levels, which was at the highest level of cost reduction and at the lowest level of organizational leadership commitment. The results indicate that leadership commitment is the foundation of supply chain agility in the hospital. Knowledge management variable had low impact and effectiveness and was known as a secondary leverage variable. The results showed that most agile supply chain management aspects of the main causes of complex communication and interaction, and the importance of agility in the hospital of the show.
Conclusion: The analysis and interpretation of functional from the aspect of Impact and Influence of agility dimensions in hospital environment Showed that, Dimensions of strategic planning, human resource development and staff skills training, human resource management and employee satisfaction, process management, process integration and organizational transformation, flexibility, organizational communication development and information management integration, service quality management and continuous improvement, acceptance of new technology and new ideas, speed of service, patient understand and satisfaction, monitor, find best responds demand and market sensitivity in the strategic area are located and They cause model instability and With high impact and high influence, They play an important role in the agility of hospital supply chain management.
Materials and Methods: The research design combined descriptive - survey exploratory approach to the future. The population study were doctors, nurses and staff at the University of Medical Sciences. The Delphi technique was used to determine the dimensions of agility and the interpretive-structural modeling approach was used for analysis and modeling. Mick Mac software was used to analyze the dimensions of agility.
Results: The final model of agile hospital supply chain management with 16 dimensions had 8 levels, which was at the highest level of cost reduction and at the lowest level of organizational leadership commitment. The results indicate that leadership commitment is the foundation of supply chain agility in the hospital. Knowledge management variable had low impact and effectiveness and was known as a secondary leverage variable. The results showed that most agile supply chain management aspects of the main causes of complex communication and interaction, and the importance of agility in the hospital of the show.
Conclusion: The analysis and interpretation of functional from the aspect of Impact and Influence of agility dimensions in hospital environment Showed that, Dimensions of strategic planning, human resource development and staff skills training, human resource management and employee satisfaction, process management, process integration and organizational transformation, flexibility, organizational communication development and information management integration, service quality management and continuous improvement, acceptance of new technology and new ideas, speed of service, patient understand and satisfaction, monitor, find best responds demand and market sensitivity in the strategic area are located and They cause model instability and With high impact and high influence, They play an important role in the agility of hospital supply chain management.
Haleh Mohammadiha, Gholam Reza Memarzadeh, Parham Azimi,
Volume 15, Issue 3 (8-2021)
Volume 15, Issue 3 (8-2021)
Abstract
Background and Aim: Health systems have played an important role in improving and increasing life expectancy. However, there is a large gap between health systems’ potential and their current performance, most of which relate to governance issues. The purpose of this study is to provide a model for improving the governance of the country's health system.
Materials and Methods: The present study is applied-developmental in terms of purpose. After reviewing the theoretical foundations and previous research, the governance strategies of the health system were identified. Then, using Fuzzy Delphi Method (FDM) and surveying 13 academic and executive experts who were purposefully selected, the research model was designed. Finally, in order to validate the model, 169 managers and specialists of health system departments in Tehran were interviewed with a questionnaire, and the data were analyzed using structural equation modeling (SEM) and SmartPLS software. At this stage, the sampling method was available and the sample size was calculated by Cochran's method.
Results: According to the research findings, in order to promote health governance, 10 main strategies and 58 sub-strategies should be considered. Identified strategies include strategic orientation, optimal financial resource management, stakeholder partnership development, knowledge resource development, administrative health promotion, technical knowledge development, value and ethical orientation, executive and operational platform development, Service delivery capacity management and Balanced and integrated stewardship. Also, the coefficient of determination for the outcome variable is 0.549 and the intensity of the effect of intervening/ facilitating and contextual factors on governance strategies is equal to 0.610 and 0.533, respectively.
Conclusion: The results showed that the governance of the health system is a multifaceted and complex phenomenon and in order to improve it, a set of strategies must be implemented. In addition, it is suggested that according to the issues and threats facing the health system, a roadmap and a long-term plan should be developed in order to move towards the governance model proposed in the present study.
Materials and Methods: The present study is applied-developmental in terms of purpose. After reviewing the theoretical foundations and previous research, the governance strategies of the health system were identified. Then, using Fuzzy Delphi Method (FDM) and surveying 13 academic and executive experts who were purposefully selected, the research model was designed. Finally, in order to validate the model, 169 managers and specialists of health system departments in Tehran were interviewed with a questionnaire, and the data were analyzed using structural equation modeling (SEM) and SmartPLS software. At this stage, the sampling method was available and the sample size was calculated by Cochran's method.
