Location of health care facilities: An analytical approach (original) (raw)

A location comparison of three health care centers in Sfax-city

The problem of health facilities location is explored under a mathematical optimization approach. Several models are developed for the location of a generalized health facility system in a manner that the selected criteria are optimized. From the literature we use in our paper the criteria efficiency and availability of the service. The optimal locations satisfying two objectives, one that minimizes health care centers-patient distance and another that captures as many patients as possible within a pre-specified time or distance. The results indicate that the existing locations provide near-optimal geographic access to health care center.

Use of location-allocation models in health service development planning in developing nations

European Journal of Operational Research, 2000

There is considerable evidence that because of poor geographical accessibility, basic health care does not reach the majority of the population in developing nations. Despite the view that mathematical methods of locational analysis are too sophisticated for use in many of these nations, several studies have demonstrated the usefulness of such methods in the locational decision-making process. This paper reviews the use of location-allocation models in health service development planning in the developing nations. The purpose of this review is to examine the suitability of these methods for designing health care systems and their relevance to overall development problems in such countries.

A spatial decision support system for special health facility location planning in developing regions

Ethiopian Journal of Environmental Studies and Management, 2017

Access to healthcare is a determinant of the wellbeing of the people. Planning the location and distribution of health facilities to ensure efficiency and equity in the face of limited resources can be challenging, especially where the type of care requires expensive equipments and specialists. This study attempts to provide a spatial decision support system (SDSS) to select specific locations for provision of mental health care out of existing health centres. The SDSS in this study uses a geographic information system (GIS) and location-allocation models. The data used in the SDSS include the coordinates of the location of the mental health facilities, the coordinates and population of the settlements and data on the roads and footpaths in the study area. The empirical results from the application of the SDSS framework shows that the average distance travelled in the existing configuration of mental health care centres (MHC) could be reduced from 15.3 km to 14 km by adopting a model plan. It is also shown that 74.85% of the settlements are more than ten kilometers from the nearest MHC. In order to minimize travel distance and maximize coverage of the population the minimize facilities, model option of the SDSS shows that 21 facilities are required to ensure that the average travel distance is 9.4km and that 98.6% of the settlements are not more than 20 km from the nearest MHC. Decision makers can use the SDSS discussed in this study to achieve efficiency or equity in the provision of health services. Thus it is hoped that health planners would adopt these techniques and tools to make their location decisions more efficient, reduce inequities and be rational in the use of resources.

A multiobjective optimization approach for location‐allocation of clinics

International Transactions in Operational Research, 2014

In order to establish new healthcare facilities, their optimal number and locations should be determined. Unsuitable locations for these facilities may result in substandard customer services and increased expenses. To solve this location‐allocation problem, this study applied a multiobjective model that combined geographical information system (GIS) analysis with a multiobjective genetic algorithm. Optimum sites for new clinics were determined by considering four objectives: minimizing total travel cost, minimizing inequity in access to clinics, minimizing the land‐use incompatibility in the study area, and minimizing the costs of land acquisition and facility establishment. Chromosomes of varying lengths were used in the multiobjective optimization process. An important advantage of this is that multiple optimal solutions with different numbers of healthcare facilities can be compared directly. An a posteriori preference method was used in this study. TOPSIS (Technique for Order P...

Location-Allocation Model of Facilities for an Integrated Medical Services Network

The growth of medical care across different treatment and surgery specialties has led to increased complexity in the healthcare supply chain. Institutions often subcontract specialized medical services, including certain surgical procedures, which present significant operational challenges due to their requirements of products and staff. This article discusses the challenge of identifying and assigning facilities as distribution centers for integrated medical services, particularly surgical services distributed by private companies and required by a network of public hospitals. We developed an optimization model based on the location theory. We propose a specific model tailored to the characteristics of integrated medical services by adapting classic model structures. The result is a model that offers decision makers a valuable tool for planning the distribution of integrated medical services. Our findings suggest that the model obtained can guide the distribution planning process, offering various solutions based on the company's time and cost requirements to meet quality standards for public clients.

Competitive Location Model in Healthcare: A Case Study on Tehran’s Health Centers

international journal of hospital research, 2017

Background and objective: The location of facilities is of great importance in healthcare and is of interest to researchers due to its importance. In this regard, a large proportion of classic location-allocation models concentrate on solving problems in an exclusive environment (non-competitive), but this assumption is rarely true in reality. Methods: At first, a basic Non-Competitive Location Model (NCLM) is presented. Then, a Competitive Location Model (CLM) is developed based on the initial model. This study proposes a multi-objective integer programming model based on Nash bargaining game. The first objective function maximizes the two-person Nash product, which in turn maximizes the total number of patients covered by the newly established healthcare centers. The second objective function minimizes the sum of distances between population centers and the newly established healthcare centers. Findings: The results obtained from applying the CLM on Tehran’s Health Centers reveale...

A Mathematical Model for Locating the Medical and Emergency Centers considering the Failure Probability of Centers

Mathematical Problems in Engineering

Enhancing the amount of industrial and chemical production is one of the most important effects of increasing rural people’s migration to cities, which leads to many abnormalities in the healthcare domain. In this regard, one of the most important tasks of health sector managers is designing and implementing some programs to monitor and control the level of community health, which is one of the health organizations’ strategic planning. On the other hand, the location of service centers is one of the most important problems in the area of strategic planning by any organization because selecting an appropriate site for constructing facilities can have a significant effect on reducing costs and increasing the coverage level. However, an appropriate site to construct the facilities must also have maximum reliability in addition to reducing costs and increasing the coverage level. This problem is important because many factors, such as natural disasters, result in failure of centers and ...

Location of preventive health care facilities

Annals of Operations Research, 2002

This paper is focused on the problem of locating preventive health care facilities. The aim is to maximize participation to prevention programs. We assume that distance is a major determinant of participation and people would go to the closest facility for preventive health care. Each facility is required to have more than a predetermined number of clients because of the direct relationship between volume and quality of preventive services. We provide a mathematical formulation and present alternative solution approaches for this new location problem. We report on computational performance of the proposed methods in locating public health centers in Fulton County, Georgia and mammography screening centers in Montreal, Quebec.