امیراشکان نصیری پور

The supply chain of hospital services is a relatively new and highly challenging field, and it is crucial for relevant officials to possess the necessary skills. The success in this domain relies on the characteristics of managers, their management practices, and their leadership style. This study aims to investigate the requirements of management and leadership in hospital services’ supply chain.

This study employed a two-stage mixed-methods approach carried out from 2018 to 2021. In the first stage, a qualitative study was conducted using purposive sampling and semi-structured in-depth interviews with 15 experts in various leadership positions. The data collected in this stage were analyzed using framework approach. Subsequently, the primary themes that emerged from the analysis were presented to 8 experts  in the form of a questionnaire. The experts' responses were then analyzed to determine the level of agreement on different topics using Delphi method, Kendall's coefficient of agreement, and the mean was compared through SPSS 21.

The experts identified transformationalism, planning capability, crisis management, and creativity as the most crucial factors. Furthermore, there was a high level of agreement regarding the influence of managers (4.62 ± 0.51), maintaining distance from mundane routines (4.50 ± 0.53), and attending to various incidents in hospital services supply chain (4.50 ± 0.53). Considering that Kendall Rank Correlation Coefficient (w) was 0.53 in the first round and 0.72 in the second round and was statistically significant, there was a strong consensus among the expert panel.

According to the results of the present study, it is necessary to pay serious attention to the change in management style and hospital services supply chain, there should be a special focus on the possibility of occurrence or impact of sudden accidents. Also, routine and ineffective actions should be eliminated and the managers and employees should be more creative to improve this chain. Transformational leaders should try to manage the hospital services supply chain by forming specialized teams and using the capabilities of employees with the reasonable use of financial resources and appropriate infrastructures, including information technology.

This study aimed to develop IoT-based machine learning algorithms care and improvement while detecting and predicting real-time epidemics.The target disease is COVID-19 due to its importance and epidemic.The research method is based on design science. The research approach is forward-looking, so the mechanism of disease transmission and its effective characteristics enable us to make predictions about the disease and thus design disease control strategies and health care.The research was carried out in a seven-step process. IoT features were extracted in the present study with experts' opinions. The features obtained in the experiment of two different algorithms, "k nearest neighbor" and "decision tree," were created on the data to determine the best model.After selecting the best depth validation of the model were performed by confusion matrix analysis.The results of running k-nearest neighborhood and Decision Tree algorithms for the prediction of COVID-19 indicated an accuracy of > 98%. Higher sensitivity (99%) was obtained in the Decision Tree algorithm, which is very important diagnosing COVID-19 and indicates the minimum number of false negatives in the test results.

 The issue of child health is considered one of the essential priorities of the health policy makers of countries around the world. Therefore, to reflect the results of implementing a comprehensive program on children's health, the present study assessed the effect of a new integrated care package for healthy children on children's health indicators. 

 This descriptive and analytical study was conducted cross-sectionally and comprehensively in the population of children under five years of age (during 1398-1400) in 1401. Data collection tools included information collection checklists based on research objectives. The data were calculated as percentages and amounts and analyzed with the Wilcoxon test and SPSS-26 software at an error level of less than 0.05.

Between the implementation of the healthy child program and the mortality rate of children under one-year-old (p=0.025), under five years mortality rate (p=0.002), 1-59 months mortality rate (p=0.008 p-value), developmental screening of children (p= 0.001), vaccination coverage (p=0.001) and child care coverage (p=0.005) a significant relationship was obtained, but with the infant mortality rate (p=0.317) and child's visit by a doctor (p=0.083) no significant association was observed.

 Implementing the new healthy child package reduces mortality indicators and increases care indicators and developmental screenings of children. Since health indicators are one of the most important criteria in evaluating the health of society, implementing the new child package is necessary to be healthy qualitatively and quantitatively.

