Journal of Health Administration
Year:2023 | Volume:25 | Issue:4|Papers Count:12

Introduction: To improve the capabilities of general practitioners (GPs), who constitute an essential segment of the healthcare system in Iran, it is necessary to identify their information needs about Persian medicine. This survey-based study aimed primarily to determine the information needs of GPs in Isfahan city about Persian medicine, and secondarily to evaluate the assocaition between their workshop attendance and information needs. Methods: This applied study employed a descriptive survey research method. The research population consisted of all GPs in Isfahan city, out of which a sample of 204 participants was selected using stratified random sampling. The data collection tool was a researcher-made questionnaire, containing seven different domains related to Persian medicine. The questionnaire was distributed among the participants after its validity, content, and reliability were confirmed. All descriptive and inferential statistical analyses were performed using SPSS version 21. Results: A total of 177 GPs completed the questionnaire. The mean information need score was found to be highest for the domain of nutritional substances (72. 2) and lowest for the domain of treatment measures (61. 7). There was no significant relationship between the participants’,information needs and their age, work experience, gender, and employment status. However, variables such as previous participation in Persian medicine workshops and the desire to participate in future workshops exhibited a significant relationship with information needs. Conclusion: Responsible officials at the Iranian Ministry of Health and Medical Education (such as the deputies for public health and curative affairs) and traditional medicine specialized groups should periodically hold training workshops to meet GPs’,information needs. It is also necessary to repeat retraining courses for GPs at regular intervals.

Introduction: Jaundice is one of the most common problems in the neonatal period, affecting about 60% of full-term and 80% of premature infants in their first week of life. The present study aimed to develop a system for predicting neonatal jaundice within the first 24 to 72 hours post-delivery by using the Support Vector Machine (SVM) algorithm. Methods: This applied-developmental study employed a quantitative method. First, based on a literature review, a questionnaire containing effective factors for predicting jaundice in newborns was designed. Data analysis was performed using descriptive statistics, and factors that were recognized as necessary by at least 50% of the experts were included in the model. Then, data from 1178 newborns delivered at Lolagar hospital in Tehran were extracted from birth records, and several machine learning algorithms were used to predict neonatal jaundice. Results: The findings of this research showed that the proposed model based on the SVM algorithm is the best output due to the distance between classes. Therefore, the final model of the SVM algorithm was created using the Gaussian kernel, with a sigma value of 1. 2360605. Thirty percent of the samples (354 cases) were tested, and 321 cases were correctly predicted. In the proposed SVM model, parameters such as precision, the area under the Receiver Operating Characteristic (ROC), and F1 score were 92. 7%, 93%, and 88% respectively. Conclusion: Incorporating SVM into a system for predicting jaundice in newborns can aid doctors with timely prediction of jaundice in newborns and provide the possibility of taking preventive measures and preventing possible risks caused by jaundice in newborns.

Introduction: Induced demand is the phenomenon where healthcare providers, especially physicians, stimulate demand for unnecessary healthcare services by exerting their influence on patients. Induced demand increases healthcare expenditure and reduces healthcare system efficiency. Therefore, this study aimed to identify strategies for reducing induced demand in the healthcare system. Methods: In the present scoping review, all published articles on strategies to reduce induced demand in the healthcare system until February 11, 2023, were searched and collected from nine English and Farsi databases and the Google Scholar search engine. Finally, 36 documents were reviewed and analyzed using MAXQDA software. Results: Overall, 44 strategies to reduce induced demand in the healthcare system were identified and grouped into three levels: macro (healthcare system), meso (healthcare organizations), and micro (healthcare providers and recipients). The most frequent strategies to reduce induced demand included using an appropriate referral system, following clinical guidelines, adopting fixed and pay-for-performance methods of payment to healthcare providers, setting a ceiling on the number of services physicians can offer, enforcing healthcare providers’,compliance with medical ethics, training healthcare providers and recipients, and monitoring and control. Conclusion: Induced demand for health services has a complex nature and is influenced by the behavior of policymakers, healthcare providers, payers, and patients. Therefore, strategies to reduce induced demand should be applied at the three levels of healthcare system, healthcare organizations, and healthcare providers and recipients to achieve better results.

Introduction: Innovation in healthcare organizations is essential to provide high-quality patient care. The theories of leadership and innovation have established a strong relationship between leadership styles and organizational innovation. The study examined the relationship between leadership styles and organizational innovation in the healthcare sector as perceived by medical doctors. The mediating effect of organizational culture on relationships was also tested. Methods: This applied study employed a cross-sectional survey design and data was collected using an online and standard questionnaire. A proportionate stratified random sampling technique was used to draw a sample from the population that consisted of medical doctors working full-time for the five largest public sector hospitals in Lahore, Pakistan. Data analysis was conducted by descriptive and inferential statistics (Structural Equation Modeling (SEM) and confirmatory factor analysis) using SPSS and Smart-PLS software. Results: The results suggested that there are significant and positive relationships between leadership styles and organizational innovation (p = 0. 000, p = 0. 030). The indirect path analysis of mediation revealed that organizational culture mediated the relationship between the three leadership styles and organizational innovation (p<0. 001). However, the direct effect of transformational leadership and ambidextrous leadership on organizational innovation became insignificant (p>0. 05) after incorporating organizational culture as a mediator, proving its impact on innovation. Conclusion: This study provides evidence of the significance of paying attention to the leadership style of healthcare supervisors as it potentially has an impact on administrative and technological innovation. The study provides empirical evidence to healthcare managers and policymakers on the essential traits of healthcare supervisors who can promote innovation. The study also provides evidence of the importance of a supportive workplace culture that promotes innovative behaviors among medical doctors.

