Published online by Cambridge University Press: 09 June 2014
In catastrophic events, a key to reducing health risks is to maintain functioning of local health facilities. However, little research has been conducted on what types and levels of care are the most likely to be affected by catastrophic events.
The Great East Japan Earthquake Disaster (GEJED) was one of a few “megadisasters” that have occurred in an industrialized society. This research aimed to develop an analytical framework for the holistic understanding of hospital damage due to the disaster.
Hospital damage data in Miyagi Prefecture at the time of the GEJED were collected retrospectively. Due to the low response rate of questionnaire-based surveillance (7.7%), publications of the national and local governments, medical associations, other nonprofit organizations, and home web pages of hospitals were used, as well as literature and news sources. The data included information on building damage, electricity and water supply, and functional status after the earthquake. Geographical data for hospitals, coastline, local boundaries, and the inundated areas, as well as population size and seismic intensity were collected from public databases. Logistic regression was conducted to identify the risk factors for hospitals ceasing inpatient and outpatient services. The impact was displayed on maps to show the geographical distribution of damage.
Data for 143 out of 147 hospitals in Miyagi Prefecture (97%) were obtained. Building damage was significantly associated with closure of both inpatient and outpatient wards. Hospitals offering tertiary care were more resistant to damage than those offering primary care, while those with a higher proportion of psychiatric care beds were more likely to cease functioning, even after controlling for hospital size, seismic intensity, and distance from the coastline.
Implementation of building regulations is vital for all health care facilities, irrespective of function. Additionally, securing electricity and water supplies is vital for hospitals at risk for similar events in the future. Improved data sharing on hospital viability in a future event is essential for disaster preparedness.