Results: According to the research findings, in order to promote health governance, 10 main strategies and 58 sub-strategies should be considered. Identified strategies include strategic orientation, optimal financial resource management, stakeholder partnership development, knowledge resource development, administrative health promotion, technical knowledge development, value and ethical orientation, executive and operational platform development, Service delivery capacity management and Balanced and integrated stewardship. Also, the coefficient of determination for the outcome variable is 0.549 and the intensity of the effect of intervening/ facilitating and contextual factors on governance strategies is equal to 0.610 and 0.533, respectively.
Conclusion: The results showed that the governance of the health system is a multifaceted and complex phenomenon and in order to improve it, a set of strategies must be implemented. In addition, it is suggested that according to the issues and threats facing the health system, a roadmap and a long-term plan should be developed in order to move towards the governance model proposed in the present study.
Moslem Soleymanpor, Mohamad Taghi Amini, Yazdan Shirmohammadi, Ali Shahnazari,
Volume 15, Issue 5 (1-2022)
Volume 15, Issue 5 (1-2022)
Abstract
Background and Aim: With the global expansion of Covid 19, the tourism industry has faced one of its biggest operational, commercial and financial crises, and most of the source-destination interactions have been suspended and have changed the view of the host community and their interactions with tourists. The purpose of this study is to provide a model for tourism development during the Covid 19 crisis and beyond.
Materials and Methods: This study was conducted using a combined (qualitative-quantitative) research approach. First, in a qualitative method with the data foundation approach, interviews with academic experts and managers and activists of the tourism industry in East and West Azerbaijan Provinces, and using purposeful and theoretical sampling, 18 people were selected to the point of information saturation. Semi-structured in-depth interviews were used to collect data. Data extracted from interviews were encoded by open, axial and selective coding. Then, to fit and test the obtained model in the second step (quantitative part), the method of structural equation modeling and confirmatory factor analysis were used.
Results: The final model consists of a total of 66 concepts extracted from the interviews, in the form of 14 categories and contextual categories, causal conditions, interventional conditions, strategies and finally, consequences and results of tourism entrepreneurship in pandemic crises and all of them affect this model. Based on the results of combined reliability, extracted variance, model determination coefficient and goodness-of-fit index, the drawn model in the field of path analysis has good experimental-theoretical assumptions and has a very good fit. Based on the obtained path coefficients, it can be concluded that the intervention conditions had the most and the causal conditions had the least impact on the strategic model of the tourism industry in pandemic crises.
Conclusion: Results indicate that strategies such as virtual tourism development, crisis management in the tourism industry, the development of domestic tourism by emphasizing the observance of health protocols and focusing on the development of tourism infrastructure, leads to the realization of consequences such as the maintenance and prosperity of tourism businesses, strengthening the tourism industry and creating a new tourism market for the post-corona era.
Materials and Methods: This study was conducted using a combined (qualitative-quantitative) research approach. First, in a qualitative method with the data foundation approach, interviews with academic experts and managers and activists of the tourism industry in East and West Azerbaijan Provinces, and using purposeful and theoretical sampling, 18 people were selected to the point of information saturation. Semi-structured in-depth interviews were used to collect data. Data extracted from interviews were encoded by open, axial and selective coding. Then, to fit and test the obtained model in the second step (quantitative part), the method of structural equation modeling and confirmatory factor analysis were used.
Results: The final model consists of a total of 66 concepts extracted from the interviews, in the form of 14 categories and contextual categories, causal conditions, interventional conditions, strategies and finally, consequences and results of tourism entrepreneurship in pandemic crises and all of them affect this model. Based on the results of combined reliability, extracted variance, model determination coefficient and goodness-of-fit index, the drawn model in the field of path analysis has good experimental-theoretical assumptions and has a very good fit. Based on the obtained path coefficients, it can be concluded that the intervention conditions had the most and the causal conditions had the least impact on the strategic model of the tourism industry in pandemic crises.