The development of information technology and its use in the health system has taken many measures to protect and promote human health, however, the world still faces long-term threats and recurrence of infectious diseases. Understanding the dynamics of infectious diseases is important in controlling the disease because the network and the mode of impact of infectious diseases are very complex. The management of infectious diseases can also be considered as a complex social system due to the fact that has many complexities (such as dimensions, parameters, interactions, behaviors and rules), for this reason, the approach of the present study is a multifaceted understanding of the spread of infectious diseases. To design the present model, an intelligent system with a combination of mathematical, machine learning and epidemiological dimensions is proposed. The disease studied in this study, due to its importance and prevalence, is Covid 19. In this study, with the approach of complex systems and using the Internet of Things and machine learning methods, an algorithm was presented that uses environmental and individual variables to predict the probability of disease in an individual. Therefore, this research can improve the prevention of infectious diseases by filling some of the gaps in 3 sections: 1- Re-emergence of infectious diseases and the potential of IoT and AI, 2- Speed of dissemination and importance of real-time tracking, and 3- Budget and cost. The evaluation of the algorithm in this study was determined by two criteria of sensitivity and specificity. The results of the proposed algorithm for predicting Covid 19 disease showed an accuracy of more than 98%. Sensitivity above 98% was also obtained. Which is very important for the diagnosis of Covid disease 19 and shows the low number of false negatives in the test results. Therefore, the proposed model, combined with the Internet of Things and machine learning, can cause early diagnosis and prevent the spread of the Covid-19 disease with high specificity and sensitivity.

The purpose of this article is to review scientific research related to air pollution and deaths caused by the corona virus and the costs of premature death and Disability Adjusted Life Years.

The present research method is a review study. The statistical population of the research is all the studies conducted in international and national scientific databases based on the index (DALY) and its relationship with pollutant particles with an emphasis on the pollutant of suspended particles with a diameter of 2.5 microns (PM2.5), as well as the effect of air pollution on The COVID-19 virus and their Willingness to Pay (WTP) in Iran and the world. The research findings were analyzed using the coding technique based on the keywords of air pollution, Contingent Valuation, Disability Adjusted Life Years (DALY) and COVID-19.

survey of environmental disease studies shows the contribution of environmental risk factors including PM2.5, have been according to the DALY index because of death or disability. Also, the study of articles are mostly about statistical analyses on the measured concentrations of PM2.5 and infection and death data by COVID-19 in different countries.

The results of the studies show a strong and significant correlation between the concentration of PM2.5 pollutants and the rate of infection and death caused by the corona virus. which shows that by controlling the concentration of pollutants, the rate of infection and death caused by the corona virus can be reduced.

Due to increasing costs of the health sector and the inefficiency of the public sector, granting autonomy to hospitals was implemented in the independent hospital program.The aim of this study was to investigate the effect of establishing an independent hospital program on the performance indicators of pilot hospital in Qazvin.

The status of eight functional indicators of the pilot hospital was collected in the period of 2017-2020 before and after the establishment of the independent hospital program. Data were analyzed using paired t-test and Wilcoxon and interrupted time series at a significant level (p<0/05) and analyzed by SPSS24 STATA15 software.

The result of paired t-test and Wilcoxon-Neschein test shows that the establishment of an independent hospital program has had effect on the average active bed, active day bed and discharge number. Based on the analysis of the interrupted time series model, the average active bed with 55.96 units, active day bed with 1576.51 units, occupied day with 3357.14 units, percentage of bed occupancy with 40.63 unit and the number of surgeries with 736.60 units had an increasing average and the number of discharges with 47.92 units and average stay with 1.42 units, shows a decreasing average.

The present study does not show a significant change in performance indicators. It is suggested that managers and policy makers of the health system, if they wish to expand the plan, conduct comprehensive and detailed studies in this field.

The development of information technology and its use in the health system have undertaken numerous measures for the protection and promotion of human health. However, long-term threats and the recurrence of infectious diseases are still the challenges in the world. Management of infectious diseases is of paramount importance in the global health system and is very complicated. Therefore, the aim of this research is designing a model to predict the covid-19 using artificial intelligence, which will ultimately be useful for rapid detection and control of Covid-19.

To design a proposed model to analyze the spread of infectious diseases, an intelligent system is presented by combining mathematical dimensions, machine learning, and epidemiology. In this research, the target disease is COVID-19 due to its importance and epidemic. Despite extensive research on this disease, each study focused on a specific area due to its extensive dimension, and no detailed study is available on the main aspects of the disease. The research method is interpretive and exploratory in terms of paradigm and strategy, respectively, and is classified as descriptive-prescriptive in terms of implementation. The research was carried out in a seven-step process.

