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Mohammad Reza Zabihi, Seyed Saeed Tabatabaee, Mohammad Reza Ghamari , Mohammad Hanif Asadi,
Volume 9, Issue 1 (5-2015)
Volume 9, Issue 1 (5-2015)
Abstract
Background and Aim: Due to the changing environment of hospitals and the necessity of providing services for patients in the shortest possible time and at an acceptable quality and cost, it seems to be necessary to utilize the maximum intellectual capacity of the organization to enhance agility in hospitals. The aim of this study is, in fact, to investigate the relationship between organizational intelligence (and its components according to the Albrecht model) and organizational agility in hospitals of Mashhad University of Medical Sciences.
Materials and Methods: This descriptive study was conducted in 2013 on 408 hospital employees seleced through stratified sampling method. To collect data on organizational intelligence, the Albrekht standardized questionnaire was used and to gather data on organizational agility, a questionnaire designed based on Goldman model was employed. For data analysis and hypothesis testing, the SPSS software version16, Pearson correlation, t-test, Anova, and regression techniques were applied.
Results: The results of the study showed that there was a significant relationship between agility in hospitals and organizational intelligence ( components : Appetite for change, heart, knowledge deployment, performance pressure, strategic vision, shared fate, and alignment and congruence). The determinants of agility were mainly strategic vision, performance pressure, and a lignment and congruence.
Conclusion: The results of the study showed that dynamic strategic planning in hospitals and developing educational programs of organizational intelligence aiming at employees' and managers' awareness could lead to an increase in the agility level of hospitals and provision of effective services for patients.
Abolfazl Dorost, Ahmad Fayaz-Bakhsh , Mostafa Hosseini , Hamzeh Mohammadi ,
Volume 11, Issue 4 (12-2017)
Volume 11, Issue 4 (12-2017)
Abstract
Background and Aim: Occupational burnout is one of the aspects of psychological hazards. One of the most important factors that can predict it is emotional intelligence. The aim of this study was to investigate the effect of emotional intelligence on occupational burnout among the managers of Tehran University of Medical Sciences (TUMS) selected hospitals.
Materials and Methods: This was a cross-sectional descriptive and analytical study in 2014. The subjects were senior, middle and executive managers of TUMS affiliated hospitals. Census was used in this study. Ninety questionnaires were distributed in accordance with the population size. For data collection, Maslach Burnout Inventory (with reliability and retest coefficients of 0.71-0.9 and 0.6-0.8, respectively), Intelligence Questionnaire by Bradberry and Greaves (with reliability and validity of 0.83 and 0.67, respectively) and demographicprofile questionnaire were used. All statistical analyses were performed by SPSS software.
Results: There was no significant relationship between job burnout and demographic variables (e.g. work experience, management experience, education, gender, marital status and occupational position). Emotional intelligence of managers and its subscales were high. The highest and lowest scores of emotional intelligence component belonged to relationship management and social awareness, respectively. There was no meaningful relationship between job burnout and emotional intelligence at the error level of 5% and P-value=0.63.
Conclusion: Since managers’ social awareness was at a low level, by improving it, we can help their emotional intelligence increase; also by identifying the factors affecting hospital managers’ occupational burnout, we can help it decrease.
Materials and Methods: This was a cross-sectional descriptive and analytical study in 2014. The subjects were senior, middle and executive managers of TUMS affiliated hospitals. Census was used in this study. Ninety questionnaires were distributed in accordance with the population size. For data collection, Maslach Burnout Inventory (with reliability and retest coefficients of 0.71-0.9 and 0.6-0.8, respectively), Intelligence Questionnaire by Bradberry and Greaves (with reliability and validity of 0.83 and 0.67, respectively) and demographicprofile questionnaire were used. All statistical analyses were performed by SPSS software.
Results: There was no significant relationship between job burnout and demographic variables (e.g. work experience, management experience, education, gender, marital status and occupational position). Emotional intelligence of managers and its subscales were high. The highest and lowest scores of emotional intelligence component belonged to relationship management and social awareness, respectively. There was no meaningful relationship between job burnout and emotional intelligence at the error level of 5% and P-value=0.63.
Conclusion: Since managers’ social awareness was at a low level, by improving it, we can help their emotional intelligence increase; also by identifying the factors affecting hospital managers’ occupational burnout, we can help it decrease.
