Analysis of the Distribution of Medical Services and the Optimal Location of the Hospital in District 4 of Tehran Metropolis

Considering the population density in Tehran as the capital of the country, the sensitivity of hospital use and its effective role in ensuring the health of the individual and society, the importance of identifying suitable locations for hospital construction is one of the priorities of urban planning and design. District 4 of Tehran is known as one of the most populous, extensive, immigrant and most construction areas in Tehran. The purpose of this study is to select a suitable location for the establishment of hospital centers and to investigate the optimal distribution of hospitals in District 4 of Tehran using new methods, models and according to the effective criteria in locating medical centers. In this research, first, descriptive-analytical method was used to collect information and effective indicators in locating hospital centers were extracted. Then, using Analysis Network Process, the purpose, criteria and sub-criteria were examined and finally the layers were analyzed. Then, using ArcGIS software and the overlap model, suitable centers for the construction of the hospital were determined. Among the locations extracted, the most suitable location for the construction of the hospital was determined using the colonial competition algorithm (ICA) and the implementation of this algorithm in Matlab software. Then, using the Q method, statements related to the desirability of the final location were extracted. Also, by asking experts about the propositions related to the desirability of the chosen location, 13 propositions were extracted and categorized into 5 attitudes using exploratory factor analysis in SPSS software. So that 53.84% of the participants were in the view of group 1, 15.38% in the view of group 2, 15.38% in the view of group 3, 7.69% in the view of group 4 and 7.69% in the view of group 5. The first view of the desirability of distance from airports, stadiums, green space, telecommunication towers, radio, television, gas stations and similar centers, police stations and law enforcement, the second view of the desirability of distance from other health centers and hospitals As well as educational spaces, the third view of desirability in terms of distance from industrial centers and pollution sources, the fourth view of desirability in terms of distance from military centers and bus terminals, etc. and the fifth view of desirability of distance from main communication routes and densely populated centers Is included. Attitude one has the highest and attitude five has the lowest  value

A Hybrid Multi-Criteria Analysis Model for Solving the Facility Location–Allocation Problem: a Case Study of Infectious Waste Disposal

Choosing locations for infectious waste disposal (IWD) is one of the most significant issues in hazardous waste management due to the risk imposed on the environment and human life. This risk can be the result of an undesirable location of IWD facilities. In this study a hybrid multi-criteria analysis (Hybrid MCA) model for solving the facility location–allocation (FLA) problem for IWD was developed by combining two objectives: total cost minimization and weight maximization. Based on an actual case of forty-seven hospitals and three candidate municipalities in the northeastern region of Thailand, first, the Fuzzy AHP and Fuzzy TOPSIS techniques were integrated to determine the closeness of the coefficient weights of each candidate municipality. After that, these weights were converted to weighting factors and then these factors were taken into the objective function of the FLA model. The results showed that the Hybrid MCA model can help decision makers to locate disposal centers, hospitals and incinerator size simultaneously. Besides that the model can be extended by incorporating additional selection criteria/objectives. Therefore, it is believed that it can also be useful for addressing other complex problems

The Spatial Allocation of Hospitals With Negative Pressure Isolation Rooms in Korea: Are We Prepared for New Outbreaks?

Background: Allocation of adequate healthcare facilities is one of the most important factors that public health policy-makers consider when preparing for infectious disease outbreaks. Negative pressure isolation rooms (NPIRs) are one of the critical resources for control of infectious respiratory diseases, such as the novel coronavirus disease 2019 (COVID-19) outbreak. However, there is insufficient attention to efficient allocation of NPIR-equipped hospitals. Methods: We aim to explore any insufficiency and spatial disparity of NPIRs in South Korea in response to infectious disease outbreaks based on a simple analytic approach. We examined the history of installing NPIRs in South Korea between the severe acute respiratory syndrome (SARS) outbreak in 2003 and the Middle East respiratory syndrome coronavirus (MERS-Cov) in 2015 to evaluate the allocation process and spatial distribution of NPIRs across the country. Then, for two types of infectious diseases (a highly contagious disease like COVID-19 vs. a hospital-based transmission like MERS-Cov), we estimated the level of disparity between NPIR capacity and demand at the sub-regional level in South Korea by applying the two-step floating catchment area (2SFCA) method.Results: Geospatial information system (GIS) mapping reveals a substantial shortage and misallocation of NPIRs, indicating that the Korean government should consider a simple but evidence-based spatial method to identify the areas that need NPIRs most and allocate funds wisely. The 2SFCA method suggests that, despite the recent addition of NPIRs across the country, there should still be more NPIRs regardless of the spread pattern of the disease. It also illustrates high levels of regional disparity in allocation of those facilities in preparation for an infectious disease, due to the lack of evidence-based approach.Conclusion: These findings highlight the importance of evidence-based decision-making processes in allocating public health facilities, as misallocation of facilities could impede the responsiveness of the public health system during an epidemic. This study provides some evidence to be used to allocate the resources for NPIRs, the urgency of which is heightened in the face of rapidly evolving threats from the novel COVID-19 outbreak

