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Md Fitrat Hossain, Thomas Kissane, Priyanka Annapureddy, Wylie Frydrychowicz, Sheikh Iqbal Ahamed, Naveen Bansal, et al. (2020). Implementing Algorithmic Crisis Alerts in mHealth Systems for Veterans with PTSD. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 122–133). Blacksburg, VA (USA): Virginia Tech.
Abstract: This paper seeks to establish a machine learning driven method by which a military veteran with Post-Traumatic Stress Disorder (PTSD) is classified as being in a crisis situation or not, based upon a given set of criteria. Optimizing alerting decision rules is critical to ensure that veterans at highest risk for mental health crisis rapidly receive additional attention. Subject matter experts in our team (a psychologist, a medical anthropologist, and an expert veteran), defined acute crisis, early warning signs and long-term crisis from this dataset. First, we used a decision tree to find an early time point when the peer mentors (who are also veterans) need to observe the behavior of veterans to make a decision about conducting an intervention. Three different machine learning algorithms were used to predict long term crisis using acute crisis and early warning signs within the determined time point.
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Benjamin Schooley, Abdullah Murad, Yousef Abed, & Thomas Horan. (2013). A mHealth system for patient handover in emergency medical services. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 188–198). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: This research uses multiple methods to investigate the use of an enterprise mobile multimedia information system aimed at improving handover of patient and emergency incident information from pre-hospital Emergency Medical Services (EMS) to hospital emergency department providers. A field study was conducted across EMS and hospital organizations in the Boise, Idaho region of the United States for three months to examine use of the system and to assess practitioner perspectives. Findings include perceived benefits and challenges to using digital audio recordings and digital pictures, captured using a smartphone application, for improving the timeliness, completeness, accuracy, convenience, and security of patient information for handover in EMS; limitations on how much data can be collected in the field due to a wide variety of contextual constraints; and a need to better understand the value of video within the EMS handover context.
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Zeno Franco, Katinka Hooyer, Rizwana Rizia, A B M Kowser Patwary, Mathew Armstrong, Bryan Semaan, et al. (2016). Dryhootch Quick Reaction Force: Collaborative Information Design to Prevent Crisis in Military Veterans. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Crises range from global catastrophes to personal disasters. However, systematic inquiry on crises rarely employs a comparative approach to examine commonalities between these seemingly very different events. We argue here that individual psychosocial disasters can inform a broader discussion on crises. Our approach applies general crisis theory to a smartphone based psychosocial support system for US military veterans. We engaged in a process designed to explore how veteran peer-to-peer mentorship can be augmented with IS support to display potential early warning signs as first step toward preventative intervention for high risk behaviors. To gain a better understanding of how military veterans might benefit from such a system, this article focuses on a community collaborative design process. The co-design process used the Small Stories method, allowing important cultural characteristics of to emerge, illuminating considerations in IS design with military veterans, and highlighting how humans think about crisis events at the individual level.
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