Zeinab Ghaderabadi , Alireza Amirkabiri , Mohammadreza Rabiee Mandejin ,
Volume 11, Issue 4 (12-2017)
Volume 11, Issue 4 (12-2017)
Abstract
Background and Aim: Emotional intelligence Skills is highly crucial in career success and achivement critical responsibilities accompolishments. Psychologists believe that 20% and 80% of individuals’ success depends on IQ and emotional intelligence (EQ) respectively. This study is aimed to investigate the relationship between emotional intelligence and job performance among the staff of Shariati Hospital at Tehran University of Medical Sciences in 2016.
Materials and Methods: In a descriptive-analytical method, 1030 individuals from different units of shariati hospital`s staff were studied. 280 persons were randomly selected by using a Cochran formula. Two questionnaires regarding Schering Siberia emotional intelligence (1990) and Patterson job performance (1975) were used after being validated through experts and specialists` view and reliablity analysis (Cronbach's alpha values of questionare of emotional intelligence=0.734 and job performance=0.768). The data were analysed by use of descriptive statistics, Pearson correlation test and Friedman test.
Results: The total studied staff was included 73% women 62% married and 67% college education. The average emotional intelligence rating was 182 (with IE of 34) and average job performance was 109 (with IE of 22).The result showed a significant correlation between emotional intelligence and job performance (p=0.030). Using Friedman statistical test, ranking of emotional intelligence components were conducted; the self-awareness and social skills had the first and fourth rank respectively.
Conclusion: Training and the improvement of emotional intelligence skills and capabilities can be used to enhance the process of the hospital staff recrument andimprove their performance level.
Materials and Methods: In a descriptive-analytical method, 1030 individuals from different units of shariati hospital`s staff were studied. 280 persons were randomly selected by using a Cochran formula. Two questionnaires regarding Schering Siberia emotional intelligence (1990) and Patterson job performance (1975) were used after being validated through experts and specialists` view and reliablity analysis (Cronbach's alpha values of questionare of emotional intelligence=0.734 and job performance=0.768). The data were analysed by use of descriptive statistics, Pearson correlation test and Friedman test.
Results: The total studied staff was included 73% women 62% married and 67% college education. The average emotional intelligence rating was 182 (with IE of 34) and average job performance was 109 (with IE of 22).The result showed a significant correlation between emotional intelligence and job performance (p=0.030). Using Friedman statistical test, ranking of emotional intelligence components were conducted; the self-awareness and social skills had the first and fourth rank respectively.
Conclusion: Training and the improvement of emotional intelligence skills and capabilities can be used to enhance the process of the hospital staff recrument andimprove their performance level.
Kaveh Nouhi Bezanjani, Hamdollah Manzari Tavakoli, Sanjar Salajeghe, Ayyub Sheikhi,
Volume 13, Issue 1 (5-2019)
Volume 13, Issue 1 (5-2019)
Abstract
Background and Aim: This study was conducted due to the increasing importance of ethics in providing nursing care and also due to the role of nurses' moral intelligence in quality of care; meanwhile, the role of authentic leadership (AL) in enhancing the moral intelligence of nurses working in Kerman University of Medical Sciences hospitals was investigated.
Materials and Methods: This is a mixed methods research. In this study, after defining nurses’ moral intelligence model qualitatively, the relationship between nurses’ moral intelligence and authentic leadership (AL) was tested quantitatively.
In order to study authentic leadership, the AL standard questionnaire of Walumbwa & et al (2008) with a reliability of 0.917 was used; moreover, a researcher-made questionnaire was used for investigating moral intelligence with overall validity (81%) and reliability (0.961). The statistical population of the study consisted of 400 hospital nurses selected by stratified sampling method. SPSS20 and Amos24 software, and statistical methods of exploratory and confirmatory factor analysis as well as structural equation modeling were used to analyze the research hypotheses.
Results: The results showed a positive and significant relationship between AL and moral intelligence of nurses (0.575). In addition, all components of AL, i. e., self-awareness (0.322), internalized moral perspective (0.360), relational transparency (0.408), balanced processing (0.394) showed a positive and significant relationship with moral intelligence.
Conclusion: Applying suitable strategies for enhancing moral intelligence of nurses and improving the quality of nursing care can have a positive effect on the quality of services. The AL in the hospitals' nursing system is one of the most suitable ways for developing the moral intelligence of nurses.