The results of the systematic review showed the rapid growth of documents since 2015, which can indicate the application of various fields of information technology such as the Internet of Things and machine learning in the field of public health and prevention of infectious diseases.In the algorithm, K values from 1 to 20 neighborhoods were calculated and the best accuracy was obtained at K equal to 2. Therefore, the accuracy of the algorithm is higher than 98% to predict the disease of Covid-19. After calculating the accuracy, the analysis of the confusion matrix showed that in K equal to 2, the sensitivity is 99% and the specificity is 92%.

A comparison of algorithm results shows that in addition to accuracy, sensitivity and specificity obtained for algorithm are higher than traditional methods of diagnosing infectious diseases. Also, due to not having unnecessary complex features that only increase the model implementation time, the algorithm runs in a few minutes, and therefore the detection speed is completely acceptable. High sensitivity (99%) was obtained in the DT algorithm, which is very important for the diagnosis of COVID-19 and indicates the minimum number of false negatives in the test results. Therefore, the proposed algorithm is practical for the purpose of identifying the maximum number of people infected with Covid-19.

Organizations' problems today cannot be solved with yesterday's solutions, and the environmental conditions have become so complex, dynamic and uncertain that organizations can no longer guarantee their long-term survival without innovation. The aim of the current research is to investigate the effect of team innovation on nurses' understanding of patient safety in the hospitals of the Faculty of Medical Sciences and Khoi Health Services.

This is a descriptive study in which 235 nurses who are responsible for the direct care of patients were selected from the research population by simple random sampling method. In order to collect the data, Kiwimaki and Alvanio innovation questionnaire (1999) and Patient Safety Culture Questionnaire of Health Service Research and Quality Agency (2004) were used. Also, the relevant analyzes were based on the structural equation modeling approach.

The results of the research showed that the state of team innovation has a significant effect on the openness of communication channels, feedback and informing others about errors, the frequency of reporting unwanted incidents, issues related to employees and manager's expectations and actions to improve safety.

The multiplicity of roles and responsibilities in nurses, as well as forced overtime and night work due to the lack of manpower, have caused nurses to be involved in several work fields, and such conditions cause superficiality, everydayness and unwillingness to implement innovation. Therefore, to be successful in innovation in the work environment, nurses must focus on one issue and one task.

Accreditation means the systematic evaluation of health care centers with specific standards. The overall purpose of this study was to investigate the effect of accreditation interventions on patient safety measurement in operating rooms of one of the social security hospitals in Tehran.

The present study is cross-sectional in terms of result, application and implementation method, analytical and time. The statistical population is information sources related to the patient safety measure and its sampling is in the period 1391-1399. The sampling method is numerical and includes all the information related to this time period. Data collection tools are receipts that have been extracted by library method from data sources and data centers in coordination with the Quality Improvement Office and the hospital statistics unit. Data analysis was performed using SPSS software and intermittent time series analysis method.

Findings of time series analysis, research has been reported in three forms of incremental effect, decreasing effect and ineffectiveness of the accreditation scheme of the scales. In the patient's safety measure, the results of the fragmentary regression table showed that at the beginning of the study period, the average patient's safety measure was 76.34%. Monthly changes in patient's safety measure were not significant before the intervention (P = 0.43). After the intervention, the mean level of the patient's safety measure did not change suddenly and significantly (P = 0.42). Also, the difference in the trend (slope) of the patient's safety measure before and after the intervention did not change significantly (P = 0.31). But the results showed that after the first intervention, the trend (slope) of the patient's average safety measurement changed significantly (P = 0.000); So that the patient's safety measure after the first intervention has increased seasonally by 1.06%. In general, the results of the study have shown that, as a result of the implementation of the accreditation scheme, the patient's safety measure has increased.

The results show that the implementation of accreditation measures has an effect on patient safety measures. The number of significant measures from 2016 to 2016 shows that the third and fourth editions of the national accreditation standards of Iranian hospitals have been effective. Based on the analyzes performed, it is recommended that the patient's safety measure be increased after the first intervention. Therefore, the implementation of accreditation in hospitals is recommended to managers.

As health and financial resources become more complex and limited in health care organizations, outsourcing and proper management become more important. This article aimed to determine the effective factors and design a model for outsourcing management of non-clinical services in public hospitals.

In the results, this research is one of the applied studies. A 28-item questionnaire was used to collect data which the variables were extracted from comparative studies of selected countries. The validity of the structure was evaluated by experts and the Cronbach's alpha coefficient was determined to be 0.85. The study population included health system policymakers, outsourcing experts, and managers of public hospitals. For sampling, the stratified method is used and data analysis is performed using IBM SPSS and LISREL software.

