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Author Geoffrey Hoare; Mary Beth Russell; Aaron Kite-Powell; Rick France
Title Developing H1N1 hospital surge dashboard indicators: A demonstration Type Conference Article
Year 2010 Publication ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings Abbreviated Journal ISCRAM 2010
Volume Issue Pages
Keywords Health care; Information systems; Public health; Esf-8; Florida; H1n1; Medical emergency; Situational awareness; Surge; Hospitals
Abstract Developing key state-wide indicators of Florida's health care system's public health capacity during the H1N1 Pandemic has been challenging. This demonstration outlines work to develop a key indicator of patient surge caused by the H1N1 outbreak. Further work to calibrate this measure and relate it to surge in other health care organizations is outlined.
Address Florida Department of Health, United States
Corporate Author Thesis
Publisher Information Systems for Crisis Response and Management, ISCRAM Place of Publication Seattle, WA Editor S. French, B. Tomaszewski, C. Zobel
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN Medium
Track Planning, Foresight and/or Risk Analysis Expedition Conference 7th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 585
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Author Jonas Rybing; Johan Larsson; Carl-Oscar Jonson; Erik Prytz
Title Preliminary Validation Results of DigEmergo for Surge Capacity Management Type Conference Article
Year 2016 Publication ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2016
Volume Issue Pages
Keywords Simulator Validation; Between Group Analysis; Command And Control; Performance Measures; Emergency Medicine; Surge Capacity
Abstract This paper presents preliminary analysis from a validation study of a novel emergency medicine command and control training and evaluation simulator: DIGEMERGO®. The simulated emergency scenario was a surge capacity event at a generic emergency department, in which the participants took on a management role as the emergency department?s coordinating head nurse. A between group validation design with medical expert and novice participants was used. Initial analysis examined three triage measures associated with surge capacity management performance: time to triage, amount of patients triaged, and triage accuracy. The results show that experts were significantly more accurate at triaging in-hospital patients, but not incoming trauma patients. No significant differences in time or number of patients triaged was found. These initial results partially indicate simulator validity, but trauma patient triage accuracy suffered from a confounding variable in the triage system used. Analysis of additional measures is undergoing to further investigate validity claims.
Address
Corporate Author Thesis
Publisher Federal University of Rio de Janeiro Place of Publication Rio de Janeiro, Brasil Editor A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3388 ISBN 978-84-608-7984-9 Medium
Track Command and Control Studies Expedition Conference 13th International Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 1386
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Author Ke Wang; Yongsheng Yang; Genserik Reniers; Jian Li; Quanyi Huang
Title An Attribute-based Model to Retrieve Storm Surge Disaster Cases Type Conference Article
Year 2021 Publication ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2021
Volume Issue Pages 567-580
Keywords Storm surge disaster, multiple attributes, retrieval model, affected region prediction
Abstract In China, storm surge disasters cause severe damages in coastal regions. One of the most important tasks is to predict affected regions and their relative damage levels to support decision-making. This study develops a two-stage retrieval model to search the most similar past disaster case to complete prediction. Based on spatial attributes of cases, the top-ranking past cases with a similar location to the target case are selected. Among these past cases, the most similar past case is selected by disaster attribute similarities. Three typical storm surge case studies have been used and implemented into this proposed model and the results show that all the most affected regions can be predicted. The proposed model simplifies the prediction process and updates results quickly. This study provides useful information for the government to make real-time response plans.
Address Tsinghua University; Tsinghua University; KU Leuven; Tsinghua University; Tsinghua University
Corporate Author Thesis
Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 978-1-949373-61-5 ISBN Medium
Track Planning, Foresight and Risk Analysis Expedition Conference 18th International Conference on Information Systems for Crisis Response and Management
Notes wangke16@mails.tsinghua.edu.cn Approved no
Call Number ISCRAM @ idladmin @ Serial 2356
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