Abstract

Adopting the case study approach present study attempts to unwrap the status of the healthcare accessibility of the Berhampur Community Development (CD) block of Murshidabad. A network-based method integrated with the gravity model is used to identify under-serviced areas that do not have access to essential healthcare services at the settlement level. The attempt is made to map the significant socio-economic and demographic factors affecting the accessibility of quality healthcare services that can suggest the best possible solution to considering the heterogeneous needs of the population concerning healthcare services. The healthcare accessibility index (Ai) to the population demand is mapped to delineate the underserviced area. The Joint Hansen’s Improved Gravity Model and Huff Model (probability model) is used with deprivation mapping. Following the human- rights approach of the good living standards, fourteen indicators were extracted from census data, and the indicators were standardized by applying a min-max normalization formula. The indices calculate to measure healthcare deprivation, and inaccessibility at the neighborhood scale indicate the sharp differences in the spatial context. The increasing coverage of healthcare facilities has yet to address the issue of accessibility as an interplay between facilities-connectivity matrix. The study used a connectivity matrix to analyze healthcare accessibility and found that network-based measurement of health accessibility is more suitable over straight-line distance. We found this work may help support policymaking and bridge the gap between the biased share of infrastructure coverage and health care disparity in the study area.

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