Hospital site selection using fuzzy AHP and its derivatives

Vahidnia, Mohammad H.; Alesheikh, Ali Asghar; Alimohammadi, Abbas

doi:10.1016/j.jenvman.2009.04.010

Cited by 359 publications

(208 citation statements)

References 44 publications

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“…Convenient road access is considered one of the major factors determining the location of clinics (Vahidnia et al, 2009). The buffer analysis indicated that the clinics were preferentially located along major roads, the 50 m buffer including most clinic points on the map.…”

Section: Discussionmentioning

confidence: 99%

“…It showed how many clinics were located within certain distances from the roads. A close location was assumed to increase awareness of the clinic and its accessibility to residents of the city (Vahidnia et al, 2009). A hot-spot analytical method (Getis and Ord, 1992) was then applied to evaluate the spatial density of clinics in the study area.…”

Section: Spatial Analysis and Multiple Regressionmentioning

confidence: 99%

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Disparity in the spatial distribution of clinics within a metropolitan city

Lee

2013

Geospat Health

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Abstract.A methodology for evaluating and understanding how healthcare agencies are distributed within a city is provided. The study undertaken analysed the disparity in the spatial distribution of clinics within the metropolitan city of Daejeon, South Korea. Address and specialty of clinics in use were collected from five public health centres in 2010. Buffer analysis, hot-spot analysis, and generalized linear models were applied to the data collected. Multivariate analysis was also conducted on data collected in 2008 from the annual records of five ward offices (mid-level city administration units) taking the lowest administrative level of the city (the dong) into account. Buffer analysis showed that numerous clinics were located near major roads, while the hot-spot analysis identified three areas with concentrations of clinics and one area with hardly any clinics. The results of the generalized linear models showed variations depending on the specialty of the clinics suggesting that their distribution differed depending on specialty. There are no current regulations in force governing clinic location. Policy makers should consider improving the clinic distribution taking their speciality into account.

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Section: Discussionmentioning

confidence: 99%

Section: Spatial Analysis and Multiple Regressionmentioning

confidence: 99%

Disparity in the spatial distribution of clinics within a metropolitan city

Lee

2013

Geospat Health

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“…Diao and Jiang [23] not only introduced factors, such as customer preference and traffic weight, but also simulated the monthly number of hospital visits using the Monte Carlo method. Vahidnia et al [24] utilized a fuzzy analytic hierarchy process to optimize the hospital location by combining a geographic information system (GIS). Soltani and Marandi [25] studied the potential location for hospitals based on fuzzy multiple criteria decision making (MCDM).…”

Section: Literature Reviewmentioning

confidence: 99%

Location Planning Problem of Service Centers for Sustainable Home Healthcare: Evidence from the Empirical Analysis of Shanghai

Sun

2015

Sustainability

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It is of theoretical and practical significance to understand what factors influence the sustainable development of home healthcare services in China. Based on a face-to-face survey, we find that the location planning, which is decisive for the improvement of patient satisfaction, can effectively reduce the risks, as well as the costs of redundant construction and re-construction of service centers for home healthcare and, thus, helps ensure the sustainability of health and the environment. The purposes of this paper are to investigate the existing problem of home healthcare in Shanghai and to find the optimum location planning scheme under several realistic constraints. By considering differentiated services provided by the medical staff at different levels and the degrees of patient satisfaction, a mixed integer programming model is built to minimize the total medical cost. The IBM ILOGCPLEX is used to solve the above model. Finally, a case study of Putuo district in Shanghai is conducted to validate the proposed model and methodology. Results indicate that the model used in this paper can effectively reduce the total medical cost and enhance the medical sustainability, and therefore, the results of the model can be used as a reference for decision makers on the location planning problem of home healthcare services in China.

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“…The multicriteria decision-making problem related to the site selection for constructing a new hospital is studied in Vahidnia et al (2009). Here, we consider a simplified version of this problem, in which six sites are to be ranked, taking into account the following four criteria:…”

Section: Application Examplementioning

confidence: 99%

“…Indeed, it is worth noting in (22) that the degrees of preference of the DM can not be directly inferred from the distances from arterial streets. For instance, although the distance of X 4 is ten times larger than the distance of X 5 , X 5 is not considered ten times better than X 4 .…”

Section: Application Examplementioning

confidence: 99%

Construction of nonreciprocal fuzzy preference relations with the use of preference functions

Parreiras¹,

Ekel²

2013

Pesqui. Oper.

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ABSTRACT. In order to model the preferences of a decision-maker (DM) by means of fuzzy preference relations, a DM can utilize different preference formats (such as ordering of the alternatives, utility values, multiplicative preference relations, fuzzy estimates, and reciprocal as well as nonreciprocal fuzzy preference relations) to express his/her judgments. Afterward, the obtained information is utilized to construct fuzzy preference relations. Here we introduce a procedure that allows the use of so-called preference functions (which is a preference format utilized in the methods of PROMETHEE family) to construct nonreciprocal fuzzy preference relations. With diverse preference formats being offered, a DM can select the one that is the most convenient to articulate his/her preferences. In order to demonstrate the applicability of the proposed procedure a multicriteria decision-making problem related to the site selection for constructing a new hospital is considered here.

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Hospital site selection using fuzzy AHP and its derivatives

Cited by 359 publications

References 44 publications

Disparity in the spatial distribution of clinics within a metropolitan city

Disparity in the spatial distribution of clinics within a metropolitan city

Location Planning Problem of Service Centers for Sustainable Home Healthcare: Evidence from the Empirical Analysis of Shanghai

Construction of nonreciprocal fuzzy preference relations with the use of preference functions

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