فهرست مطالب

Hospital Research - Volume:7 Issue: 4, 2018
  • Volume:7 Issue: 4, 2018
  • تاریخ انتشار: 1397/09/10
  • تعداد عناوین: 6
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  • Mohammadreza Ghatreh Samani, Seyyed Mahdi Hosseini Motlagh Pages 81-101
    Background

    The efficiency of health system services is a critical measure for societies development. During the last fifty years, the world has witnessed a massive increase in health expenditure, and health-related cost, especially in developing countries, is the main obstacle in the way of advance in health care systems. As a remarkable portion of this cost belongs to blood supply chains, almost any improvement in performance is considered as a critical part of health systems, which contributes to modifying cost-savings and responsiveness policies. 

    Method

    In this paper, a novel multi-criteria decision-making technique is conceptually proposed and presented to location supplementary blood centers so as to prevent disruption to a large extent. In this respect, Grey theory and TOPSIS, a distance-based multiple criteria method, are employed to integrate and evaluate the alternative performance for selecting supplementary blood centers. From a research perspective, TOPSIS method is improved to more effectively tackle grey numbers by presenting a degree of likelihood instead of converting grey numbers into crisp numbers functions, that provides the more flexible ranking procedure.

    Results

    The real data from Tehran blood transfusion center is applied to validate the method and provide insight into its operational execution, obtained results and validity. Overall, this paper found the proposed hybridized methodology to provide relatively consistent results of top-performing alternatives comparing with the more complicated and less intuitively appealing grey-rough set theory approach. 

    Conclusion

    The proposed hybrid methodology is a useful tool for managers, as well as researchers, who seek to evaluate alternative performance in various studies related to multi-criteria decision making. The technique can also be applied in a regular spreadsheet situation, can take into consideration a variety of metrics, both tangible and intangible, and can be devised with a minimal outside effort from decision-makers and be based completely on archival data if necessary.

    Keywords: blood supply chain, Supplementary Blood Center, TOPSIS, Grey Theory, Uncertainty
  • Mahdi Yousefi Nejad Attari Pages 102-115
    Background and Objectives
     One of the key issues in determining location for blood supply center is the design of blood supply chain. To minimize the cost of blood supply, the donors should be reached easily with appropriate distribution of blood and blood products to the hospital. The aim of this study was calculating of the optimal number and location of different various types blood supply centers 
    Methods
     This was mathematical modeling study of potential donors in the East Azerbaijan Province cities. The cost of construction and operation for each facility was calculated based on the activities and after which a mathematical model has been used. Blood supply centers was included fixed centers and mobile teams. Data collection for this study was obtained in March 2014 to September 2015. The mathematical model developed by software 24.1 GAMS 
    Results
     The location of Blood Transfusion Centers in the city of Tabriz in East Azerbaijan province were showed that optimal location for constructing of preparation and processing centers of East Azerbaijan province are cities of Maragheh, Mianeh and Marand. Establishing fixed blood supply centers in the cities of Ahar, Tabriz, Shabestar, Azarshahr, Ajab Shir, Bonab, Malekan, Bostanabad and Sarab had the lowest opening and transportation cost. Therefore, optimal situation for mobile teams were Julfa,Varzaqan,Khodaafarin, Harris, Tabriz, Osku, Maragheh, Khoda Afarin, Hashtrud and Charuymaq.
    Conclusion
     The appropriate allocation of satellite, fixed centers and mobile teams for the cities of East Azerbaijan reduces the cost of supplying blood. Observing this can reduce transportation costs. Therefore, the blood transfusion organization should choose the places to set up the blood supply centers to reduce its costs.
  • The Prediction of Complications of Blood Transfusion in Thalassemia Patients Using Deep Learning Method
    Shirin Dohkt Farhadi, Mohammad Mehdi Sepehri *, Aliakbar Pourfathollah Pages 116-130
    Background and purpose

    Thalassemia is the acute hereditary anemia and the most common hemoglobin disorder in the world. The main treatment for this disease is the persistent blood injection, but the injection of blood can have different complications. These complications affect the quality of life of patients and increase the risk of mortality. Moreover, it increases the use of healthcare services and hospital costs. Predicting the risk of complications before blood transfusion, more appropriate alternative treatment can be selected to prevent or reduce the complications. Moreover, identifying high-risk patients and following them after transfusion provides the possibility of timely interventions. So far, several studies have analyzed the effects of blood transfusion and the risk factors of these complications by statistical methods. However, few studies have attempted to predict these complications. In this study, the risk of post-transfusion complications in thalassemia patients is predicted using machine learning algorithms.

    Method

    The cross-sectional data were collected from 3489 cases in 12 thalassemia centers in Tehran province and 14 thalassemia centers in Mazandaran province in 2018. A set of different classification models including classic and deep learning techniques were trained and studied on this data set.

    Results

    The results showed that machine learning methods have good accuracy to predict the risk of post-transfusion complications. According to the results, the deep learning method has improved the results considerably in comparison to other models (precision=0.21, sensitivity=0.77, f1-score=0.33).