Materials and Methods: This is a mixed methods research. In this study, after defining nurses’ moral intelligence model qualitatively, the relationship between nurses’ moral intelligence and authentic leadership (AL) was tested quantitatively.
In order to study authentic leadership, the AL standard questionnaire of Walumbwa & et al (2008) with a reliability of 0.917 was used; moreover, a researcher-made questionnaire was used for investigating moral intelligence with overall validity (81%) and reliability (0.961). The statistical population of the study consisted of 400 hospital nurses selected by stratified sampling method. SPSS20 and Amos24 software, and statistical methods of exploratory and confirmatory factor analysis as well as structural equation modeling were used to analyze the research hypotheses.
Results: The results showed a positive and significant relationship between AL and moral intelligence of nurses (0.575). In addition, all components of AL, i. e., self-awareness (0.322), internalized moral perspective (0.360), relational transparency (0.408), balanced processing (0.394) showed a positive and significant relationship with moral intelligence.
Conclusion: Applying suitable strategies for enhancing moral intelligence of nurses and improving the quality of nursing care can have a positive effect on the quality of services. The AL in the hospitals' nursing system is one of the most suitable ways for developing the moral intelligence of nurses.
Aeen Mohammadi, Rita Mojtahedzadeh, Afzal Shamsi,
Volume 13, Issue 4 (11-2019)
Volume 13, Issue 4 (11-2019)
Abstract
Background and Aim: Students' academic achievement is one of the important indicators in evaluating the educational system. Emotional intelligence is one of the success factors in educational environments that can predict success in different aspects of life.The purpose of this study was to determine the relationship between emotional intelligence and academic achievement in students of Anesthesiology and Operating Room of Tehran University of Medical Sciences.
Materials and Methods: This cross-sectional study was performed on 140 people of anesthesiology students and operating room of Tehran University of Medical Sciences in 2018. The samples were selected by available method. The instrument consisted of two demographic questionnaires and the Bradbury and Graves' standard questionnaire for emotional intelligence. In order to measure academic achievement, the average score of the whole course of the students was used. Data were analyzed by SPSS software and P<0.05 was considered as significant.
Results: Pearson's correlation coefficient showed a significant positive correlation between academic achievement and total emotional intelligence(r=0.554) and all its dimensions(self-awareness, self-management, social awareness and relationship management)(P=0.000). The mean score of emotional intelligence in female students(114.11±11.40) was higher than that of male students(113.39±12.57)(P=0.887).
Conclusion: The mean score of students' emotional intelligence and its dimensions was in a desired level. There was a positive and significant relationship between emotional intelligence and all aspects of it with academic achievement. Therefore, it is essential for the authorities to plan for the improvement of the level of emotional intelligence for the students' academic achievement.
Materials and Methods: This cross-sectional study was performed on 140 people of anesthesiology students and operating room of Tehran University of Medical Sciences in 2018. The samples were selected by available method. The instrument consisted of two demographic questionnaires and the Bradbury and Graves' standard questionnaire for emotional intelligence. In order to measure academic achievement, the average score of the whole course of the students was used. Data were analyzed by SPSS software and P<0.05 was considered as significant.
Results: Pearson's correlation coefficient showed a significant positive correlation between academic achievement and total emotional intelligence(r=0.554) and all its dimensions(self-awareness, self-management, social awareness and relationship management)(P=0.000). The mean score of emotional intelligence in female students(114.11±11.40) was higher than that of male students(113.39±12.57)(P=0.887).
Conclusion: The mean score of students' emotional intelligence and its dimensions was in a desired level. There was a positive and significant relationship between emotional intelligence and all aspects of it with academic achievement. Therefore, it is essential for the authorities to plan for the improvement of the level of emotional intelligence for the students' academic achievement.
Nastaran Abbasi Hasanabadi, Farzad Firouzi Jahantigh, Payam Tabarsi,
Volume 13, Issue 6 (2-2020)
Volume 13, Issue 6 (2-2020)
Abstract
Background and Aim: Despite the implementation of effective preventive and therapeutic programs, no significant success has been achieved in the reduction of tuberculosis. One of the reasons is the delay in diagnosis. Therefore, the creation of a diagnostic aid system can help to diagnose early Tuberculosis. The purpose of this research was to evaluate the role of the Naive Bayes algorithm as a tool for the diagnosis of pulmonary Tuberculosis.