According to the final model, 6 main and effective factors on outsourcing management were identified, which included planning, decision making, performance management, contract, communication and knowledge management, in orderly. Planning factors with coefficients of 0.94 had the most impact and knowledge management had the least impact with a coefficient of 0.34 on the outsourcing management of non-clinical services in Iranian hospitals.

Based on the resulting model, there are various factors in effective management that dimensions related to planning and decision making are of special importance and need to be more considered when outsourcing non-clinical services in public hospitals

One of the fundamental changes in the health system of Iran is the implementation of the "Health System Reform Plan", the effects of which should be examined from various dimensions. The purpose of this study was to determine the effect of reform plan on performance indicators of health at Ahvaz University of Medical Sciences.

In this descriptive-analytical study, the data of the selected health indicators of Ahvaz University of Medical Sciences in the period before and after the health system reform plan (from 2012 to 2018) were collected, described and analyzed with SPSS. Study indicators include the coverage of neonatal hypothyroidism screening, annual incidence of neonatal hypothyroidism, the prevalence of hypertension, prevalence of diabetes, coverage of rural family physicians, percentage of rural households with sanitary toilets, and percentage of rural households with sanitary disposal.

The highest rate of change with regard to rural family physician index was between 2013 and 2017 years with a mean difference of 22.263 and the highest percentage of rural households with sanitary disposal index was between 2012 and 2017 years with a mean difference of 9.169 (p=0.002 & p=0.009, respectively). Also the rate of hypertension and diabetes prevalence indices were significant. The coverage of neonatal hypothyroidism screening index, annual incidence of neonatal hypothyroidism, and the percentage of rural households with sanitary toilets was not significant.

The coverage of rural family physicians and the percentage of rural households with sanitary disposal has increased after the reform plan. Also, the prevalence of hypertension and diabetes in populations over 30 years increased which is affected by various factors. The health reform plan has not affected coverage of neonatal hypothyroidism screening, annual incidence of neonatal hypothyroidism, and the percentage of rural households with sanitary toilets.

 Considering the rewards, intrinsic motivation and trusting the goodwill can provide a situation for employee creativity that is vital to the survival of the organization. Therefore, considering the important role of creative employees in organizations, the goal of present research was to investigate the relationship between reward systems and staff creativity of Pars Abad health network

 The present study is descriptive-survey in terms of method and applied in terms of purpose. Data were collected using the Standard Employee Creativity Scale by Torrance (1963) and the Kabura Reward Systems Questionnaire (2009). 238 people were selected as the sample by Cochran's formula and simple random sampling method. The obtained data were tested by Pearson correlation and multivariate regression analysis.

 The results showed that there were relationships between reward systems with stretch dimension (ß=0.173, p=0.007), with initiative dimension (ß=0.170, p=0.008) and with flexibility dimension (ß=144, p=0.026), but there was no significant relationship between reward systems with fluid dimension.

 Considering the relationship between reward systems and the creativity of the officials and employees of the health network of the studied city, it is suggested that the managers of the organization provide a suitable environment for creativity through methods such as timely reward in proportion to employees' performance. The implementation of the reward system and the program of job privileges and the granting of related benefits should be based on the results of the employee performance evaluation process.

The purpose of this study is Investigating the effect of strategic planning on human performance from the perspective of the staff of Shohada Tajrish Hospital in Tehran.

This research is applied-practical in terms of purpose and correlational in terms of nature and descriptive method. The statistical population of the present study includes all permanent staff of Shohada Tajrish Hospital. Using simple random sampling method and according to Cochran's formula, 184 people were selected as a statistical sample. In this study, the Strategic Human Resources Management Questionnaire and the Performance Questionnaire were used to collect data. Experts' opinions were used to confirm the validity of the questionnaire and SPSS software was used to assess the reliability. Cronbach's alpha was 0.868 and 0.751. SPSS software and simple linear regression were used to analyze the data.

The results showed that planning, supply, development, performance management, reward and employee relations have a significant effect on the performance of employees of Shohada Tajrish Hospital in Tehran.

Since the results of the research indicate a very strong relationship between strategic human resource management and the performance of the organization in Shohada Tajrish Hospital, it is necessary to pay sufficient attention to human resource management in health centers. It is also necessary to pay special attention to categories such as human education and development, effective interaction and communication with employees, and hiring and hiring.

