2022
DOI: 10.1186/s12942-022-00316-1
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Spatial-temporal analysis of cerebral infarction mortality in Hokkaido, Japan: an ecological study using a conditional autoregressive model

Abstract: Background: Accessibility to stroke treatments is a challenge that depends on the place of residence. However, recent advances in medical technology have improved health outcomes. Nevertheless, the geographic heterogeneity of medical resources may increase regional disparities. Therefore, evaluating spatial and temporal influences of the medical system on regional outcomes and advanced treatment of cerebral infarction are important from a health policy perspective. This spatial and temporal stu… Show more

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“…In addition, hospital-related factors were identified, such as whether or not the hospital was a primary stroke center (PSC), hospital size defined by the number of beds, and hospital volume defined by the number of AIS cases experienced. The Japan Stroke Society accredits PSCs as facilities that meet the necessary conditions for stroke care 20,21) . Hospital size was divided into the following three groups based on previous studies: 1-199 (small), 200-499 specialists, longer transportation times, and a higher prevalence of various risk factors for AIS, such as diabetes and smoking, in rural areas than in urban areas, possibly due to region-specific behavioral and cultural features [7][8][9][10] .…”
Section: Data Collection Variables and Potential Biasmentioning
confidence: 99%
“…In addition, hospital-related factors were identified, such as whether or not the hospital was a primary stroke center (PSC), hospital size defined by the number of beds, and hospital volume defined by the number of AIS cases experienced. The Japan Stroke Society accredits PSCs as facilities that meet the necessary conditions for stroke care 20,21) . Hospital size was divided into the following three groups based on previous studies: 1-199 (small), 200-499 specialists, longer transportation times, and a higher prevalence of various risk factors for AIS, such as diabetes and smoking, in rural areas than in urban areas, possibly due to region-specific behavioral and cultural features [7][8][9][10] .…”
Section: Data Collection Variables and Potential Biasmentioning
confidence: 99%