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. 2023 Feb 10;20(4):3147.
doi: 10.3390/ijerph20043147.

Spatial Accessibility of Primary Care in the Dual Public-Private Health System in Rural Areas, Malaysia

Jabrullah Ab Hamid  1   2 , Muhamad Hanafiah Juni  1 , Rosliza Abdul Manaf  1 , Sharifah Norkhadijah Syed Ismail  3   4 , Poh Ying Lim  1
Affiliations

Spatial Accessibility of Primary Care in the Dual Public-Private Health System in Rural Areas, Malaysia

Jabrullah Ab Hamid et al. Int J Environ Res Public Health. .

Abstract

Disparities in access to health services in rural areas represent a global health issue. Various external factors contribute to these disparities and each root requires specific remedial action to alleviate the issue. This study elucidates an approach to assessing the spatial accessibility of primary care, considering Malaysia's dual public-private system specifically in rural areas, and identifies its associated ecological factors. Spatial accessibility was calculated using the Enhance 2-Step Floating Catchment Area (E2SFCA) method, modified as per local context. Data were secondary sourced from Population and Housing Census data and administrative datasets pertaining to health facilities and road network. The spatial pattern of the E2SFCA scores were depicted using Hot spot Analysis. Hierarchical multiple linear regression and geographical weight regression were performed to identify factors that affect E2SFCA scores. Hot spot areas revolved near the urban agglomeration, largely contributed by the private sector. Distance to urban areas, road density, population density dependency ratios and ethnic composition were among the associated factors. Accurate conceptualization and comprehensive assessment of accessibility are crucial for evidence-based decision making by the policymakers and health authorities in identifying areas that need attention for a more specific and localized planning and development.

Keywords: factor; floating catchment area method; primary care; rural; spatial accessibility.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Study area and districts from adjacent district/states. (a) Population density (person per square kilometer) of rural Selangor. (b) Primary care facility distribution (by clinic type) and road network.
Figure 2
Figure 2
Spatial pattern of E2SFCA scores distribution and mapping of Hot Spot Analysis of the E2SFCA scores (a) Aspub score, (b) Aspri score, and (c) Astot score.
Figure 3
Figure 3
Regression coefficient of each explanatory variables (a–f) and standardized residuals (g) of the GWR on Astot score.
Figure 3
Figure 3
Regression coefficient of each explanatory variables (a–f) and standardized residuals (g) of the GWR on Astot score.
See this image and copyright information in PMC

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