Spatio-temporal analysis of spatial accessibility to primary health care in Bhutan

© 2015 by the authors; licensee MDPI, Basel, Switzerland. Geographic information systems (GIS) can be effectively utilized to carry out spatio-temporal analysis of spatial accessibility to primary healthcare services. Spatial accessibility to primary healthcare services is commonly measured using floating catchment area models which are generally defined with three variables; namely, an attractiveness component of the service centre, travel time or distance between the locations of the service centre and the population, and population demand for healthcare services. The nearest-neighbour modified two-step floating catchment area (NN-M2SFCA) model is proposed for computing spatial accessibility indices for the entire country. Accessibility values from 2010 to 2013 for Bhutan were analysed both spatially and temporally by producing accessibility ranking maps, plotting Lorenz curves, and conducting spatial clustering analysis. The spatial accessibility indices of the 205 sub-districts show great disparities in healthcare accessibility in the country. The mean-and median-based classification results indicate that, in 2013, 24 percent of Bhutan's population have poor access to primary healthcare services, 66 percent of the population have medium-level access, and 10 percent have good access

Measuring Primary Health Care Accessibility in Mississippi State Using an Extended Kernel Density 2SFCA Method

The accessibility of primary health care is fundamentally important to people’s life quality and wellbeing. Based on the block group level 2010 census data from the U.S. Census Bureau and primary health care data from Association of American Medical Colleges, this study focuses on measuring the primary health care accessibility using an extended kernel-density two Step Float Catchment Area method. The study area is the Mississippi State, which is ranked last state for health care. The objectives of this study are to calculate the accessibility and analyze the spatial and non-spatial disadvantages of communities in accessibility of primary health care of the Mississippi State. Results showed that the two-step floating catchment area integrated by a Gaussian function method is a viable method of calculating accessibility. Overall, urban and the fringe areas have higher spatial accessibility to primary health care, while lower accessibility areas are the suburban and rural areas. Relatively, Hinds County, Madison County, Rankin County, Lamer County, Forrest County, Jones County, Lauderdale County, and Lee County have higher accessibility, while some counties have lower accessibility, such as Marshall County, Winston County, Noxubee County, Wilkinson County, Smith County, and Greene County. From the factor analysis, those urban areas showed greater mobility disadvantages and higher health care needs. Besides, the attempts to integrate the health needs index and the mobility index with the spatial accessibility helps to balance accessibility with different non-spatial conditions. Additionally, this study provides implications for public policy about the health care distribution and the high health needs population

Spatio-temporal modelling and analysis of spatial accessibility to primary health care: A case study of Bhutan

Both spatial and aspatial dimensions of healthcare system are important in strengthening the healthcare system of any country. Knowing the spatial aspects of healthcare accessibility can help develop proper health policies in planning equitable allocation of health resources across the country. This thesis deals with the modelling of population and spatial accessibility using GIS, and an analysis of spatial and temporal changes in accessibility to healthcare services in Bhutan

Are Oklahoma City residents OK? A socio-spatial analysis of physicians and supermarkets via accessibility and affordability

Scope and Method of Study: The scope of the study examined how the built environment could contribute to individual health by analyzing neighborhoods in the Oklahoma City, Oklahoma Metropolitan Statistical Area (MSA). Due to poor health statistics throughout the state of Oklahoma and Oklahoma City, accessibility to physicians and supermarkets were analyzed as possible mechanisms contributing to poor health in the MSA. Price of healthy food could also be a factor that causes residents to eat cheaper, unhealthy food. Accessibility indices, market basket prices, and bivariate spatial autocorrelation techniques were used to evaluate the built environment's influence on health.Findings and Conclusions: The findings of the study found that the majority of the MSA had relatively good access to both physicians and supermarkets. Also, prices for the basket of goods were similar across the MSA. The rural areas had the worst access to physicians as well as Native Americans. For supermarket accessibility, rural areas again had poorer access and African-Americans had the worst access. However, in terms of pricing, African-Americans paid the least for this basket of goods and the residents without a vehicle paid the highest. The major conclusion is that physicians and supermarkets are not contributing heavily to the poor health statistics that are found in the Oklahoma City MSA