Lack of financial resources and liquidity are the main problems of hospitals. Pharmacies are one of the sectors that affect the turnover of hospitals and due to lack of forecast for the use and supply of medicines, at the end of the year, encounter over-inventory, large volumes of expired medicines, and sometimes shortage of medicines. Therefore, medicine prediction using available retrospective data leads to improved resource management in hospitals. Due to the high capability of data mining in modeling medical problems, selected algorithms were used to determine the optimal model of medicine preparation.  

In this cross-sectional study, to investigate different types of data mining algorithms, an information form was developed based on the design objectives and then defined in the form of reports in the hospital information system. The data were extracted using Crystal Report software. To develop the model, the accuracy of the data mining prediction algorithms including KNN, SVM, NN, Random Forest, LR, and Adaboost was examined based on MSE, RMSE, MAE, and R2 criteria in Weka software.

Concerning R2, MAE, and RMSE criteria, Adaboost method (0.78, 247, 827) and random forest method (0.6, 1170, 1868) had the highest accuracy compared to other models and reduced the error rate more. Other methods with the above criteria had poorer performance in predicting the research problem.

The results of this study indicated that the Adaboost and random forest methods are more accurate than other methods. A small percentage of hospitals plan to manage the preparation of medicines; thus, it is suggested that managers of hospitals and pharmacies use data mining in the management of their respective units.

Employee`s loyalty is an important factor in achieving organizational goals and increasing the productivity of human resources in the organization. With this approach, the present study was conducted with the aim of developing a comprehensive model for nurses' loyalty during the Covid19 pandemic period in Golestan Hospital, Ahvaz.

The present study is a developmental-applied one in terms of purpose and the research method is (quantitative-qualitative) of data-based type. In the qualitative part, experts of human resource management and skilled nurseswith at least 15 years of experience and a master's degree by a non-random purposive method and in the quantitative part method of research was descriptive which were selected 215 people among the nursesof Golestan Hospital in Ahvaz based on Cochran'sformula by simple random method. Results of the interview using data-based method (Eshtruss Korbin 1998) and MaxQuda software and in the quantitative part with the structural equation model were analyzed.EthicalConsiderations:About the objectives of the research and the confidentiality of information were explained to the participants and their satisfaction wasobtained in written form.

The results showed that the causation factors which affect the loyalty of nurses during the covid19 pandemicperiod should be sought in the organizational factor. According to the fulfilled steps of open and pivotal and selective coding of the data, nurses' loyalty in this study can be considered as behavioral and attitudinal dimensions. According to the resultsof the open (43 concepts) and pivotal (7 categories) and selective coding stage, it can be said that causal conditions including (organizational factors, contextual conditions including job-related factors) and interferential factors (job motivation and extra-organizational) were identified. Also, the use of strategies such as reward and job motivation can be considered in building nurses' loyalty during the covid19 outbreak. Also results of quantitative part showed that the provided model has a suitable fitness.

According to the results of this study, it is necessary for managers to master a set of skills and technologies to be able to gain a proper understanding of the situation and needs of their employees. Also, in order to reduce managers'misunderstanding of employees, human resources training courses should be organized with the aim of improving the relationship between managers and employees and managers should have a better and more realistic understanding of the situation of employees.

Medical tourism is one of the important sub-branches of the tourism industry. One of the factors influencing the choice of hospital by the tourist is the way of providing hotel services in hospitals.

The research was a descriptive correlational study conducted in 2009 in selected private hospitals in Tehran. A researcher-made questionnaire was used to collect information about the components of hoteling and a Shahroudi questionnaire was used to examine the observance of the components affecting the attraction of health tourists. The samples included 78 employees of the international department of two private hospitals in Tehran. To measure normality, Kolmogorov-Smirnov tests and multivariate regression and Pearson correlation coefficient were used to measure and determine the relationship between variables by SPSS 21.

This study showed that there is a significant relationship between the six pillars of hospital hotels with the attraction of medical tourists. Pillars of "buildings and installations" (p <0.05), (r = 0.231), "equipment and facilities" (p <0.05), (r = 0.263), "welfare services" (P <0.05), (r = 0.357), "cleaning and hygiene services" (p <0.05) and (r = 0.234), "nutrition" (p <0.01), (r = 0.393), and "administrative affairs and workflow" (p <0.01), (r = 0.332), are directly correlated with the attraction of medical tourists. It was also found that "human resources" is not correlated with the attraction of medical tourists.

