Mizuki Umemoto’s research while affiliated with The University of Tokyo and other places

In this study, we developed a simulation model of detailed in-hospital disaster response to a mass casualty incident based on the analysis of related documents and actual in-hospital disaster response training, aiming to assess the hospital’s response capacity under various disaster situations. This simulation model includes detailed models of patients, floor configurations, resources, and response tasks, which consider resource requirements for the treatment of different patients with various injuries and physical conditions. The model covers patients’ arrivals to hospitalization or discharge. We conducted simulations of the target hospital to test two resource allocation strategies under two patient scenarios. By comparing the results under different resource allocation strategies, we found that the X-ray photography examination capacity could become a fundamental bottleneck in responding to mass casualty incidents. Also, we found that the appropriate resource allocations and quick replenishment could alleviate the negative effect of resource shortages and maintain a higher performance. Furthermore, the results show that the length of stay can be heavily affected by the patients’ configuration. As a result, by monitoring and anticipating the situation, a resilient and responsive resource allocation strategy must be prepared to handle such uncertain disaster situations.

This paper presents a nationwide survey about how Japanese home-visit nursing stations prepared and coped with the coronavirus disease 2019 COVID-19 pandemic. This study also aimed to provide a practical foundation and guide to develop business continuity plans (BCPs) for home-visit nursing stations and nursing care facilities to cope with pandemics. We applied a resource-focused BCP framework to efficiently collect and summarize knowledge and experiences from many facilities about the responses and countermeasures based on the three fundamental purposes to keep resources: prevent loss, promote increase, and utilize limited resources. We conducted a survey during Japan’s third wave of the COVID-19 pandemic and analyzed the responses using a qualitative and inductive content analysis method. We could develop categories to summarize various responses and countermeasures in a consistent and comprehensive manner. Based on the analysis results, we proposed six fundamental sub-plans to reorganize resource-focused BCP. The categorization and sub-plans are not special or innovative; however, since they focus only on resources and explain what we need to consider in BCPs in terms of action plans for resources, we expect that it is easier for BCP non-experts to understand the concept and utilize it for developing practical responses and countermeasures.

Hospitals need to prepare for disasters. For this purpose, they need to formulate a BCP and a response plan and conduct training and exercise. Through training and exercise, they are expected to learn necessary actions and procedures, as well as to find problems in the BCP and response plan. It is, however, not easy to comprehend and evaluate the entire training and exercise process, particularly as the scale of the training and exercise becomes larger. Besides, it also becomes more difficult to find important problems and their causes in training and exercise. To solve this problem, it is necessary to record the events and activities during training and exercise as much detail as possible and analyze them from various viewpoints. This paper describes the comprehensive data recordings in a disaster response exercise in a big hospital in Kanagawa Prefecture, Japan. This hospital is one of the largest hospitals in the region and is designated as a disaster-base hospital which is expected to play a central role in disaster medicine in the area. The target exercise is an annual exercise for a mass casualty incident assuming a big earthquake, in which 46 injured patients are transported to the hospital. We collected data on the following three aspects of the exercise: judgment and decision-making, such as triage and diagnosis and treatment, the in-hospital flow of patients and medical instruments, and the flow of information in and among different areas and rooms. Regarding the data on judgment and decision-making, we collected the documents used in actual disaster medicine, such as triage tags and medical charts. For the other data, we used action cameras attached to hospital staff, station cameras to observe the activities in specific areas, IC recorders attached to patients and several important hospital staff, PHS-IC recorders attached to area leaders to record inter-area communication, Zoom recordings for online communications, and several observers to record inter-area transfer of patients.This paper also describes preliminary analyses of the data recorded in the exercise, including the accuracy of 1st and 2nd triage, the details of patient flow, and the length of stay in each area.Finally, this paper describes the data analysis planned in the next step, such as network analysis of inter-area communication, task analysis of the activities in each area, and so on. In addition, we will discuss the possibility of utilizing the study to reproduce the exercise using the agent-based simulation we developed for a deeper understanding of the entire process of the in-hospital disaster medicine process.