    Conclusion

    In this study, machine learning methods were used to predict the occurrence of post-transfusion complications in thalassemia patients. Finally, the deep learning method produced the best prediction results. Using this method,  of patients who will suffer complications are detected before transfusions. Appropriate alternative methods can be used for treating these patients in order to prevent or reduce transfusion complications.

    Keywords: Thalassemia, Blood transfusion, complication, prediction, Deep Learning
  • Evaluation of Hospital Performance using the Developed BSC Model
    Rouhangiz Asadi, Fatemeh Semnani * Pages 131-149
    Background and objective
    To improve an organization's performance, a suitable model is required as it is not possible to reach the goals without a suitable model. In addition, assessment and review of the programs will not be done effectively without employing a suitable model, and also the organizations could not have effective management on their performance without considering the results of their activities. Using effective tools to evaluate the performance of hospitals as multi-function organizations has always been one of the main challenges of top managers of hospitals. Hospitals are the main places dealing with the life of people from birth to death. Therefore, not only people with different specialties work there but, in some jobs, there is very little agreement among the experts. Therefore, evaluation of hospitals' performance is very important; it can also be complex for such a systematic organization.
    Method
    Hasheminejad Kidney Hospital used the improved and combined Balanced Score Card (BSC) based on the strategic program presented by the top managers in order to evaluate the performance of the hospital. indicators were determined by Delphi method  
    Results
    30 performance indicators were determined by Delphi method in the Strategic committee of the hospital in four perspective scorecards, and then the performance program and project were defined based on the objectives of each aspect.
    Conclusion
    This model can be a useful tool for evaluating and comparing the performance of hospitals. However, this model is flexible and can be adjusted according to differences in the target hospitals. This study can be beneficial for hospital administrators and it can help them to change their perspective about performance evaluation.
    Keywords: Balance Score Card (BSC), Performance Assessment, Cascading, Hospital
  • Optimal Site Selection of Hospital Using Fuzzy TOPSIS (Case Study in Malayer City)
    Mostafa Ebrahimi, Javad Behnamian *, Meysam Rabiee Pages 131-176
    Background and Objectives

    Building new service centers requires many expenses, and health-care uses are one kind of this field that it`s distribution on the city and specifying the optimal place for it is so important in order to give every citizen the best performance. Malayer is one of the cities of Hamedan in Iran that doesn't have suitable health-care and the hospital distribution, and by considering the increase in population, and need to fast access to the hospital, selecting the proper position become more important. In this paper, Malayer is chosen as a case study. This research aims to study on selecting the appropriate place by considering qualitative criteria and presenting the appropriate model for Malayer.

    Methods

    In this research, we tried to choose the optimal place to build a hospital in Malayer by using the ordinary fuzzy decision-making method. The parameters that are taken into account are population density, distance to other hospitals, access to main roads, and distance to industrial and military centers. These parameters are combined ordinary by fuzzy TOPSIS.

    Results

    Results indicate that constructed hospitals in Malayer do not match with position-selecting criteria.

    Conclusion

    This important point shown by this research is some regions of the town have no health service. In contrast, the citizens placed in the other areas receive more suitable services and the number of hospitals needed at the moment for Malayer is six.

    Keywords: Site Selection, Hospital, Multi-Criteria Decision-Making, Fuzzy TOPSIS
  • Dynamic Analysis of Environmental Factors Affecting Health Costs Applying a System Approach (Case Study: Zanjan City, Iran)
    Nasim Ghanbar Tehrani *, Ahmad Hashemi, Mohammad Vahid Sebt Pages 150-175
    Background and objective

    Today, due to the growth of technology in various societies and in line with the industrialization of the global community, environmental issues are becoming a serious threat to human health and consequently, to the economy of the international community. The city of Zanjan, as a case study of this research, has been witnessing various civil protests in this regard and over the past years due to environmental concerns.

    Methodology

    System Dynamics (SD) methodology is applied to simulate the dynamics of environmental pollutions of the various industries affecting health costs. Dealing with SD, study has been applying content analysis technique to select the most repetitive variables applied with similar studies which led study to the early mental model (causal loop diagram). Interview with experts is the next step which would assist the study to make the early dynamic model. The modified dynamic model has been grasped as the structural validation is conducted within 4 divisions of boundary adequacy test, extreme condition test, dimensional consistency test and parameter assessment test. Finally, the secondary validation including: behavior replication test and family tests have been assessed to assure the compliance of model outputs with the historical records.

    Results

    According to the simulation, the most prior recommendations are: "Long-term policies for less utilization of non-renewable resources", "Increasing the life of industrial capital through the promotion of maintenance and repair departments", "Replacing fossil fuels with natural gases and enhancing their combustion quality" and "desertification policies to combat the release of solid PM10 particles".

    Conclusions

    Based on the results of the study, long term policies to find out the appropriate tradeoff for exploitation of renewable and nonrenewable energies in order to minimize their pollution will have a bigger effect on the citizen’s health costs comparing other policies like desertification.

    Keywords: Pollutant, Environmental, Health cost, System dynamic