TY - JOUR
T1 - A Spatial Analysis of Preventable Hospitalization for Ambulatory Care Sensitive Conditions and Regional Characteristics in South Korea
AU - Kim, Jinkyung
AU - Kang, Hye Young
AU - Lee, Kwang Soo
AU - Min, Songhee
AU - Shin, Euichul
N1 - Publisher Copyright:
© 2019 APJPH.
PY - 2019/7/1
Y1 - 2019/7/1
N2 - Hospitalization rates for ambulatory care sensitive conditions (ACSCs) can indicate the accessibility of a community’s primary care. We examined regional variation in ACSC hospitalization rates and identified associated factors. ACSC hospitalization rates in the 232 districts in 2013 ranged from 4.08 to 101.53 per 1000 adults. Spatial analysis showed that none of the 24 highest rate districts were located near Seoul, whereas 80% of the 45 lowest rate districts were, suggesting health care inequality between people living near Seoul and in other areas. Regression analysis showed significantly higher ACSC hospitalization rates in districts with higher elderly (β = 0.94) and low-income populations (β = 2.25), more remote areas (β = 0.29), and more hospital beds (β = 0.03). The number of primary care clinics was negatively associated with ACSC hospitalization (β = −1.37). For these variables, geographically weighted regression analysis provided local regression coefficients, useful for developing region-specific strategies to reduce ACSC hospitalization.
AB - Hospitalization rates for ambulatory care sensitive conditions (ACSCs) can indicate the accessibility of a community’s primary care. We examined regional variation in ACSC hospitalization rates and identified associated factors. ACSC hospitalization rates in the 232 districts in 2013 ranged from 4.08 to 101.53 per 1000 adults. Spatial analysis showed that none of the 24 highest rate districts were located near Seoul, whereas 80% of the 45 lowest rate districts were, suggesting health care inequality between people living near Seoul and in other areas. Regression analysis showed significantly higher ACSC hospitalization rates in districts with higher elderly (β = 0.94) and low-income populations (β = 2.25), more remote areas (β = 0.29), and more hospital beds (β = 0.03). The number of primary care clinics was negatively associated with ACSC hospitalization (β = −1.37). For these variables, geographically weighted regression analysis provided local regression coefficients, useful for developing region-specific strategies to reduce ACSC hospitalization.
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U2 - 10.1177/1010539519858452
DO - 10.1177/1010539519858452
M3 - Article
C2 - 31253046
AN - SCOPUS:85068377371
SN - 1010-5395
VL - 31
SP - 422
EP - 432
JO - Asia-Pacific Journal of Public Health
JF - Asia-Pacific Journal of Public Health
IS - 5
ER -