Introduction: The outbreak of Covid-19 canceled unnecessary hospital admissions. Therefore, hospitals face economic consequences. In this context, this research has investigated the effect of the Corona virus pandemic on the revenue of a hospital in Tehran. Methods: This study is retrospective interrupted time series studies. In this time series study, the monthly revenue of all services provided by a hospital in Tehran was collected and analyzed in the form of a census in two groups before and during the Covid-19 outbreak. Data analysis was done using Eviews. Chow test was used to detect structural breaks in the studied time series. Results: The findings of this study showed that the outbreak of Covid-19 reduced the revenue of all hospital services. According to the negative coefficient of the variable of the Covid-19 period and the regression coefficient, it indicates the existence of a negative relationship between the total revenue of the hospital and the prevalence of Covid-19. After the outbreak of Covid-19, the revenue of laboratory services and internal services decreased by 50% compared to the previous year after the outbreak of Covid-19 and continued to decrease by 20%. Conclusion: The results of the study showed in the Covid-19 pandemic, with the change of admission priorities, the number of referrals decreased due to the fear of the hospital being infected with financial shocks. it is suggested that the hospital managers take action to train the forces, improve service productivity, reduce costs, and make optimal use of potential financial and human resources during the peace period.

Introduction: The supply chains of medical equipment and necessities in healthcare centers are highly complex, diverse, and dynamic, making optimal selection and purchase a specialized and challenging task. This research aimed to design an intelligent decision support system that could aid the expertise process of purchasing medical supplies. Methods: In this developmental-applied and descriptive-survey study, we used artificial intelligence, fuzzy sets, and neural networks as well as MATLAB software to design a model that could simulate the decision-making process of experts in the purchase of medical supplies by predicting the score of medical supplies after obtaining information. The required data was extracted from the website of the General Directorate of Medical Equipment and Knowledge of Specialists in 2022. Results: The results showed that a three-layer perceptron neural network, with a mean square error of 0. 0011 and an overall correlation of 0. 97, could be used as a suitable decision aid in the evaluation and selection of medical supplies. Conclusion: The use of an intelligent decision support system can greatly aid the expertise process of purchasing medical supplies, thus helping the healthcare system to preserve resources and improve the quality of healthcare services. The high speed and accuracy of processing data by using neural networks, one of the most effective methods for learning and generalizing, can assist experts in purchasing medical supplies and lead to optimal decisionmaking.

Introduction: Methodological validity is one of the aspects of quality. Methodological elements are parts of the text of articles that deal with research methodology. The purpose of this study was to determine the contribution and role of methodological elements in explaining the relationship between evidence and questions. Methods: This semi-experimental study employed a one-group pretest–,posttest design. The research population consisted of clinical trial articles included in the meta-analysis of Cochrane systematic review articles. The sampling method employed was purposeful, whereby systematic review articles containing at least 50 related clinical trial articles retrieved by the retrieval system were selected as the research sample. Results: The results of the paired t-test showed that the difference in the average nDCG score across all four groups was negative at all points of accuracy. The highest average difference (−, 0. 064) was observed for the basic and standard methodological elements in the abstract at accuracy point 10 (the tenth document in the retrieved results), while the lowest average difference (−, 0. 021) was observed for the basic methodological elements in the abstract at the 50th and 70th accuracy points. Conclusion: The findings of this research showed that methodological elements, whether independently or to expand the abstract, do not affect the ranking of relevance results or may even have a negative effect. In other words, the occurrence of methodological elements in the text or their weighting can reduce relevant results.

Introduction: Hypertension is one of the most common cardiovascular diseases worldwide. Self-care ability in patients with hypertension can be influenced by various factors, such as health literacy. The aim of this study was to determine the relationship between health literacy and self-care ability in patients with hypertension. Methods: This cross-sectional descriptive correlational study employed a convenience sampling method to investigate 120 hypertensive patients referred to medical centers in Sanandaj, Iran, between November 2018 and February 2019. The inclusion criteria included age between 30 and 75 years, diagnosis of hypertension by a specialist, and diagnosis of hypertension at least six months ago. A demographic characteristics checklist and standard hypertension self-care questionnaires (HSCALE) and Adult Health Literacy Assessment (HELIA) were used to collect data. Data were analyzed with SPSS version 16 software. A significance level of 0. 05 was considered. Results: The mean and standard deviation of patients' self-care scores and health literacy were 56. 1 , ±,  , 8. 6 and 117 , ±,  , 25. 2, respectively. There was a positive and significant correlation between the mean scores of self-care and health literacy (r , = , 0. 409, P , = , 0. 001), with health literacy scores increasing in line with a rise in self-care scores. Conclusion: Considering the observed relationship between health literacy and self-care, it seems necessary to perform educational interventions aimed at promoting the health literacy of patients with hypertension.