Conclusion: Results indicate that strategies such as virtual tourism development, crisis management in the tourism industry, the development of domestic tourism by emphasizing the observance of health protocols and focusing on the development of tourism infrastructure, leads to the realization of consequences such as the maintenance and prosperity of tourism businesses, strengthening the tourism industry and creating a new tourism market for the post-corona era.
Seyed Amir Reza Nejat, Mahmoud Bigler, Seyedeh Bahareh Kashian,
Volume 16, Issue 1 (3-2022)
Volume 16, Issue 1 (3-2022)
Abstract
Background and Aim: Intellectual capital, with its basic knowledge nature, is an intangible, strategic, unique and competitive advantage resource. The purpose of this study is to investigate the current state of intellectual capital maturity in the field of management and planning of Tehran university of medical sciences.
Materials and Methods: This research was applied in terms of purpose and with a quantitative approach in 1400 and a questionnaire was used to collect information. The statistical population is the middle and basic managers of the Vice Chancellor for Resource Management Development and Planning. Using Morgan table, 57 people were randomly selected and analyzed by t-test and non-parametric statistical tests using SPSS software. Has been. The content validity of the questionnaire was obtained by examining the research background and obtaining the opinions of experts, and the Cronbach’s alpha coefficient was used to assess the reliability, the value of which was 0.874.
Results: Statistical tests show that the five levels of intellectual capital management maturity follow a nonlinear pattern and the level of realization of the initial level characteristics, ie lack of intellectual capital structure, is higher than acceptable, but the statistical test of other levels of maturity Included; Managed, defined, quantified and optimal management is not significant at the significance level of 0.05.
Conclusion: The current situation of intellectual capital in the study population indicates that management is unaware of the importance of intellectual capital and no action has been taken to implement the knowledge capital management process. Although there is a lot of necessary infrastructure in the Vice Chancellor, however, insufficient understanding of the capabilities of intellectual capital management as a strategic resource is evident in this research. To reach the defined level and the next levels, the organization needs to identify, activate and direct the intangible source and then quantify, standardize and manage quantitatively and analyze the strengths and weaknesses and finally the continuous improvement of processes and Focus on innovation.
Materials and Methods: This research was applied in terms of purpose and with a quantitative approach in 1400 and a questionnaire was used to collect information. The statistical population is the middle and basic managers of the Vice Chancellor for Resource Management Development and Planning. Using Morgan table, 57 people were randomly selected and analyzed by t-test and non-parametric statistical tests using SPSS software. Has been. The content validity of the questionnaire was obtained by examining the research background and obtaining the opinions of experts, and the Cronbach’s alpha coefficient was used to assess the reliability, the value of which was 0.874.
Results: Statistical tests show that the five levels of intellectual capital management maturity follow a nonlinear pattern and the level of realization of the initial level characteristics, ie lack of intellectual capital structure, is higher than acceptable, but the statistical test of other levels of maturity Included; Managed, defined, quantified and optimal management is not significant at the significance level of 0.05.
Conclusion: The current situation of intellectual capital in the study population indicates that management is unaware of the importance of intellectual capital and no action has been taken to implement the knowledge capital management process. Although there is a lot of necessary infrastructure in the Vice Chancellor, however, insufficient understanding of the capabilities of intellectual capital management as a strategic resource is evident in this research. To reach the defined level and the next levels, the organization needs to identify, activate and direct the intangible source and then quantify, standardize and manage quantitatively and analyze the strengths and weaknesses and finally the continuous improvement of processes and Focus on innovation.
Mostafa Shanbehzadeh, Hadi Kazemi-Arpanahi, Raoof Nopour,
Volume 16, Issue 2 (5-2022)
Volume 16, Issue 2 (5-2022)
Abstract
Background and Aim: Breast cancer is one of the most common and aggressive malignancies in women. Timely diagnosis of breast cancer plays an important role in preventing the progression of this disease, timely treatment measures, and aftermath reducing the mortality rate of these patients. Machine learning has the potential ability to diagnose diseases quickly and cost-effectively. This study aims to design a CDSS based on the rules extracted from the decision tree algorithm with the best performance to diagnose breast cancer in a timely and effective manner.
