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利用地理信息系统对医疗设施洪水损害假设的横断面研究。

Cross-Sectional Study of Flood Damage Assumptions in Medical Facilities Using Geographic Information Systems.

作者信息

Kaneko Yuji, Komine Hideo, Kataoka Yuki

机构信息

Department of Medicine, Hokkaido University, Sapporo, JPN.

Department of Civil & Environmental Engineering, Waseda University, Tokyo, JPN.

出版信息

Cureus. 2024 May 3;16(5):e59577. doi: 10.7759/cureus.59577. eCollection 2024 May.

DOI:10.7759/cureus.59577
PMID:38832151
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11144585/
Abstract

Introduction Floods not only directly damage medical facilities but also hinder access to medical facilities, potentially disrupting local medical services. The scale of damage that medical facilities suffer from floods in Japan is unknown. In this study, we assessed the potential impact of floods on Japanese healthcare facilities by facility characteristics. Methods We conducted a cross-sectional study involving medical facilities registered in the Japan Medical Association Regional Medical Information System. Geographic data for the inundation area was obtained from open data of the Japanese government. Facilities that overlap with flooded areas were designated as affected facilities. The primary outcomes were the percentage of damaged facilities and beds. We calculated odds ratios (OR) and 95% confidence intervals (95%CI) using the Wald method to assess the impact of disaster base hospital designation on damage extent. Results We included 140,826 general clinics and 8,126 hospitals, which had 137,731 and 1,483,347 beds, respectively. The planned scale of flooding is estimated to affect 8.0% of general clinics and 10.8% of their beds. For hospitals, these figures were 8.8% and 7.8%, respectively. The maximum potential scale of flooding is estimated to affect 23.6% of general clinics and 23.9% of their beds. For hospitals, these figures were 22.5% and 20.6%, respectively. At the planned scale of flooding, there was no difference found in the rate of damaged facilities between disaster base hospitals and non-disaster base hospitals, and the rate of damaged beds was lower at non-disaster base hospitals (OR = 0.92, 95%CI = 0.71-1.18 for damaged facilities and OR = 0.79, 95%CI = 0.78-0.80 for damaged beds). At the maximum potential scale of flooding, there was no difference found in the expected damage between disaster base hospitals and non-disaster base hospitals (OR = 1.14, 95%CI = 0.95-1.38 for damaged facilities and OR = 0.99, 95%CI = 0.98-1.00 for damaged beds). Conclusion In Japan, floods can hinder nationwide medical functions, particularly in certain regions. Healthcare professionals should assess potential flood damage in advance and ensure that their workplace's business continuity plan includes appropriate countermeasures.

摘要

引言

洪水不仅会直接损坏医疗设施,还会阻碍人们前往医疗设施,有可能扰乱当地的医疗服务。日本医疗设施遭受洪水破坏的规模尚不清楚。在本研究中,我们根据设施特征评估了洪水对日本医疗机构的潜在影响。

方法

我们进行了一项横断面研究,涉及在日本医师协会区域医疗信息系统中注册的医疗机构。淹没区域的地理数据来自日本政府的公开数据。与洪水淹没区域重叠的设施被指定为受影响设施。主要结果是受损设施和床位的百分比。我们使用Wald方法计算比值比(OR)和95%置信区间(95%CI),以评估灾害基地医院指定对受损程度的影响。

结果

我们纳入了140,826家普通诊所和8,126家医院,分别拥有137,731张和1,483,347张床位。预计的洪水规模估计会影响8.0%的普通诊所及其10.8%的床位。对于医院,这些数字分别为8.8%和7.8%。最大潜在洪水规模估计会影响23.6%的普通诊所及其23.9%的床位。对于医院,这些数字分别为22.5%和20.6%。在预计的洪水规模下,灾害基地医院和非灾害基地医院的设施受损率没有差异,非灾害基地医院的床位受损率较低(设施受损的OR = 0.92,95%CI = 0.71 - 1.18;床位受损的OR = 0.79,95%CI = 0.78 - 0.80)。在最大潜在洪水规模下,灾害基地医院和非灾害基地医院的预期受损情况没有差异(设施受损的OR = 1.14,95%CI = 0.95 - 1.38;床位受损的OR = 0.99,95%CI = 0.98 - 1.00)。

结论

在日本,洪水会阻碍全国范围内的医疗功能,特别是在某些地区。医疗专业人员应提前评估潜在的洪水破坏,并确保其工作场所的业务连续性计划包括适当的应对措施。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e680/11144585/a424ccbf9377/cureus-0016-00000059577-i08.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e680/11144585/d52acaecbeb7/cureus-0016-00000059577-i09.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e680/11144585/20ee96445b43/cureus-0016-00000059577-i10.jpg
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