Integrating expected coverage and local reliability for emergency medical services location problems

Daskin's MEXCLP model [Daskin M. A maximum expected covering location model: formulation, properties, and heuristic solution. Transportation Science 1983;17:48-70] was one of the first efforts to capture the stochastic nature of emergency medical services (EMS) location problems within a mixed-integer formulation. With their subsequent introduction of MALP, ReVelle and Hogan [The maximum availability location problem. Transportation Science 1989;23:192-200] offered two key advances, local vehicle busyness estimates and the α-reliability objective. While these constructs have influenced many subsequent EMS location models, they have been subjected to relatively little empirical analysis. To address this, we introduce the LR-MEXCLP, a hybrid model combining the local busyness estimates of MALP with the maximum coverage objective of MEXCLP. We then solve a series of problems with all three models and employ simulation to estimate aggregate service levels. We find that LR-MEXCLP leads to modest but consistent service gains over both MALP and MEXCLP. These results support the merits of local busyness estimates, but they also suggest that the α-reliability objective may be inappropriate when seeking to maximize aggregate system response capabilities. More generally, our research underscores the utility of (a) linking modeling assumptions and goals with real-world application contexts, and (b) employing simulation or other techniques to validate theoretical results.     

Modeling mobile health service delivery to Syrian migrant farm workers using call record data

A significant number of Syrian refugees under temporary protection in Turkey work in agriculture seasonally in various rural areas during several months a year. These migrant farm workers and their families are deprived of access to the regular health care system and preventive services due to their remote locations. The government supports the delivery of different types of mobile health care services, such as vaccination for children, reproductive health and screening services. While planning the mobile health care service delivery, it is critical to know where the refugees will work during what time frame; hence the demand for the services. By analyzing the call record data of a major mobile network operator in Turkey, we quantify the increase in the volume of calls made by Syrian refugees in various agricultural areas during the harvesting season of local crops. This information helps us to forecast spatial and temporal distribution of demand for mobile health care services at a fine granularity. Taking demand over multiple periods as input into a mathematical programming model, we optimize the routing of mobile clinics that visit locations close to where refugees are concentrated over the given planning horizon. We consider three hierarchical objectives. Given the availability of a number of mobile clinics at community health centers in the districts, the first objective aims to maximize the percentage of refugees that can benefit from each service type within pre-defined close distances. The second objective minimizes the number of clinics needed while covering the maximum percentage of refugees. The third objective minimizes the total travel distance of the clinics, while keeping the maximum coverage level using a minimum number of clinics to achieve this level. We quantify the benefits of centralized planning (by the province directorate) over decentralized planning (by each district separately). We also show the trade-off between the required number of clinics and coverage of potential patients.     

Efficiency analysis of emergency departments in metropolitan areas

The demand in the healthcare industry is increasing exponentially due to aging population of the world and this is leading to a rapid increase in the cost of healthcare. The emergency departments of the hospitals are the frontline of health care systems and play an additional critical role in providing an efficient and high-quality response for patients. The overcrowding at the emergency departments due to growing demand results in a situation where the demand for ED services exceeds the ability to provide care in a reasonable amount of time. This has led countries to reconsider their health policies in a way to increase their efficiency in their healthcare systems in general and in emergency departments, in particular. As in many countries, there has been a steady and significant increase in the number of patients that seek health services at the emergency departments of state hospitals of Turkey, due to the significant structural reforms in health services since 2003. While meeting this increasing demand, it is ever more important to provide these critical health services efficiently. Therefore, the efficiency of the emergency departments of seven general hospitals run by Istanbul's Beyoglu State Hospitals Association have been analyzed using categorical Data Envelopment Analysis (DEA) models. The analysis of DEA results is supported by a set of statistical methods to make it easier for the hospital administrators to interpret the analysis and draw conclusions. The analysis shows that less-equipped EDs are supported by better equipped, larger EDs, resulting in a hub-and-spoke type of structure among the EDs where “satellite” EDs serve an important referral function and thus evaluating their efficiency without taking the interoperability among these units into account would not be an accurate assessment of their performance.     