In order to attract more medical tourists, it’s necessary that hospital managers and health policy makers pay more attention to the hoteling pillars, especially "nutrition" and "administrative affairs and workflow", which have the most correlation with attracting medical tourists.

Effective management of human resources in accordance with changes in the inside and outside environment of the health care system is essential and has a significant impact on costs, time spent, speed of service delivery, and overall quality of health services. The purpose of this study was to design a local model of human resource management for the private health sector in West Azerbaijan province in 2019.

In this descriptive-analytical study, the Delphi method was used to evaluate the current status of human resource management in private health centers of West Azerbaijan province and to identify the effective components. A questionnaire was prepared by consulting experts. Cronbachchr('39')s alpha coefficient and SPSS software were used to determine the reliability of the questionnaires. Then, through modeling structural equations by Smart PLS software, the impact of human resource management components was assessed.

After implementing the three Delphi stages, using the valuable opinions of experts, the effective components of human resource management in the health sector and their various factors were determined and the 4 components of maintaining effectiveness, attracting effectiveness, hiring effectiveness, and improving effectiveness were identified by impact rates.

Factors affecting human resource management in the private health sector can be used as a pattern for development in the public sectors of the health system by managers to use scientific and principled processes to formulate strategies and policies of the organization and thus help to increase the productivity of its organization.

Due to the frequency, prevalence, and specific nature of cardiovascular diseases in our country, and the multiplicity, variety, complexity, and high cost of diagnostic and therapeutic services and equipment, the possibility of inducing demand in this category of diseases is higher. Using the partial least squares approach, this study aimed to test the factors affecting the induced demand in cardiovascular diseases, and provide a model of the relationship between these factors.

This was a library study with a systematic review of 49 articles, and then a survey of 118 people selected via random sampling method. First, a list of factors, sub-factors and components related to induced demand was extracted using qualitative content analysis technique; and then, using analysis technique, the path of the fitting model and the final model were validated by completing a validated questionnaire by physicians, experts, staff, and clients of Shahid Chamran Heart Hospital in Isfahan, Iran, in 2019.

Results:

In this study, 5 main factors, 18 sub-factors, and 82 items were obtained. In fitting the measurement model, the combined reliability coefficient, cross validity, convergent, and divergent the results of test was acceptable, and in structural fit model, path coefficients were significant, except for “patients” coefficient, at the 95% confidence, the mean model determination coefficient was 0.822 (strong), and the predictive fit index, except for the characteristics of medical services, was greater than 0.02 (acceptable). The result of the overall fit test was 0.133, which indicated the desirability of the overall fit of the model. The validity of the final model was confirmed with 77% agreement of experts.

Based on the findings of this study, it is necessary to adopt an appropriate policy at the macro-level to reform the network structure and referral and strengthen information management, and at the executive level, to modify payment methods, change tariffs and franchises for services, and change insurance methods and coverage.

Optimal management of food services in hospitals plays an important role in their performance, accelerating the patients’ recovery and increasing the level of patient satisfaction. The purpose of this study was to design a model for food service management in Iranian hospitals.

Methots:

This descriptive correlational study was carried out using structural equation modeling. Simple random sampling was performed and the study participants were selected among  hospital managers, nutrition experts, and environmental health experts in a hospital management conference in Tehran in September 2018. The measurement tool was a researcher-made questionnaire with confirmed construct validity and corroborated reliability through Cronbachchr('39')s alpha. For data analysis, exploratory factor analysis and confirmatory factor analysis were performed via SPSS 21 and AMOS 22 software.

Based on the obtained model, 5 main factors affecting the management of food service sector were identified, including: health and safety factors, satisfaction factors, food waste factors, monitoring and control factors, and mechanism factors. Among these, health and mechanism factors with coefficients of 0.874 and 0.612 had the highest and the lowest effect in the management of food services in Iranian hospitals, respectively.

According to the obtained model, various factors are effective in food management that should be considered in hospital planning. Based on this, the food health and safety dimensions are of particular importance.