Materials and Methods: In this practical study, the study population included Patients with TB symptoms, the study sample is recorded data of 582 individuals with primary Tuberculosis symptoms in Tehran's Masih Daneshvari Hospital. The data of samples were investigated in two classes of pulmonary Tuberculosis and non-Tuberculosis. A Naive Bayes algorithm for screening pulmonary Tuberculosis using primary symptoms of patients has been used in Python software version 3.7.
Results: Accuracy, sensitivity and specificity after the implementation of the Naive Bayes algorithm for diagnosis of pulmonary Tuberculosis were %95.89, %93.59 and %98.53, respectively, and the Area under curve was calculated %98.91.
Conclusion: The performance of a Naive Bayes model for diagnosis of pulmonary Tuberculosis is accurate. This system can be used to help the patient and manage illness in remote areas with limited access to laboratory resources and healthcare professional and cause to diagnose early Tuberculosis. It can also lead to timely and appropriate proceedings to control the transmission of TB to other people and to accelerate the recovery of the disease.
Materials and Methods: In this practical study, the study population included Patients with TB symptoms, the study sample is recorded data of 582 individuals with primary Tuberculosis symptoms in Tehran's Masih Daneshvari Hospital. The data of samples were investigated in two classes of pulmonary Tuberculosis and non-Tuberculosis. A Naive Bayes algorithm for screening pulmonary Tuberculosis using primary symptoms of patients has been used in Python software version 3.7.
Results: Accuracy, sensitivity and specificity after the implementation of the Naive Bayes algorithm for diagnosis of pulmonary Tuberculosis were %95.89, %93.59 and %98.53, respectively, and the Area under curve was calculated %98.91.
Conclusion: The performance of a Naive Bayes model for diagnosis of pulmonary Tuberculosis is accurate. This system can be used to help the patient and manage illness in remote areas with limited access to laboratory resources and healthcare professional and cause to diagnose early Tuberculosis. It can also lead to timely and appropriate proceedings to control the transmission of TB to other people and to accelerate the recovery of the disease.
Eng. Meisam Fallahnezhad, Reza Safdari,
Volume 15, Issue 3 (8-2021)
Volume 15, Issue 3 (8-2021)
Abstract
Background and Aim: Large amounts of hospital costs are not reimbursed annually by health insurance as deductions. Therefore, reducing deductions is very important for the hospital. In the study of design and implementation of analytical dashboard of insurance deductions based on medical intelligence business, to improve financial management with the aim of focusing on assessing the level of satisfaction and its applicability has been done.
Materials and Methods: To design the questionnaire, first 27 questions were prepared through library studies and interviews with members of the hospital board of directors, and the validity and consistency of its items were determined through content validity and Cronbach’s alpha coefficient. Data were analyzed in SPSS software and the results were used to design and implement the dashboard.
Results: The study is of development-applied type. In the first phase, to determine Content Validity Ratio CVI (Content Validity Index), and CVR (Content Validity Ratio) a researcher-made questionnaire was provided to 20 experts. In the second phase, by building a data warehouse in SQL (Structured Query Language), the information of the tables related to the deductions of the hospital HIS system was transferred to it and the operational information of the organization was extracted and converted into DW format and the map information was tested. OLAP (Online Analytical Processing) services were then loaded on the created analytics database. In the last step, Power BI tool was selected and used to create business intelligence mechanisms, display and visualize information. In the third phase, using the QUIS (Questionnaire for User Interface Satisfaction) standard questionnaire, the level of satisfaction and usability of the dashboard was evaluated by 15 experts.
Conclusion: In this study, two questionnaires were used. CVR was measured in all items of the first questionnaire, more than 0.50 and CVI was measured in the upper areas of 0.90 and Cronbach’s alpha coefficient was obtained between 0.8 and 0.9, which indicated a good level. The second questionnaire was to evaluate the level of satisfaction and usability of the dashboard that the average of the total evaluation based on the indicators of the QUIS questionnaire is equal to 85.40. Therefore, the level of satisfaction and usability of the dashboard was “very good” for the evaluators.
Materials and Methods: To design the questionnaire, first 27 questions were prepared through library studies and interviews with members of the hospital board of directors, and the validity and consistency of its items were determined through content validity and Cronbach’s alpha coefficient. Data were analyzed in SPSS software and the results were used to design and implement the dashboard.