Analyzing the volume and nature of emergency medical calls during severe weather events using regression methodologies

An effective emergency medical service (EMS) response to emergency medical calls during extreme weather events is a critical public service. Nearly all models for allocating EMS resources focus on normal operating conditions. However, public health risks become even more critical during extreme weather events, and hence, EMS systems must consider additional needs that arise during weather events to effectively respond to and treat patients. This paper seeks to characterize how the volume and nature of EMS calls are affected during extreme weather events with a particular focus on emergency preparedness. In contrast to other studies on disaster relief, where the focus is on delivery of temporary commodities, we focus on the delivery of routine emergency services during blizzards and hurricane evacuations. The dependence of emergency service quality on weather conditions is explored through a case study using real-world data from Hanover County, Virginia. The results suggest that whether it is snowing is significant in nearly all of the regression models. Variables associated with increased highway congestion, which become important during hurricane evacuations, are positively correlated with an increased call volume and the likelihood of high-risk calls. The analysis can aid public safety leaders in preparing for extreme weather events.     

Siting a facility in continuous space to maximize coverage of a region

Siting facilities in continuous space such that continuously distributed demand within a region is optimally served is a challenging location problem. This problem is further complicated by the non-convexity of regions typically encountered in practice. In this paper a model for maximizing the service coverage of continuously distributed demand through the location of a single service facility in continuous space is proposed. To address this problem, theoretical conditions are established and associated methods are proposed for optimally siting a service facility in a region (convex or non-convex) with uniformly distributed demand. Through the use of geographic information systems (GIS), the developed approach is applied to identify facility sites that maximize regional coverage provided limitations on facility service ability.     

Simulation modeling and optimization for ambulance allocation considering spatiotemporal stochastic demand

To ensure a timely response to emergencies, governments are obliged to implement effective ambulance allocation plans. In practice, an emergency medical service (EMS) system works in an uncertain environment, with stochastic demand, response-times, and travel-times. This uncertainty significantly affects ambulance allocation planning. However, few studies in this field adequately consider the effect of spatiotemporal uncertainty in demand, because it is difficult to measure it quantitatively. As a result, few analytic models capture the dynamic nature of an EMS system and, thus, the allocation plans they generate are not efficient in practice. Therefore, this study proposes a simulation-based optimization method for ambulance allocation. A simulation model is constructed to mimic the operational processes of an EMS system, and to evaluate the performance of an ambulance allocation plan in an uncertain environment. Gaussian mixture model clustering is used to derive the uncertain spatial demand. Then, the simulation generates emergency demand based on the obtained spatial distribution. A Gaussian-process-based search algorithm is used together with the simulation model to identify optimal solutions. To validate the proposed method, a case study is conducted using data on emergency patients in the Shanghai Songjiang District. Compared with the current plan adopted in Songjiang, the experimental results demonstrate that the delay time and frequency of the EMS system can be reduced significantly by employing the proposed methods. Furthermore, nearly 41% of the allocation cost can be saved.     

Measuring the spatial accessibility to fire stations using enhanced floating catchment method

Enhancing the spatial accessibility of population to fire services is a key strategy to help improve emergency response, minimise property loss, and reduce injuries and deaths. Given its significance for fire service policy and strategic planning, we draw on small area population forecasts, fire station locations and the road network, and employ the enhanced two-step floating catchment method to compute the levels of spatial accessibility of population to fire services in relation to current and future population growth in Brisbane, Australia. Results show that lower levels of spatial accessibility to fire services exist in the most populated areas compared to those that are least populated. Further, we reveal that some areas are more likely to suffer a reduction in spatial accessibility than others. Spatial accessibility of population to fire services over the period to 2036 is likely to reduce as a consequence of rising demand for service. The identification of locales that experience lower levels of accessibility to fire services will enable fire services agencies to strategically plan infrastructure investment and help enhance the operational efficiency of emergency response.     

An optimization model for planning community health services.

This article reports results of a project to develop methods of planning health care delivery for a community with emphasis on ambulatory services in a health maintenance organization setting. Some of the special difficulties of the problem are discussed and a linear optimization model is presented that addresses the problem of planning the ambulatory service mix for a specified population. The model accounts for population characteristics, financial data, and system dynamics (including referral patterns). An application is shown for the case of a “model cities” population in Buffalo, New York, and some implications for further research are presented.     

A paradigm for location and multidimensional problems in planning

Several theories, concepts, methods, or alternatively, “paradigms” have been suggested for the explanation and prediction of the location behavior of urban households. Increasingly, hwoever, “behavioral” approaches to the explanation of the dimensions of “choice” and/or exploration of alternative hypotheses have been cumbersome in the “mechanistic” paradigms of the social system and its related subsystems.An alternative paradigm of Analytic Hierarchy Process (AHP) is proposed to explore alternative structural specification hypotheses (sequential versus simultaneous) on the grouping and changing relative importance of “instrumental” and “non-instrumental” factors affecting location decision-making. AHP estimates of the “locational shares” of an urban (corridor) zonal population provide a paradigmatic basis for behavioral, vis-a-vis environmental, explanation of location decision-processes in a methodologically efficient, robust and theoretically inclusive framework of hierarchy systems.This paradigm is proposed for locational analysis requiring an effective integration of multilevel, environmental (contextual) and behavioral measures of relative importance, with limited data, and, for multidimensional problems in planning and policy-making, formidably requiring the integration of positive with normative analysis of systems.     

