Decentralization to local governments and amending of Health center Law are to promote the efforts of health planning at the level of local agencies. In the health facility planning, it is important to take into account that what to be built, where to be located, how far should be service area and so forth, because health facilities are immovable, and require capital as well as personnel and consumable supplies. The aim of our study, answering to the question of 'where to be located?`, is to determine the best location of urban health sub-center. At the local level, planning is the matter of finding the best location of specific facility, in relation to population needs. We confine the accessibility, which is basic to location planning, to geographic one. Location-Allocation Model is used to solve the problem where the location is to maximize geographic accessibility. To minimize the weighted travel distance, objective function, Rk= aijwidij is used. Distances are measured indirectly by map measure-meter with l:25,000 Suwon map, and each potential sites, 10 administrative Dongs in Kwonson Gu, Suwon, are weighted by each number of households, total population, maternal age group, child age group, old age group, Relief for the livelihood, and population/primary health clinics. we find that Kuwoon-Dong, Seodun-Dong, Seryu3-Dong, according the descending orders, are best sites which can minimize the weighted distance, and conclude that it is reasonable to determine the location of urban health sub-center among those sites.
Child ; Equipment and Supplies ; Family Characteristics ; Gyeonggi-do ; Health Facilities ; Health Facility Planning ; Health Planning ; Humans ; Jurisprudence ; Maternal Age ; Politics ; Urban Health*

Background: and Purpose Endovascular recanalization therapy (ERT) is becoming increasingly important in the management of acute ischemic stroke (AIS). However, the hospital volume threshold for optimal ERT remains unknown. We investigated the relationship between hospital volume of ERT and risk-adjusted patient outcomes. Methods: From the National Health Insurance claims data in Korea, 11,745 patients with AIS who underwent ERT from July 2011 to June 2016 in 111 hospitals were selected. We measured the hospital’s ERT volume and patient outcomes, including the 30-day mortality, readmission, and postprocedural intracranial hemorrhage (ICH) rates. For each outcome measure, we constructed risk-adjusted prediction models incorporating demographic variables, the modified Charlson comorbidity index, and the stroke severity index (SSI), and validated them. Risk-adjusted outcomes of AIS cases were compared across hospital quartiles to confirm the volume-outcome relationship (VOR) in ERT. Spline regression was performed to determine the volume threshold. Results: The mean AIS volume was 14.8 cases per hospital/year and the unadjusted means of mortality, readmission, and ICH rates were 11.6%, 4.6%, and 8.6%, respectively. The VOR was observed in the risk-adjusted 30-day mortality rate across all quartile groups, and in the ICH rate between the first and fourth quartiles (P<0.05). The volume threshold was 24 cases per year. Conclusions There was an association between hospital volume and outcomes, and the volume threshold in ERT was identified. Policies should be developed to ensure the implementation of the AIS volume threshold for hospitals performing ERT.