Results: The study is of development-applied type. In the first phase, to determine Content Validity Ratio CVI (Content Validity Index), and CVR (Content Validity Ratio) a researcher-made questionnaire was provided to 20 experts. In the second phase, by building a data warehouse in SQL (Structured Query Language), the information of the tables related to the deductions of the hospital HIS system was transferred to it and the operational information of the organization was extracted and converted into DW format and the map information was tested. OLAP (Online Analytical Processing) services were then loaded on the created analytics database. In the last step, Power BI tool was selected and used to create business intelligence mechanisms, display and visualize information. In the third phase, using the QUIS (Questionnaire for User Interface Satisfaction) standard questionnaire, the level of satisfaction and usability of the dashboard was evaluated by 15 experts.
Conclusion: In this study, two questionnaires were used. CVR was measured in all items of the first questionnaire, more than 0.50 and CVI was measured in the upper areas of 0.90 and Cronbach’s alpha coefficient was obtained between 0.8 and 0.9, which indicated a good level. The second questionnaire was to evaluate the level of satisfaction and usability of the dashboard that the average of the total evaluation based on the indicators of the QUIS questionnaire is equal to 85.40. Therefore, the level of satisfaction and usability of the dashboard was “very good” for the evaluators.
Fatemeh Bahador, Azam Sabahi, Samaneh Jalali, Fatemeh Ameri,
Volume 16, Issue 6 (1-2023)
Volume 16, Issue 6 (1-2023)
Abstract
Background and Aim: Diabetes is one of the most common metabolic diseases in Iran and the fifth leading cause of death all over the world. Its spread around the world has created new methods in biomedical research, including artificial intelligence. The present study was carried out to review the studies conducted in the area of artificial intelligence and diabetes in Iran.
Materials and Methods: This study was carried out using a systematic review method. Valid domestic databases, including Irandoc, Magiran, Sid and Google Scholar search engine, were reviewed using the keywords of artificial intelligence and diabetes in Persian both individually and in a combined manner without time limitation until June 20, 2021. A total number of 7495 articles were retrieved, which were screened in different stages (exclusion of duplicates (1824), title and summary of the articles (5884) and full text (30) and finally 20 articles that met the criteria desired by the researchers were carefully reviewed.
Results: Among the retrieved articles, 20 articles met the inclusion criteria, of which 16 articles dealt with methods based on artificial intelligence and 4 articles dealt with the design of new systems based on artificial intelligence. Also, 10 articles examined the role of artificial intelligence in prediction, 8 articles in diagnosis, and 2 articles dealt with the control and management of diabetes. Most of the articles were related to the use of data mining methods such as artificial neural network, decision tree, etc. (16 articles). Some studies also evaluated and compared artificial intelligence methods on application, accuracy and the sensitivity of artificial intelligence in diagnosing and predicting diabetes (10 studies).
Conclusion: A systematic review of articles revealed that the use of data mining methods for diabetes management in Iran has been associated with good progress, but there is a need to design artificial intelligence systems and algorithms and more measures should be taken in the area of diabetes control and management.
Materials and Methods: This study was carried out using a systematic review method. Valid domestic databases, including Irandoc, Magiran, Sid and Google Scholar search engine, were reviewed using the keywords of artificial intelligence and diabetes in Persian both individually and in a combined manner without time limitation until June 20, 2021. A total number of 7495 articles were retrieved, which were screened in different stages (exclusion of duplicates (1824), title and summary of the articles (5884) and full text (30) and finally 20 articles that met the criteria desired by the researchers were carefully reviewed.
Results: Among the retrieved articles, 20 articles met the inclusion criteria, of which 16 articles dealt with methods based on artificial intelligence and 4 articles dealt with the design of new systems based on artificial intelligence. Also, 10 articles examined the role of artificial intelligence in prediction, 8 articles in diagnosis, and 2 articles dealt with the control and management of diabetes. Most of the articles were related to the use of data mining methods such as artificial neural network, decision tree, etc. (16 articles). Some studies also evaluated and compared artificial intelligence methods on application, accuracy and the sensitivity of artificial intelligence in diagnosing and predicting diabetes (10 studies).