Data-driven forecasting for operational planning of emergency medical services

Emergency medical services (EMS) play a vital role in delivering pre-hospital care. The operational efficiency of such services is critical and adequate demand forecasts can contribute to such a goal. But for that, the available data need to be well characterized before being used. Previous studies have failed to address some important aspects of this need, such as exploring a comprehensive list of contextual data to decide which are relevant to explain the EMS demand behavior. Moreover, modern forecasting techniques have been explored in the EMS context, including neural networks, but the computational complexity inherent to the methods and their use was not discussed. Finally, it is also unclear how different demand patterns can be when predicting the volume of emergency calls considering the priority level and the number of dispatches according to vehicle type. This study proposes a generic data-driven forecasting method to address these shortcomings and to support operational decisions. The results obtained with the proposed method indicate that each priority call and vehicle type shows different patterns, which suggests that such differentiation should contribute to better resource allocation. At the same time, the operational impact of the demand shared by neighboring zones proved to be significant at bases near the border. The models developed resulted in important decision tools that can be used to predict the dynamic demand of EMS on an hourly or shift basis. Additionally, the method adds value for decision-makers that want to plan not only when and how many but also where resources are demanded, avoiding assumptions that impact the operational performance.     

Locating emergency medical services in small town and rural settings

Locating emergency medical services in small town and rural settings presents subtle, but significant differences to those in metropolitan areas. The lack of service mix and unit choice, the measurement of response time in minutes rather than seconds, and the limits of the planning environment are discussed. Using time-distance comparisons and location-allocation techniques within a microcomputing environment, some aspects of planning emergency medical services are illustrated within the context of the Kingston (Ontario) Regional Ambulance Service.     

A model for measuring the need for services in a district

Administrators of social programs are often faced with decisions regarding how to distribute available funds. An important factor in this decision is the geographic location of the population in need of the agency's services. One would assume that those areas of the community where there are more people in need of the agency's support would receive a larger portion of the budget. However, in many cases, dollars are apportioned without adequate knowledge of what parts of the community are in the greatest need of services.This paper presents a method that can be used by most agencies for making a determination of the service need in different parts of the community. The agency used in the model construction is the Office of Community Services (OCS). The mandate of OCS is to implement a comprehensive plan for the delivery of social services in New York City. The “community” (New York City) is divided into forty Human Resource Districts (HRD's). In each of these districts there are outstations that provide a range of social services.In the past, misleading population characteristics of the districts were used to represent the need for OCS services. The characteristics were misleading because they did not represent the number of persons who would be in need of the services. For example, the number of persons receiving public assistance would not adequately represent the number of persons who needed child health services. This is especially true because some persons who are not eligible for public assistance are eligible for child health services.     

Screening the impacts of municipal service policy changes

The planning of municipal service delivery systems requires accurate forecasts of demand, and particularly of the effects the quality of service delivery has on demand. A metholology for this problem should meet three criteria, if it is to be useful for municipal planning: it must be low-cost and use generally available data; it must be based on user behavior, so that the effects of policy changes can be correctly attributed; and it must allow testing of the transferability of the results, since this is required for general forecasting use. This paper develops such a methodology, based on econometric analysis of data from a number of service areas within a number of regions, forming a double cross-section. Empirical tests of the methodology were performed for two local government services where the effect of service quality on demand is important: sewer and highway construction, which have been hypothesized to affect the patterns of development within regions; and solid waste collection, where the level of service provided affects how much waste enters the collection system and how much is littered, burned or recycled. The two case studies and other analyses suggest that the methodology is a useful tool for testing whether policy changes have an effect on the demand for service, but not for accurate demand forecasting. Thus, these simple models are relevant for the role of screening the effect of policy changes, but more detailed and localized approaches are necessary for system design.     

