scholarly journals Medical support based on the disaster situation/phase and its concept as the sole university hospital of a prefecture in the East Japan Great Earthquake Disaster

2012 ◽  
Vol 23 (5) ◽  
pp. 231-231
Author(s):  
Shigeki Kushimoto
Keyword(s):  
University Hospital ◽  
Great Earthquake ◽  
Medical Support ◽  
Earthquake Disaster ◽  
Disaster Situation

scholarly journals Telemedical consultation for remote islands

2020 ◽  
Vol 6 (3) ◽  
pp. 13-15
Author(s):  
Lukas Dölger ◽  
Robert Wendlandt ◽  
Jan-Thorsten Gräsner ◽  
Niels Renzing
Keyword(s):  
Conventional Approach ◽  
University Hospital ◽  
Medical Support ◽  
Research Project ◽  
Medical Expertise ◽  
Term Evaluation ◽  
Remote Islands ◽  
Innovative Concept

AbstractThe following work gives an overview of telemedical consultation in emergencies based on a research project. A telemedical centre located at a university hospital offers medical expertise for rural islands independent from place, time and urgency. Medical employees on the islands were relieved in matters of responsibilities and received medical support whenever it is necessary. Results from the projects mid-term evaluation compare the innovative concept with the conventional approach.

Informative Tweet Classification of the Earthquake Disaster Situation In Indonesia

2019 ◽  
Author(s):  
Windu Gata ◽  
Fachri Amsury ◽  
Nia Kusuma Wardhani ◽  
Ipin Sugiyarto ◽  
Daning Nur Sulistyowati ◽  
...  
Keyword(s):  
Earthquake Disaster ◽  
Disaster Situation ◽  
Tweet Classification

EARTHQUAKE DISASTER PREPAREDNESS AND LIFE OF HOMESTAY SYSTEM EVACUEES IN HIGH-RISE CONDOMINIUMS

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Akie Hisagi ◽  
Takashige Ishikawa
Keyword(s):  
Disaster Preparedness ◽  
Disaster Mitigation ◽  
Internet Survey ◽  
Earthquake Disaster ◽  
High Rise ◽  
Emergency Shelters ◽  
The Future ◽  
Disaster Situation ◽  
At Home

The possibility of a huge earthquake affecting Tokyo in the future is high. In the event of such an earthquake, many people will face problems returning to their homes, causing complete disorder and confusion as it will be impossible for everyone to access emergency shelters. If buildings such as high-rise condominiums remain standing and safe, it will be desirable that their residents take refuge at home. In this study, we investigated the awareness of disaster mitigation needs using an internet survey of over 800 residents of high-rise condominiums (of 10 or more stories) in central Tokyo. Our results show that approximately 60% of residents would take refuge at home. However, almost none of the respondents had emergency supplies such as water, food, and other daily necessities. This lack of preparedness would result in many people needing to move to emergency shelters. By analyzing these results, we aim to develop a method for avoiding confusion in the aftermath of a disaster and educate building residents on their needs in a disaster situation and the preparatory actions they must take.

scholarly journals Service-oriented Subscription Management of Medical Decision Data in the Intensive Care Unit

2008 ◽  
Vol 47 (04) ◽  
pp. 364-380 ◽  
Author(s):  
J. Decruyenaere ◽  
C. Danneels ◽  
K. Taveirne ◽  
K. Colpaert ◽  
E. Hoste ◽  
...  
Keyword(s):  
Intensive Care ◽  
Response Time ◽  
Support Services ◽  
Secure Communication ◽  
Smart Phone ◽  
University Hospital ◽  
Medical Decision ◽  
Medical Support ◽  
Service Oriented Architectures ◽  
Service Oriented

Summary Objectives: This paper addresses the design of a platform for the management of medical decision data in the ICU. Whenever new medical data from laboratories or monitors is available or at fixed times, the appropriate medical support services are activated and generate a medical alert or suggestion to the bedside terminal, the physician’s PDA, smart phone or mailbox. Since future ICU systems will rely ever more on medical decision support, a generic and flexible subscription platform is of high importance. Methods: Our platform is designed based on the principles of service-oriented architectures, and is fundamental for service deployment since the medical support services only need to implement their algorithm and can rely on the platform for general functionalities. A secure communication and execution environment are also provided. Results: A prototype, where medical support services can be easily plugged in, has been implemented using Web service technology and is currently being evaluated by the Department of Intensive Care of the Ghent University Hospital. To illustrate the platform operation and performance, two prototype medical support services are used, showing that the extra response time introduced by the platform is less than 150 ms. Conclusions: The platform allows for easy integration with hospital information systems. The platform is generic and offers user-friendly patient/service subscription, transparent data and service resource management and priority-based filtering of messages. The performance has been evaluated and it was shown that the response time of platform components is negligible compared to the execution time of the medical support services.

Grasp of Disaster Situation and Support Need Inside Affected Area with Social Sensing – An Analysis of Twitter Data Before and After the 2011 Great East Japan Earthquake Disaster Occurring –

2016 ◽  
Vol 11 (2) ◽  
pp. 198-206 ◽  
Author(s):  
Shosuke Sato ◽  
◽  
Kazumasa Hanaoka ◽  
Makoto Okumura ◽  
Shunichi Koshimura
Keyword(s):  
Great East Japan Earthquake ◽  
Earthquake Disaster ◽  
Social Sensing ◽  
Natural Language Text ◽  
Twitter Data ◽  
Before And After ◽  
Disaster Situation ◽  
Social Media Text ◽  
Source Of Information ◽  
Language Text

There are increasing expectations that social sensing, especially the analysis of social media text as a source of information for COP (Common Operational Picture), is useful for decision-making about responses to disasters. This paper reports on a geo-information and content analysis of three million Twitter texts sampled from Japanese Twitter accounts for one month before and after the 2011 Great East Japan Earthquake disaster. The results are as follows. 1) The number of Twitter texts that include geotag (latitude and longitude information) is too small for reliable analysis. However, a method of detecting the tweet’s location from the tweet’s text using GeoNLP (an automatic technology to tag geo-information from natural language text) is able to identify geo-information, and we have confirmed that many tweets were sent from stricken areas. 2) A comparison of Twitter data distribution before and after the disaster occurred does not identify clearly which areas were significantly affected by the disaster. 3) There were very few Twitter texts that included information about the damage in affected areas and their support needs.

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