Materials and Methods: The data of 597 suspected people with breast cancer (255 patients and 342 healthy people) were retrospectively extracted from the electronic database of Ayatollah Taleghani Hospital in Abadan city with 24 characteristics, mainly pertained to lifestyle and medical histories. After selecting the most important variables by using the Chi-square Pearson and one-way analysis of variance (P<0.05), the performance of selected data mining algorithms including RF, J-48, DS, RT and XG -Boost was evaluated for breast cancer diagnosis in Weka 3.4 software. Finally, the breast cancer diagnostic system was designed based on the best model and through C# programming language and Dot Net Framework V3.5.4.
Results: Fourteen variables including personal history of breast cancer, breast sampling, and chest X-ray, high blood pressure, increased LDL blood cholesterol, presence of mass in upper inner quadrant of the breast, hormone therapy with estrogen, hormone therapy with Estrogen-progesterone, family history of breast cancer, age, history of other cancers, waist-to-hip ratio and fruit and vegetable consumption showed a significant relationship with the output class at the P<0.05. Based on the results of the performance evaluation of selected algorithms, the RF model with sensitivity, specificity, accuracy, and F- measure equal to 0.97, 0.99, 0.98, 0.974, respectively, AUC=0.936 had higher performance than other selected algorithms and was suggested as the best model for breast cancer diagnosis.
Conclusion: It seems that using modifiable variables such as lifestyle and reproductive-hormonal characteristics as input to the RF algorithm to design the CDSS, can detect breast cancer cases with optimal accuracy. In addition, the proposed system can be effectively adapted in real clinical environments for quick and effective disease diagnosis.
Materials and Methods: The data of 597 suspected people with breast cancer (255 patients and 342 healthy people) were retrospectively extracted from the electronic database of Ayatollah Taleghani Hospital in Abadan city with 24 characteristics, mainly pertained to lifestyle and medical histories. After selecting the most important variables by using the Chi-square Pearson and one-way analysis of variance (P<0.05), the performance of selected data mining algorithms including RF, J-48, DS, RT and XG -Boost was evaluated for breast cancer diagnosis in Weka 3.4 software. Finally, the breast cancer diagnostic system was designed based on the best model and through C# programming language and Dot Net Framework V3.5.4.
Results: Fourteen variables including personal history of breast cancer, breast sampling, and chest X-ray, high blood pressure, increased LDL blood cholesterol, presence of mass in upper inner quadrant of the breast, hormone therapy with estrogen, hormone therapy with Estrogen-progesterone, family history of breast cancer, age, history of other cancers, waist-to-hip ratio and fruit and vegetable consumption showed a significant relationship with the output class at the P<0.05. Based on the results of the performance evaluation of selected algorithms, the RF model with sensitivity, specificity, accuracy, and F- measure equal to 0.97, 0.99, 0.98, 0.974, respectively, AUC=0.936 had higher performance than other selected algorithms and was suggested as the best model for breast cancer diagnosis.
Conclusion: It seems that using modifiable variables such as lifestyle and reproductive-hormonal characteristics as input to the RF algorithm to design the CDSS, can detect breast cancer cases with optimal accuracy. In addition, the proposed system can be effectively adapted in real clinical environments for quick and effective disease diagnosis.
Sakineh Motayerzadeh, Rahim Tahmasebi, Behrooz Kavehie, Azita Noroozi,
Volume 16, Issue 3 (8-2022)
Volume 16, Issue 3 (8-2022)
Abstract
Background and Aim: Vaccination is one of the most effective preventive measures to control of infectious diseases. To create effective interventions for the acceptance of the COVID-19 vaccine, it is important to identify the factors that affect the vaccine acceptance. The aim of this study was to determine the predictive power of the Extended Parallel Process Model (EPPM) for acceptance of Covid-19 vaccine.
Materials and Methods: In this cross-sectional study, 1455 people over 18 years old covered in health centers living in Bushehr province in cities of Bushehr, Genaveh, Tangestan, and Asaluyeh in 2021 were selected by convenience method. Data collection was online by using questionnaire included three sections comprised of demographic factors, questionnaire related to model constructs, and self-administered questionnaire related to acceptance of Covid-19 vaccine. Data were analyzed using chi-square, two independent sample T-test and logistic regression; in SPSS software.
Results: Out of 1455 participants, 1067 persons (73.3%) had been vaccinated. The results showed that men (P=0.006), people with higher education (P=0.001), government employees (P=0.001), single people (P=0.01), people with history of specific disease (P=0.05), individuals with a history of Covid-19 positive test (P=0.001) and their family (P=0.03) were more than other vaccine recipients. Perceived severity, response efficacy and perceived self-efficacy were predictors of vaccine acceptance. Predictive variables and constructs explained 43.8% of changes in vaccine acceptance. Among the participants in the study, 1366 (93.9%) were in the fear control process, in which the highest defense response has been avoided.