Conclusion: A systematic review of articles revealed that the use of data mining methods for diabetes management in Iran has been associated with good progress, but there is a need to design artificial intelligence systems and algorithms and more measures should be taken in the area of diabetes control and management.
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.
Mrs Fatemeh Rangraz Jeddi, Ehsan Nabovati, Shima Anvari Tafti, Parisa Yousefi Konjdar,
Volume 17, Issue 5 (12-2023)
Volume 17, Issue 5 (12-2023)
Abstract
Background and Aim: A medication dashboard could provide executive directors and managers with the ability to manage medication resources in hospitals. This study aimed to design, implement, and evaluate a medication resources management dashboard for general hospitals.
Materials and Methods: This study was of the development-applied type conducted in an academic therapeutic community center. Based on scientific sources, the dashboard’s key performance indicators (KPIs) and functional requirements were identified. The data collection tool was a questionnaire comprising demographic information, KPIs, and functional requirements. The dashboard conceptual model was designed using Rational Rose software, and then POWER BI software was used to develop the system. The usability of the dashboard was evaluated using the standard questionnaire for End User Computing Satisfaction by 10 users. The data were analyzed in SPSS software using descriptive statistics.
Results: The most important KPIs determined for a medication resources management dashboard in general hospitals were “the ratio of antibiotic consumption to total number of drugs”, “the ratio of the antibiotic prescribed by general practitioners to total number of drugs”, “the ratio of patients for whom antibiotics were prescribed to all patients”, and “the ratio of the number of drug items prescribed by specialists to all physicians”. The most important functional requirements determined were “updating information at specific intervals “, “checking the dashboard at different time intervals”, “defining access levels to view the information”, and “choosing between graphical and tabular displays”. Usability evaluation showed that users’ satisfaction with the dashboard content variable was “very high” and for the other variables was at a “high” level.
Conclusion: The KPIs associated with antibiotics and drug costs within the medication dashboard of general hospitals are high priority. Future studies should evaluate the impact of using a medication dashboard on hospital executive directors’ and managers’ decision-making.
Malihe Ghanaatjoo, Nader Jahanmehr, Dr. Hamed Dehnavi, Aida Samadi,
Volume 18, Issue 2 (5-2024)
Volume 18, Issue 2 (5-2024)
Abstract
Background and Aim: The increase in the amount of information and the need for their daily monitoring have led to the development of tools called management dashboards that have the ability to analyze graphical data. In addition to preparing quick reports in different time frames and user-specific format, the dashboard can be useful for providing dynamic updated information for accurate decision-making and quick response to changes.
Materials and Methods: The current research was carried out in the form of qualitative studies and participatory action research method in 9 steps. In this applied and developmental research that was conducted cross-sectionally using the data of the first half of 2022, 11 members of the leadership team of a super-specialized children’s hospital were selected as research participants. The data collection tool was an interview using a questionnaire to determine the importance of indicators and a usability questionnaire (usability) of the dashboard based on three independent variables (usefulness, ease of use and satisfaction). The Excel file of data needed for the dashboard was collected from the HIS system of the hospital, and the dashboard was designed with Power BI software, and the capabilities and access levels of users were determined based on their duties. Data analysis was done using descriptive statistics and Excel software version 2016.
Results: In the stage of determining key performance indicators, out of 39 indicators selected by the research team, 22 indicators scored an average score of 4 or higher (from 5 points) and 21 indicators were able to be implemented. The data repository in Excel format was used as an intermediate environment. The dashboard was displayed on six pages (indicators related to the performance of inpatient beds, mortality, emergency and other indicators) and the capabilities of each page were determined. After implementing the dashboard and determining the access levels of users, obtaining a high score from the questions of the usability questionnaire (5 out of 7 points) and obtaining an average score of 71.8 out of 5 questions related to usefulness variables, 70.5 out of 8 questions related to ease of use. And 71 out of 3 questions related to the satisfaction variable showed that the dashboard designed for the hospital had high usability.
Conclusion: Hospital management dashboard information can be a basis for informed decision-making to achieve benefits such as identifying the best performance, improving performance quality, making faster decisions, reducing errors, improving capacity management and work flow, allocating resources and planning for growth and development.
