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Updated: Sep 18, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
The Bayesian Network Model Revealed the Hospital Decision-making Rationale for Flood Evacuation Planning
Takashi Nagata1, Takeru Abe2, Koji Nishiyama3
1Department of Emergency Medicine, https://ror.org/05jr18655Japan Self Defense Forces Central Hospital, Setagaya, Tokyo, Japan.
Backgrounds:
Heavy rain and flood frequently occur in recent years and hospitals' preparedness for flood is important. To secure patient safety, hospital evacuation planning and drills due to flooding by heavy rain is inevitable. In the study the relation of factors with hospitals' preparedness for flood by heavy rain was analyzed.
Methods:
Subjects of the study were disaster base hospitals in Japan (n = 765). Internet survey conducted in 2022. Bayesian network was used to analyze the interrelation of factors.
Results:
430 hospitals (56.2%) were used for analysis. 42.1% of the hospital were located in designated flooded area and 33.7% of the hospitals have planning of hospital evacuation due to flooding. Display of area where flooding is expected in case of heavy rain and landslide warning area leads to a hospital evacuation planning and evacuation drills.
Conclusion:
Display of flooded area by heavy rain or landslide warning zone by governments is effective in advancing hospital preparedness for flood. Hospitals' recent experience of flood or landslide did not lead to evacuation planning or evacuation drills due to flood. These findings are useful in advancing hospitals' preparedness for flood and heavy rain.
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