Conclusion: In order to increase the acceptance of the vaccine, the efficacy and effectiveness of the vaccine and the severity of the complications of the disease should be emphasized. Therefore, public health campaigns aimed at increasing vaccine acceptance should provide a high level of transparency about the safety and effectiveness of vaccines to the community.
Materials and Methods: In this cross-sectional study, 1455 people over 18 years old covered in health centers living in Bushehr province in cities of Bushehr, Genaveh, Tangestan, and Asaluyeh in 2021 were selected by convenience method. Data collection was online by using questionnaire included three sections comprised of demographic factors, questionnaire related to model constructs, and self-administered questionnaire related to acceptance of Covid-19 vaccine. Data were analyzed using chi-square, two independent sample T-test and logistic regression; in SPSS software.
Results: Out of 1455 participants, 1067 persons (73.3%) had been vaccinated. The results showed that men (P=0.006), people with higher education (P=0.001), government employees (P=0.001), single people (P=0.01), people with history of specific disease (P=0.05), individuals with a history of Covid-19 positive test (P=0.001) and their family (P=0.03) were more than other vaccine recipients. Perceived severity, response efficacy and perceived self-efficacy were predictors of vaccine acceptance. Predictive variables and constructs explained 43.8% of changes in vaccine acceptance. Among the participants in the study, 1366 (93.9%) were in the fear control process, in which the highest defense response has been avoided.
Conclusion: In order to increase the acceptance of the vaccine, the efficacy and effectiveness of the vaccine and the severity of the complications of the disease should be emphasized. Therefore, public health campaigns aimed at increasing vaccine acceptance should provide a high level of transparency about the safety and effectiveness of vaccines to the community.
Negin Saldar, Rahim Shahbazi,
Volume 17, Issue 2 (5-2023)
Volume 17, Issue 2 (5-2023)
Abstract
Background and Aim: Health literacy plays a role in “reducing human casualties and financial costs” in a society. Emotional intelligence and media literacy also contribute to people’s success in life. Therefore, the aim of this study was to investigate the mediating role of media literacy in the relationship between emotional intelligence and health literacy among graduate students of Azarbaijan Shahid Madani University.
Materials and Methods: This research is based on the nature and general characteristics, quantitative; Based on the purpose, it is applied and based on the research method and data collection method, is a descriptive correlation based on structural equation model. The statistical population was graduate students of Azarbaijan Shahid Madani University in 2020 (2218 students). The statistical sample of the research is 327 people who were selected by stratified random sampling method. To collect data, Emotional Intelligence Questionnaire (1998), Montazeri et al. Health Literacy Questionnaire (2014) and media literacy questionnaire were used. The reliability of the questionnaires was obtained using Cronbach’s alpha coefficient of 0.91, 0.84 and 0.79, respectively. The collected data were analyzed using descriptive statistics and inferential statistics (structural equation model) using SPSS and LISREL software.
Results: The findings showed the mean of emotional intelligence, health literacy and media literacy of graduate students of Azarbaijan Shahid Madani University is 3.10, 3.47 and 3.58, respectively. Also, the results showed a significant relationship between emotional intelligence and students’ health literacy. According to the findings, there is a significant relationship between emotional intelligence with media literacy, and media literacy with health literacy. Also, the media literacy variable plays a mediating role in the relationship between emotional intelligence and health literacy (coefficient) of 0.58 units. The results of the structural equation model test also showed that the proposed conceptual model fits the relationship between emotional intelligence, health literacy and students’ media literacy.
Conclusion: Media literacy can not only directly affect students’ health literacy, but also has a mediating role between emotional intelligence and health literacy. Due to the effect of emotional intelligence on students’ health and media literacy, it is recommended that the necessary planning to be done in graduate education and to strengthen emotional intelligence.
