Spatial Distribution of Underserved Emergency Medical Service Areas and Their Residents' Attributes -Focusing on Chungnam Province

Im, Jun-Hong; Park, Jeong‐Hwan

doi:10.17208/jkpa.2016.02.51.1.63

Cited by 6 publications

(3 citation statements)

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“…As demonstrated by Kim and O'Kelly [37], this tightening constraint improves the computational performance in finding optimal solutions because d opt tightens the feasible solution space of D with the substantial reduction in the number of branches and bounds (B&B). Constraints ( 9) and (10) define that decision variables are binary integers.…”

Section: • Parameter Inputsmentioning

confidence: 99%

“…Despite these efforts, however, the current placement of the facilities is disproportionately arranged due to various factors [5,6], which raises concerns about geographic disparities in healthcare service access [7,8]. Specifically, certain provinces in South Korea face challenges in providing coverage to people living in remote areas, such as rural or suburban areas, through the LEMIs [9][10][11]. This spatial inequity becomes more pronounced as the aging population tends to reside in these areas to escape financially stressful living environments after retirement.…”

Section: Introductionmentioning

confidence: 99%

“…Given this context, this area represents a good study area for exploring effective planning scenarios for optimizing the placement of LEMIs. There is a sizeable body of research regarding assessing the distribution of EMS facilities in the context of South Korea [10]. However, a majority of the studies focused on assessing EMS coverage to identify underserved areas regarding medical services.…”

Section: Introductionmentioning

confidence: 99%

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Location Planning of Emergency Medical Facilities Using the p-Dispersed-Median Modeling Approach

Oh,

Chun,

Kim

2023

IJGI

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This research employs a spatial optimization approach customized for addressing equitable emergency medical facility location problems through the p-dispersed-median problem (p-DIME). The p-DIME integrates two conflicting classes of spatial optimization problems, dispersion and median problems, aiming to identify the optimal locations for emergency medical facilities to achieve an equitable spatial distribution of emergency medical services (EMS) while effectively serving demand. To demonstrate the utility of the p-DIME model, we selected Gyeongsangbuk-do in South Korea, recognized as one of the most challenging areas for providing EMS to the elderly population (aged 65 and over). This challenge arises from the significant spatial disparity in the distribution of emergency medical facilities. The results of the model assessment gauge the spatial disparity of EMS, provide significantly enhanced solutions for a more equitable EMS distribution in terms of service coverage, and offer policy implications for future EMS location planning. In addition, to address the computational challenges posed by p-DIME’s inherent complexity, involving mixed-integer programming, this study introduces a solution technique through constraint formulations aimed at tightening the lower bounds of the problem’s solution space. The computational results confirm the effectiveness of this approach in ensuring reliable computational performance, with significant reductions in solution times, while still producing optimal solutions.

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Section: • Parameter Inputsmentioning

confidence: 99%