Individuals With Disabilities (IWDs) are part of the society that, respecting their situation, have the greatest need for social support and the provision of desirable services. However, in underdeveloped and developing countries, the existence of a negative and incorrect view towards IWDs is effective in providing services to them, especially in care centers; accordingly, this condition makes this part of society encounter numerous challenges in receiving the necessary services. Factors, such as the number of IWDs in care centers, their age, their ratio to the number of caregivers, and the characteristics of caregivers, such as their professional skills and experience, are influential in the occurrence of abusive behaviors. Due to the necessity of providing efficient and effective service to IWDs, the present study aimed to identify the challenges of providing services in care centers for IWDs.

This qualitative study was conducted in 2020. The research setting consisted of all care centers for IWDs in Tehran City, Iran. Moreover, the study population included the managers of care centers for IWDs in Tehran. Using the purposive sampling method, 19 managers of the centers were selected and interviewed according to the objectives of the study. The interviews continued until reaching data saturation. For data collection, we used semi–structured interviews; the interviews were recorded, then transcribed, and analyzed with the consent of the study participants. For data confirmation, each interview was provided to the study participants after analysis, and their opinions were re–obtained concerning their interviews. The latent content analysis method was also used to analyze the collected data. For this purpose, after listening to each interview several times and reading the transcripts line by line, important phrases in the content of the data were identified; consequently, the appropriate concepts were determined and placed in the same categories. To observe ethical issues, verbal informed consent was obtained from all study participants before conducting the interviews. SPSS was used to investigate the frequency distribution of study participants respecting the demographic variables.

The mean age of study participants was 41.13 years. The majority of the study participants (57.89%) were in the age group of 41–46 years. Their average work experience equaled 14.51 years and the majority (68.42%) were in the group of 13–20 years. Additionally, most of the respondents had a BA degree (68 .</span>42%). After analyzing the interviews with 19 managers of the centers, the first 321 separate codes were obtained; after analyzing, they were grouped under 15 sub–categories. Finally, after reviewing and analyzing these subcategories, 3 main categories, including cultural–educational factors, planning, and necessary resources, as well as facilities and infrastructures were developed. Cultural–Educational characteristics, included the lack of culture creating, the lack of promotion of public knowledge, the lack of individual and public education, not introducing resources about disability, no belief in the ability of IWDs, and the lack of education and training of human resources. Planning consisted of the lack of a database, no codified service delivery programs, no plan to increase service coverage, guidelines, and specific program for use by IWDs. Necessary resources, facilities, and infrastructures included the lack of adequate equipment and items, drug shortages, human and financial resources, the lack of interdepartmental supports to support IWDs.

According to the current research findings, factors related to culture–education, planning, and the necessary resources, facilities and infrastructures were the main challenges and obstacles in providing services to IWDs.

Organizations to develop and succeed need the knowledge, capabilities, and experience of human resources in a highly competitive global market. In knowledge organizations such as health organizations, is essential existence of performance evaluation system to maintain and grow tacit knowledge. The purpose of this study is to identify the most important dimensions and appropriate indicators for evaluation the performance of knowledge workers.

This study was a narrative review articles and reports on the knowledge workers health system between 2010 and 2020. In order to access related scientific documents, electronic search in both Persian and English using the keywords performance evaluation, performance evaluation system of knowledge workers, Scientific (SID), Iran Medical Sciences Articles Database (Magiran), Iran Medex article database (Iran Medex), PubMed, Science Direct, Inter Science, Ovid, Pro Quest.

The search results in different sites, including 7 articles in Persian in the field of evaluating the performance of knowledge workers, have been paid a survey variable such as independence, creativity and self-control by considering the results-based management and educational and research activities.

In the health system as a knowledge-based organization, managers must plan to implementation an optimal knowledge performance evaluation system. Thus fit model should be design to evaluation performance of knowledge workers, so that in addition an effective management of service delivery processes better health care quality outcomes.can be achieved.

Police hospitals provide specialized and general care services to staff, soldiers, and the public, according to their main mission, which is to support police missions in different situations. Some clients of these hospitals have rights that need to be considered due to special circumstances. This study aimed to design and validate the evaluation model of service recipient supports in accreditation of police hospitals.

The present study was a mixed-method conducted in three phases in 2020 includes library, qualitative, and Delphi phases. At the first, using the appropriate keywords and a thorough review of the literature in the main databases, including PubMed, Scopus, Web of Science, Science Direct, related military websites, as well as existing documents and instructions, all sources related to the support of the recipient in public and Police hospitals were identified. Also, to identify more structures, infrastructures, and standards, 9 policymakers and officials of the Department of Health, rescue and treatment were interviewed and after analyzing them, the initial questionnaire of the evaluation model of service recipient support in police hospitals was designed. Then the validity of the model was confirmed using the Delphi method and a survey of 45 experts and key informants in police hospitals by descriptive statistics.