Materials and Methods: This research is based on the nature and general characteristics, quantitative; Based on the purpose, it is applied and based on the research method and data collection method, is a descriptive correlation based on structural equation model. The statistical population was graduate students of Azarbaijan Shahid Madani University in 2020 (2218 students). The statistical sample of the research is 327 people who were selected by stratified random sampling method. To collect data, Emotional Intelligence Questionnaire (1998), Montazeri et al. Health Literacy Questionnaire (2014) and media literacy questionnaire were used. The reliability of the questionnaires was obtained using Cronbach’s alpha coefficient of 0.91, 0.84 and 0.79, respectively. The collected data were analyzed using descriptive statistics and inferential statistics (structural equation model) using SPSS and LISREL software.
Results: The findings showed the mean of emotional intelligence, health literacy and media literacy of graduate students of Azarbaijan Shahid Madani University is 3.10, 3.47 and 3.58, respectively. Also, the results showed a significant relationship between emotional intelligence and students’ health literacy. According to the findings, there is a significant relationship between emotional intelligence with media literacy, and media literacy with health literacy. Also, the media literacy variable plays a mediating role in the relationship between emotional intelligence and health literacy (coefficient) of 0.58 units. The results of the structural equation model test also showed that the proposed conceptual model fits the relationship between emotional intelligence, health literacy and students’ media literacy.
Conclusion: Media literacy can not only directly affect students’ health literacy, but also has a mediating role between emotional intelligence and health literacy. Due to the effect of emotional intelligence on students’ health and media literacy, it is recommended that the necessary planning to be done in graduate education and to strengthen emotional intelligence.
Kourosh Abbasiyan, Mohammad Alimoradnori, Mohammad Bagher Karami,
Volume 18, Issue 2 (5-2024)
Volume 18, Issue 2 (5-2024)
Abstract
Background and Aim: Managers, as the main decision-makers in facing various internal and external organizational problems, play a significant and determining role in the success or even failure of an organization. If competent and experienced managers are positioned at the top of organizations, the success of these organizations in achieving their goals will be guaranteed and an organization can achieve maximum efficiency with minimal resources. The aim of this study was to design a model of managerial competencies for hospital managers.
Materials and Methods: This qualitative research was conducted from year 2020 to 2022. After reviewing studies related to the topic, the extracted competencies were given to 19 experts consisted of relevant academic faculty members and managers with experience in the healthcare system and hospitals. Eventually, a managerial competency model was formulated through the use of the Delphi method and expert panel discussions. Collected data were analyzed in Excel software.
Results: The developed model in this research for the concept of hospital managers’ competencies includes 33 managerial competencies of hospital managers in four main management functions (planning, organizing, leadership and control) and managerial roles, which starts from literature review and performing two Delphi steps and implementing two expert panel plans. In the competency of hospital managers model, the planning dimension consists 4 components, organizing consists 4 components, leadership consists 12 components, control consists 4 components, and managerial roles consists 9 components. Strategic thinking, which is a subset of planning, has the highest weight (0.495) and highest rank among other components, and continuous improvement, which is a subset of managerial roles, has the lowest weight (0.033) and lowest rank among other components.
Conclusion: This study proposes an exclusive and comprehensive model, utilizing practical techniques as a suitable solution for evaluating the managerial competencies of hospital managers. The proposed framework in this study can serve as a standard performance assessment tool for evaluating managers.
Materials and Methods: This qualitative research was conducted from year 2020 to 2022. After reviewing studies related to the topic, the extracted competencies were given to 19 experts consisted of relevant academic faculty members and managers with experience in the healthcare system and hospitals. Eventually, a managerial competency model was formulated through the use of the Delphi method and expert panel discussions. Collected data were analyzed in Excel software.
Results: The developed model in this research for the concept of hospital managers’ competencies includes 33 managerial competencies of hospital managers in four main management functions (planning, organizing, leadership and control) and managerial roles, which starts from literature review and performing two Delphi steps and implementing two expert panel plans. In the competency of hospital managers model, the planning dimension consists 4 components, organizing consists 4 components, leadership consists 12 components, control consists 4 components, and managerial roles consists 9 components. Strategic thinking, which is a subset of planning, has the highest weight (0.495) and highest rank among other components, and continuous improvement, which is a subset of managerial roles, has the lowest weight (0.033) and lowest rank among other components.
Conclusion: This study proposes an exclusive and comprehensive model, utilizing practical techniques as a suitable solution for evaluating the managerial competencies of hospital managers. The proposed framework in this study can serve as a standard performance assessment tool for evaluating managers.
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