ACCESSIBILITY AND THIRD WORLD RURAL DEVELOPMENT: A Case Study of Sumatra*

Road and transport service improvements are widely recognized as important catalysts to economic development in most third world countries. When integrated with other programs which create new employment opportunities, roads and bus services enable subsistence farmers to seek off-farm salary-earning jobs. This paper examines the relationship between accessibility and economic well-being using data from rural Sumatra in Indonesia. The research relies on multiple indicators of both measures. Households in more remote rural villages are found to average appreciably lower levels of consumption expenditures. When isolated from subregional market and trade centers, consumption levels fall dramatically. The research also shows that the average value of farm produce increases with road quality, frequency of bus service, and close proximity of commerical centers. Thus, agriculture productivity is linked to both transport supply and spatial proximity factors. Additionally, the analysis shows that off-farm earnings increase when migrant households have access to both motorcycles and bicycles. Loans and subsidies for purchasing such “low tech” vehicles as bicycles, scooters, and micro-buses could prove more beneficial to many rural villagers than capital-intensive road projects. Lastly, the research suggests that the siting of transmigration settlements within reasonable proximity to regional and subregional market centers is important if the planned villages are to develop trade linkages and experience sustained economic growth.     

应急物流服务网点选址模型研究

应急物流是应对突发事件的重要保障。应急物流可以降低灾害影响程度,缩短受害持续时间,使突发性事件造成损失最小化。而在进行应急物流决策时,首先会面临应急物流服务网点的选址问题。应急物流服务网点置于合理的位置,不仅可以降低成本,而且还能够保证提供应急物资的时效性,从而避免可能导致的更大损失。在给定限制条件下应急服务网点选址模型基础上,综合考虑应急需求的随机性和由灾害导致应急配送时间模糊的不确定情况,研究新的模糊和随机混合机会约束规划选址模型。     

Regional hospital needs projection: An input-output approach

Steeply rising medical costs and the inadequacies of health care for the needy have recently stirred up unprecedented concern over the health industry in this country. In order to achieve more efficient allocation of medical resources and, hence, more equitable distribution of medical services, regional planning and regulatory authorities have been established and periodically reorganized in the health field in this country. This paper develops a systematic input-output model utilizing a clinical approach to project the impatient services needed for a given population by age, sex, residence and medical specialty. On the basis of empirical discharge data, relationships between regional demographic characteristics and diagnoses, between diagnoses and inpatient services, and between inpatient services and the production capacity of hospitals were derived. Given the projected regional population, the coefficients so derived are adjusted and employed to project future inpatient service needs. By comparing the existing to projected capacity, the location and investment decisions for hospitals can then be properly made, and the possibility of resource misallocation may be minimized. The applicability of this model is demonstrated in forecasting the hospital needs in the Kansas City Metropolitan Area, 1975–1995.     

Research notes on socioeconomic siting dynamics

The inclusion of socioeconomic considerations in the process of industrial location/siting analysis has received limited attention in recent years. More commonly the social and economic impacts associated with the construction and operation of a major project emerge only after a prime site has been selected. This result serves to characteristically delimit advance socioeconomic planning and prevents a full and complete examination of relative cost-benefit alternatives. Impacted communities and the mitigation problems they pose can be insurmountable when addressed after the fact.This article will discuss a strategy for socioeconomic inputs to project siting and outline a model that has been utilized for the purpose of instigating potential socioeconomic impacts at the earliest possible stage within the industrial location siting process.     

Does Service Bundling Reduce Churn?

We examine whether bundling in telecommunications services reduces churn using a series of large, independent cross sections of household decisions. To identify the effect of bundling, we construct a pseudo‐panel dataset and utilize a linear, dynamic panel‐data model, supplemented by nearest‐neighbor matching. We find bundling does reduce churn for all three “triple‐play” services. The effect is only “visible” during times of turbulent demand. We also find evidence that broadband was substituting for pay television in 2009. This analysis highlights that bundling helps with customer retention in service industries, and may play an important role in preserving contracting markets.     

Direct and incentive planning within a university

This paper explores appropriate roles of “direct” and “incentive” academic planning in helping universities relate advantageously to the aspect of their environments represented by the instructional and research demands of their constituencies. Adopting these roles requires a university to have flexible, uncommitted resources which are difficult to obtain from program reductions because of the impossibility of administratively valuing a university's programs. The paper presents evidence that at one university these funds can be derived alternatively from improved tuition policy and legislative funding relationships.     

如何用遗传算法解决公路客运枢纽选址问题

文中首先分析了公路客运交通枢纽选址问题的研究思路.然后从客运枢纽为了达到方便客户、优化路网、减少投资等综合交通最优化的角度建立了教学模型,并给出了用遗传算法求解的程序流程图.最后通过某城市的客运枢纽规划实例,表明此理论型布局能够满足人们的出行需求,显示了该方法的科学性和可行性.