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The development of health care facilities in a nation improves the quality of life of its citizens, and enhances their efficiency and productivity; eventually, reducing poverty. This paper proposed a methodology that uses GIS and multi-criteria decision-making technique for development of health care units (HCUs), to attain spatial efficiency in the distribution of facilities. The methodology assigns spatial weightage to the suitability index of the candidate locations in the objective function of maximizing coverage location-allocation problem embedded in ArcGIS. Habitations unserved by the existing HCUs are considered as candidate locations. The five criteria considered to determine the suitability index of a location are: Access distance to nearest existing HCU (C 1) , Accessibility index of habitations to existing HCUs based on service to population ratio (C 2) , Connectivity to all-weather roads (C 3) , Population of neighborhood (C 4) , and Health care requirement of a zone (C 5). The proposed methodology is applied in Jhunjhunu district, India as a case study, for the development of Community Health Centers (CHCs). Accessibility of habitation to facilities (jointly C 1 , C 2, and C 4) found to be the most influencing criteria in deciding the suitability of a candidate location to site the CHCs. The proposed methodology enables maximization of coverage, minimization of needless competition within CHCs, and satisfaction of the zonal requirement for health. Study findings would be helpful to national policymakers for developing HCUs by prioritizing fund allocation to shortage areas to improve the health index as well as the quality of life. • A generic practice ready methodology is proposed to develop healthcare units in rural area • GIS and Multi-criteria technique are used concurrently for location-allocation • Spatial weightage is assigned to the suitability index of the candidate location in MCLP • Proposed methodology ensures spatial efficiency in the distribution of facilities • Findings would help policy makers for fund allocation to improve quality of life [ABSTRACT FROM AUTHOR]

The study concerns with the quantification of accessibility to health facilities which is a prime concern in rural areas. In order to assure access to health care, planning commissions and policy decision makers require definite and reliable measures of accessibility values, thus that appropriate health care shortage areas can be analyzed and a policy decision can be taken accordingly to pacify the problem. Thus in this paper enhanced two step floating catchment area (E2SFCA) method, a special case of gravity model is used to quantify the present accessibility levels to health in rural areas. E2SFCA method which is an enhancement of two step floating catchment area (2SFCA) method differentiates the accessibility of the population within the catchment area by introducing a distance decay function. At the point when calibrating the distance decay from the travel behavior of patients in the study areas, it is revealed that sigmoidal functions are more likely suitable for the high population density regions and also plain terrains and decline functions for low population density regions and difficult desert or hilly areas. The paper yields health care shortage areas. [ABSTRACT FROM AUTHOR]

Research at the confluence of accessibility, equity and health is flourishing. And yet, there is only slow and modest progress in terms of improving the spatial and temporal accuracy of measuring accessibility and equity of accessibility to health care services. This paper critically reviews the latest methodological and empirical research developments and trends in this area through a transport geography lens. More specifically, this paper discusses recent accomplishments in terms of modeling accessibility and provides a systematic and comprehensive literature review of their application in empirical studies of health care delivery. Based on this literature review a research agenda is put forward, identifying knowledge gaps that transport researchers can help to fill. These knowledge gaps pertain to the need for more spatially disaggregated, individualized and temporally-aware accessibility metrics, more sophisticated geocomputational tools to operationalize such metrics and improved measurement of equity considerations in empirical research. [ABSTRACT FROM AUTHOR]

Access to health care is key to well-being, and it is increasingly clear that aggregated accessibility analysis is hard to reflect people's actual healthcare behaviour. This paper employs a patient-based healthcare travel survey to obtain a nuanced picture of how healthcare travel varies across patients. The existing literature shows transportation is an essential factor in accessing health care; however, most studies focus on separate healthcare travel mode choices or hospital choices for certain segments of patients, making it difficult to derive clear profiles of patients. Also, the attitudinal factors in healthcare travel have long been neglected. This research explores the joint hospital choice and travel behaviour of patients. We conducted an online survey with patients in Shanghai to identify the heterogeneity in healthcare travel behaviour and hospital choice. A latent class model with covariates is adopted to identify different patient types that exhibited distinct hospital choices and healthcare travel behaviour. Attitudinal factors are included in our model to form clear-separated clusters. Four categories of patients are identified: public transit patients, car-oriented patients, near-hospital patients, and non-downtown hospital patients, which differ in sociodemographic characteristics, healthcare-seeking behaviour, and public transit accessibility. Our research shows that a substantial share of non-downtown hospital patients should not be underestimated in healthcare travel demand analysis. The behaviour of public transit and non-downtown patients requires improvement of quality and public transit accessibility in non-downtown tertiary hospitals. Our study contributes to a better understanding of the market segments of patients and tailored healthcare and transport policies to meet patient healthcare travel demand. [ABSTRACT FROM AUTHOR]

Abstract: This paper reports the results of an empirical analysis of the Kuznets curve relationship between per capita income and road fatalities across 60 countries over the period 1972–2004. This relationship hypothesizes that the number of road fatalities increases with increasing motorization in the early stages of economic growth. Eventually, due to advances in technical, policy and political institutions, it declines as per capita income increases. The quality of political institutions as well as improvements in medical care and technology are hypothesized to impact road fatalities. Results indicate evidence of a Kuznets curve relationship between per capita income and road fatalities for both highly developed and less developed countries and support our hypothesis that changes in institutional quality and medical improvements underlie the Kuznets relationship. The evidence presented in this study suggests that lowering corruption levels as well as improvements in medical care and technology would help to reduce road fatalities. [Copyright &y& Elsevier]