Materials and Methods: The current research was carried out in the form of qualitative studies and participatory action research method in 9 steps. In this applied and developmental research that was conducted cross-sectionally using the data of the first half of 2022, 11 members of the leadership team of a super-specialized children’s hospital were selected as research participants. The data collection tool was an interview using a questionnaire to determine the importance of indicators and a usability questionnaire (usability) of the dashboard based on three independent variables (usefulness, ease of use and satisfaction). The Excel file of data needed for the dashboard was collected from the HIS system of the hospital, and the dashboard was designed with Power BI software, and the capabilities and access levels of users were determined based on their duties. Data analysis was done using descriptive statistics and Excel software version 2016.
Results: In the stage of determining key performance indicators, out of 39 indicators selected by the research team, 22 indicators scored an average score of 4 or higher (from 5 points) and 21 indicators were able to be implemented. The data repository in Excel format was used as an intermediate environment. The dashboard was displayed on six pages (indicators related to the performance of inpatient beds, mortality, emergency and other indicators) and the capabilities of each page were determined. After implementing the dashboard and determining the access levels of users, obtaining a high score from the questions of the usability questionnaire (5 out of 7 points) and obtaining an average score of 71.8 out of 5 questions related to usefulness variables, 70.5 out of 8 questions related to ease of use. And 71 out of 3 questions related to the satisfaction variable showed that the dashboard designed for the hospital had high usability.
Conclusion: Hospital management dashboard information can be a basis for informed decision-making to achieve benefits such as identifying the best performance, improving performance quality, making faster decisions, reducing errors, improving capacity management and work flow, allocating resources and planning for growth and development.
Sara Hashemi, Shahla Faramarzi, Laya Rahmani Pirouz, Azita Yazdani,
Volume 18, Issue 2 (5-2024)
Volume 18, Issue 2 (5-2024)
Abstract
Background and Aim: Burn injury are one of the most common traumas worldwide and the sixth leading cause of death in Iran. The challenges related to the survival rate of burn patients, as well as the associated mortality cases, have led to advancements in the identification of risk factors. Early detection and recognition of these risk factors are essential, and the provision of predictive models can be beneficial. This research was conducted with the aim of reviewing the effectiveness of artificial intelligence in predicting survival in burn patients.
Materials and Methods: This study was a systematic review. A comprehensive search of Scopus, PubMed, IEEE, and Web of Science databases was conducted from inception to July 2023 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Keywords and Mesh terms related to burn, artificial intelligence, survival and prediction were used in the search.
Results: Out of 3599 identified studies, only nine were included in the analysis. Based on the articles reviewed, the effective factors in predicting survival or mortality in burn patients were classified into four main categories: demographic, clinical, tests and co-morbidities. Some of the known effective factors in patient survival, which have been examined in over 40% of studies, include age, gender, total body surface area, inhalation injury, and type of burn. The results showed that in the studies reviewed, the volume of the smallest dataset used in the analyses was 92 samples. In contrast, the volume of the largest dataset used was reported to be 66,611 samples. Among these studies, 33% have indicated that artificial neural network algorithms and random forest show the best performance. The criteria used to evaluate the models in the retrieved studies are diverse.
Conclusion: The use of machine learning algorithms in predicting the survival of burn patients is promising. The results obtained from identified influential factors can assist data science researchers in the data understanding phase and can serve as a roadmap in collecting the initial dataset.
Materials and Methods: This study was a systematic review. A comprehensive search of Scopus, PubMed, IEEE, and Web of Science databases was conducted from inception to July 2023 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Keywords and Mesh terms related to burn, artificial intelligence, survival and prediction were used in the search.
Results: Out of 3599 identified studies, only nine were included in the analysis. Based on the articles reviewed, the effective factors in predicting survival or mortality in burn patients were classified into four main categories: demographic, clinical, tests and co-morbidities. Some of the known effective factors in patient survival, which have been examined in over 40% of studies, include age, gender, total body surface area, inhalation injury, and type of burn. The results showed that in the studies reviewed, the volume of the smallest dataset used in the analyses was 92 samples. In contrast, the volume of the largest dataset used was reported to be 66,611 samples. Among these studies, 33% have indicated that artificial neural network algorithms and random forest show the best performance. The criteria used to evaluate the models in the retrieved studies are diverse.
Conclusion: The use of machine learning algorithms in predicting the survival of burn patients is promising. The results obtained from identified influential factors can assist data science researchers in the data understanding phase and can serve as a roadmap in collecting the initial dataset.
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