The proposed model was presented for evaluating the service recipient supports in police hospitals in four main dimensions include providing the necessary facilities for special services recipients, planning and managing medical councils and medical services, the satisfaction of clients, patients, and their families with services and the charter of patientschr('39') rights to special clients.

This study led to the design of an evaluation model for service recipients in Police hospitals in the form of 4 dimensions and 15 indicators that can be used as a comprehensive tool and complementary to current evaluation methods such as national accreditation standards of Iranian hospitals, evaluates the service recipients in these hospitals.

Induced demand is defined as the sale of unnecessary services to patients by exercising power and ordering health stakeholders. The purpose of this study is to identify and provide a comprehensive framework of factors affecting the inductive demand in the Iranian health system from the perspective of experts and specialists.

In terms of the type of study, the research was a qualitative content analysis from 2014 to 2018. 14 articles from Iranian data and 101 articles from global citation databases were selected, and 20 related articles were selected according to the purpose of the research. By carefully studying them by qualitative analysis method, a list of main and sub-factors and components of induced demand were identified. Then, the list was modified with the opinions of a group of experts, and the final list was obtained.

The final results of the initial analysis and the opinions of experts and experts in relation to the factors affecting the induced demand in the 5 main categories of fundamental, social, organizational structure, economic, stakeholders, and 18 sub-categories and 82 factors were identified and presented.

Summarizing the findings of this study shows that due to the expansion and multiplicity of factors and the complex nature of the induced demand phenomenon in the health system, only by identifying the relevant factors can its harmful effects be controlled.

One of the fundamental changes in the health system of Iran in recent years is the "health system reform plan", that the effects of which should be examined from various dimensions. The purpose of this study is to determining the effect of health system reform plan on health indicators in population covered by Ahvaz University of Medical Sciences.

In this descriptive-analytical study, the data of the selected health indicators of Ahvaz University of Medical Sciences in the period before and after the health care system reform plan (from 2012 to 2018) was collected, described and analyzed with SPSS.

The highest rate of change in mortality indices was between 2013 and 2015, orderly in U5MR, IMR & NMR, With the mean difference 13.282, 10.825 & 7.955 (P=0.001, P=0.002 & P=0.004). The highest rate of change in Care Coverage for Children Under-five, is between 2014 and 2015 with mean difference of 11.335 and about the Antenatal Care Coverage, between 2014 and 2017, with mean difference 10.050 (orderly p=0.002 & p>0.001). MMR was not significant.

The time trend analysis on health indicators confirms that the changes in the early years of the reform plan have been a lot, then it has slow down. Most of the change in health indicators is related to years of 2015 and 2016. The findings indicate that the latest health reform plan in Iran has improved the mortality indices (Reduce in NMR, IMR & U5MR), Care Coverage for Children Under-five and Antenatal Care Coverage (6+). Health reform plan has not affected on MMR.

 Demand for health in the sense of providing unnecessary services with the intention of benefiting  to patients or clients has always been challenging with the exercise of power and order by stekeholders. The present article aims to identify factors for controlling induced demand in cardiovascular diseases with basic and supplemental insurance with the help of experts and experts, to provide strategies for controlling it to be used in macro-level policy and planning and implementation levels.

 This research was a mixed method. In the first part of the narrative review and consensus of experts a researcher-made questionnaire was prepared and its validity and reliability were confirmed. Shahid Chamran data were collected and analyzed in SPSS 20 software.

 The highest and the lowest mean score of induction-related factors in cardiovascular patients were social (3.36 ± 0.76) and stakeholders (2.90 ± 0.76))respectively. Among the social factors sub-factors, community health literacy (3.38 ± 0.81) and among the sub factors, stakeholders, physicians, and professional ethics (3.13 ± 0.97) had higher average insurance coverage (Insurers showed a lesser role in stimulating consumption and possibly inducing demand).

 According to the findings of this study, it recommends to policy makers adopted and communicated their to prioritize appropriate policies for fundamental and structural change focusing on changing the knowledge and attitudes of people at all levels of education in the country, including people, physicians, insurers and stekholders.  It advises executives to provide the necessary infrastructure for the development of insurance in the country by following these policies.