An Optimization Approach to Improve Equitable Access to Local Parks

Local parks are public resources that promote human and environmental welfare. Unfortunately, park inequities are commonplace as historically marginalized groups may have insufficient access. Platforms exist to identify the geographical areas that would benefit from future park improvements. However, these platforms do not include budget, infrastructure, and environmental considerations that are relevant to park location decisions. To support recreational and government agencies in addressing inequities in the distribution and quality of parks, we propose a mixed-integer program that minimizes insufficient access, defined as weighted deviations across multiple categories. We consider an equity-focused min-max objective and an overall objective to minimize total weighted deviations. We apply the model to a case study of Asheville, North Carolina. We conduct extensive data collection to parameterize the model. In policy analyses, we consider the effects of available budget, planning horizons, strategic demographic priorities, and thresholds of access. The model reflects user-defined criteria and goals, and the results suggest that the framework may be generalizable to other cities. This study serves as the first step in the development and incorporation of mathematical modeling to achieve social goals within the recreational setting

Assessing performance in health care: A mathematical programming approach for the re-design of primary health care networks

Mathematical models allow studying complex systems. In particular, optimal facility location models provide a sound framework to assess the performance of first-level of health care networks. In this work, a methodology founded on need/offer/demand quantification through a facility location-based mathematical model is proposed to assess the performance of existing networks of Primary Health Care Centers (PHCC) and assist in its re-design. The proposed re-design problem investigates the re-allocation of existing resources within the given infrastructure (existing PHCCs) to better satisfy the estimated health needs of the target population. This problem has not been widely addressed in the open literature despite its paramount importance in modern societies with fast demographic dynamics and constrained investment capacities. The model seeks to optimally assign the required type of service and the corresponding capacity to each PHCC (offer). The objective function to be maximized is the number of (needed) patients’ visits effectively covered by the network (demand). The following constraints are explicitly considered: i) geographic accessibility from need centers to PHCCs, ii) maximum delivery capacity of each service in each PHCC, and iii) total budget regarding fixed, variable, and relocation costs. The proposed methodology was applied to a medium-size city. Results show that the non-attended necessity can be reduced by introducing capacity modifications in the existing network. Moreover, different solutions are obtained if budgetary restrictions or minimum attention volume constraints are included. This reveals how model-based decision support tools can help health decision-makers assessing primary health care network performance.Fil: Elorza, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaFil: Moscoso, Nebel Silvana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaFil: Blanco, Anibal Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentin

Distribuição dos utentes na Rede Nacional de Cuidados Continuados Integrados do Alentejo

Mestrado em Decisão Económica e EmpresarialEsta pesquisa aborda a Rede Nacional de Cuidados Continuados Integrados (RNCCI) em Portugal, focando-se na especialidade de unidade de cuidados continuados de internamento com o objetivo de criar uma distribuição dos utentes pelas unidades da zona do Alentejo. Após recolha dos dados, disponibilizados na internet, procedeu-se ao seu estudo e tratamento. Seguidamente, num ambiente de planeamento a nível tático, procedeu-se à distribuição dos utentes conforme a área inserida no estudo e a quantidade de camas que cada zona da referida área tem disponível ao ano. Esta distribuição foi feita minimizando o custo total de internamentos nas respetivas zonas, custo este que contabiliza as despesas relacionadas com o transporte e internamento para todas as unidades abrangidas pelo estudo. De modo a aplicar os conhecimentos adquiridos no mestrado, no que toca a Investigação Operacional, utiliza-se neste estudo um modelo de otimização, particularmente, um modelo de tipo de transportes de programação linear.O software utilizado na resolução do problema foi o Solver do Microsoft Office Excel. Com esta abordagem ao problema de planeamento de distribuição de utentes na RNCCI do Alentejo, pretende-se dar ênfase ao progresso da RNCCI em Portugal, disponibilizando uma ferramenta que pode ser usada pelos gestores no âmbito da saúde.This research reports the National Network for Continuous Care (RNCCI), in Portugal, focusing on admission of patients in continuous care units. The intent of this work is to create a distribuition network for users of the Alentejo region. After data collection, available on the internet, we proceeded with the study and treatment of data. Afterwards, in the tactical planning setting, we proceeded with the distribution of users depending on the residential area and the number of beds available per year in each zone. This distribution was performed to reduce the total cost of hospitalization, a cost wich covers expenses related to transport and admission in the units covered by the study. In order to deepen the knowledge acquired in the master degree courses, with respect to operational research, in this study an optimization model is developed a linear programming transportation problem. The software used for solving the problem was the Solver of Microsoft Office Excel. With this approach to the problem of planning the distribution of users in the RNCCI of Alentejo region, we intend to emphasize the progress of the RNCCI in Portugal, and provide a tool that can be used by health policy makers.info:eu-repo/semantics/publishedVersio

Disease diagnosis in smart healthcare: Innovation, technologies and applications

To promote sustainable development, the smart city implies a global vision that merges artificial intelligence, big data, decision making, information and communication technology (ICT), and the internet-of-things (IoT). The ageing issue is an aspect that researchers, companies and government should devote efforts in developing smart healthcare innovative technology and applications. In this paper, the topic of disease diagnosis in smart healthcare is reviewed. Typical emerging optimization algorithms and machine learning algorithms are summarized. Evolutionary optimization, stochastic optimization and combinatorial optimization are covered. Owning to the fact that there are plenty of applications in healthcare, four applications in the field of diseases diagnosis (which also list in the top 10 causes of global death in 2015), namely cardiovascular diseases, diabetes mellitus, Alzheimer’s disease and other forms of dementia, and tuberculosis, are considered. In addition, challenges in the deployment of disease diagnosis in healthcare have been discussed