Background: Road traffic accidents in Iran are a critical issue that hinders economic development and one of the main threats to the health and safety of people in the community. The statistics indicate that after cardiovascular diseases, traffic accidents are the second leading cause of death in different age groups, which reflects the necessity of prediction in this area. Materials and Methods: The present study investigated the data of the traffic-accident injured people between April 2009 and March 2012 in Golestan, Mazandaran, Guilan, and Ardebil provinces, presented to forensic medicine. We used the Box-Jenkins method as one of the most advanced methods in prediction and future studies in the field of health systems, to estimate the number of injuries by province, for the years 2016 to 2019. Results: The obtained results suggested the appropriate time series patterns for predicting injured people in Golestan Province with Autoregressive Integrated Moving Average (ARIMA)
Background: Any accident is a disturbance in the balance between the human system, vehicle, road and environment. Future prediction of traumatic accidents is a valuable factor for managers to make strategic decisions in the areas of safety, health and transportation. Materials and Methods: In this study, by using Grey Model (GM) (1.1), Rolling Grey Model (RGM), Fourier Grey Model (FGM) (1.1), survival modification model, ARIMA time series, harmonic pattern and statistical data, the number of traffic injuries referred to forensic medicine centers in Semnan Province between 2017 and 2020 were predicted based on the number of traffic injured in Semnan Province from March 2009 and March 2016. Results: The mean absolute error percentage for the GM (1.1), RGM (1), FGM (1.1), survival model, ARIMA and harmonic models were 0.994, 0.082, 0.091, 0.105, 0.05, 0.11, respectively, indicating a greater accuracy of the ARIMA method, compared to the other methods. The number of road traffic injuries in Semnan Province is decreasing and will reach 4052 in 2020. Conclusion: ARIMA model is the best method of the future studies model for the number of injured patients referred to the forensic medicine centers in Semnan Province compared to other studied methods. Future studies model shows that the injuries caused by accidents in the province of Semnan are decreasing
Background: Educational planning and managing critical situations of accidents and disasters are among the most important issues. Triage, which means the classification of patients and injuries based on specific situations and needs, is one of the important tasks of hospitals at times of disasters. In this study, triage knowledge and practice of nurses working in hospitals affiliated to Ilam University of Medical Sciences are evaluated. Materials and Methods: This is a cross-sectional and analytic study conducted in 2017. The statistical population comprised all nurses working in Ilam Medical Sciences hospitals. Using Cochran's formula, 174 people were sampled and 160 of them completed the study questionnaires and returned them. The main tool of collecting data was a researcher-made questionnaire based on Canadian triage scale. Validity of the questionnaire was assessed by 10 members of the Ilam University of Medical Sciences. The reliability of the questionnaire was between 0.83 and 0.89 using Cronbach α coefficient. The obtained data were analyzed using descriptive and inferential statistics in SPSS. Results:The Mean±SD duration of nurses' working in the emergency department was 5.2±3.4 years, of which 46.2% had an experience of using triage. The Mean±SD score of nurses' knowledge and practice of triage were respectively 10.44±2.11 and 9.22±2.14 out of 15. There was no significant relationship between work experience, gender and age with knowledge and practice of triage, but there was a significant relationship between knowledge and practice of nurses about triage with nursing educational degree. Conclusion:The level of nurses' knowledge and practice of triage in hospitals of Ilam University of Medical Sciences is moderate.
Introduction: One of the factors that increases competitive ability is to improve the quality of presented service in organizations such as hospitals. Providing superior services through maintaining high quality is a prerequisite for the success of service organizations. The SERVQUAL model is one of the most commonly used tools for measuring service quality satisfaction. So the aim of this study was to assess the quality of services of selected hospitals through the SERVQUAL model. Materials and Methods: This study was a descriptive-analytical study that conducted in 2016. The population of the study consisted of all patients which needed to outpatient care services and referred to selected hospitals. Using Morgan's table, the sample size was 398, of which 381 completed questionnaires. The main tool of this research was questionnaire based on SERVQUAL model. Data were analyzed by SPSS version 19 using descriptive statistics methods and descriptive inferential methods for explaining the research hypotheses. Results: Pearson correlation test was showed that there is a direct relationship between perceived service and patient satisfaction. About responsiveness: high response rate, about empathy dimension: quite location, physical factors: possessing suitable space for waiting, from reassurance: providing accurate information to patients, and about reliability: personnel's timeliness has the greatest impact on patient satisfaction. Also, reliability
In this paper, the notion of the q -duality mappings in locally convex spaces is introduced. An implicit method for finding a fixed point of a Q -nonexpansive mapping is provided. Finally, the convergence of the proposed implicit scheme is investigated. Some examples in order to illustrate of the main results are presented.
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