Journal of

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Background: vulnerable events could damage structural, non structural and functional components of hospitals that might lead to community crisis, accordingly. Risk assessment is the first step to develop of a hospital disaster plan. In this study, a primary phase of developing a local tool for Iran's hospital disaster risk assessment entitled "Hospital Safety Index (HSI)" was conducted by World Health Organization originally.
Materials and Methods: First, the original index was translated into Farsi in five forms and 145 items. Then a group of four experts from the fields of medicine and engineering assessed the items one-by-one for their relevance and applicability. Revised edition tested three times at Shariati hospital in Tehran. An expert panel also evaluated the feature and content validity of the index. They also weighted the items as well.
Results: Test-retest of the index by two independent research groups found 93% of agreement. Furthermore, 244 points were revised or added to the original edition. The most important changes included: Combining instruction parts with related items for increasing educational properties, completing the list of hazards, developing a plan to analysis, and to present a quantitative and graphic of the model and finally to prepare an educational package as well.
Conclusion: Persian version of HSI, in response to needs of Iranian's health system, represents a rapid no-expensive tool for screening disaster risks at hospitals based on an international template that was tested in several countries. Based on this study, the Farsi index would be evaluated in more hospitals around the country. The assessment results will provide Iranian's health system with evidence-based information for more effective allocated resources and interventions evaluating.

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  Background: In Iran, the rapid growth of urbanization is in a way that it fits into the appropriate location for urban spaces are not switching. The main consequence of this is failure of service delivery and service system to citizens. One of the most important public services that hospitals provide most of the citizens' health. The purpose of this study, “Optimal locating of hospitals in region 7 in Tehran city”.

  Material and methods: This research is descriptive - analytical study has been done. For collecting information and data is used field studies and According to information obtained, To review the study area in terms of access to communication road, green space, away from industrial centers, military, and the fault, as well as for weighting the criteria, is used the AHP model. Then, using a decision model of TOPSIS in GIS software, valuation of criteria has been studied and appropriate maps is prepared, finally map that represents the best location for the construction of hospitals in this area is extracted.

  Results: with combination and overlaying of data layers, the final map was obtained and determined that the northeastern section (Cross Resalat Street and cabli), central (martyr Motahari streets and Miremad) and southeast (Bakhshi fard and part of Damavand street) in district 7 are have priority and more points to construct hospitals.

  Conclusion : System of Multi Criteria Decision Making (MCDM) with GIS can be used as effective tool in site selection of hospitals. Being located of hospitals, near to green spaces and comunication road and its distance from the industrial and military areas as well as the fault, capability of this model in this study is prove.

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Background: Emergency department (ED) is the first place for providing diagnostic and therapeutic services to emergency patients. Due to importance of speed and accuracy in providing services the proper allocation of resources, the department must consider this matter in a particular way. Planning Emergency resources implements regardless of patient overcrowding which occurs at different times. In conclusion the emergency department may faces lack of resources and it results in delay of providing services, a whole mess in functions and decreasing in quality of services. This study is aimed to overcome these problems by suggesting a model for predicting the number of arrival patients at ED. Materials and Methods: The number of arrival patients is predicted based on the data colleted by counting arrival patients and using the data mining technique and neural network model (Multi-layer Perceptron). Results: The number of arrival patients during whole days of a week and 24 hours a day were calculated by sorting out 1, 2 and 3 priorities . The highest number of arrival patients counted was for Saturdays and the lowest for Fridays. Holidays and non-holidays` number of arrival patients differ . The number of arrival patients on formal holidays was similar to Fridays. The highest number of arrivals was between 9 am and 11 and also between 20 pm and 23 pm and the lowest arrivals was between 2 am and 7 am. Conclusion: prediction the number of ED arrival patients can be used for estimating required sources and distributing them appropriately and improving quality of services.