|
Anton Björnqvist, Marc Friberg, Carl-Oscar Jonson, Jenny Pettersson, & Peter Berggren. (2022). An Analysis of a Swedish Medical Command and Control System’s Situation Reports from the COVID-19 Pandemic. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 334–348). Tarbes, France.
Abstract: This paper presents an analysis of situation reports used and created by a crisis management team within the Swedish healthcare sector during the early phase of the COVID-19 pandemic. The analysis was conducted through a deductive content analysis, where categories were identified based on the concepts of common operational pictures, sensemaking, and situation awareness. In the analysis, support for all identified categories was found. Based on the analysis and the concepts, future recommendations regarding what type of information that ought to be included in situation reports were created. These recommendations include, amongst others, the categories of consequences, how it is perceived by the public, objectives, status and implications of information, future scenarios, actions, resources, and work procedures.
|
|
|
Erik Prytz, Anna-Maria Grönbäck, Krisjanis Steins, Craig Goolsby, Tobias Andersson Granberg, & Carl-Oscar Jonson. (2020). Evaluating the Effect of Bleeding Control Kit Locations for a Mass Casualty Incident Using Discrete Event Simulation. 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. 167–178). Blacksburg, VA (USA): Virginia Tech.
Abstract: The purpose of this study was to develop a simulation model to evaluate bleeding control kit location strategies for a mass casualty incident scenario. Specifically, the event simulated was an explosion at a large sports arena. The model included a representation of the arena itself, simulated crowd movements following the detonation of an improvised explosive device, injuries and treatments, and different ways for immediate responders to help injured patients using tourniquets. The simulation model gave logically consistent results in the validation scenarios and the simulation outcomes were in line with the expected outcomes. The results of the different tourniquet location scenarios indicated that decentralized placement (more than one location) is better, easy access is important (between rather than at emergency exits) and that an increased number of available tourniquets will result in an increased number of survivors.
|
|
|
Jonas Rybing, Johan Larsson, Carl-Oscar Jonson, & Erik Prytz. (2016). Preliminary Validation Results of DigEmergo for Surge Capacity Management. 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: 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.
|
|
|
Jose J. Gonzalez, Colin Eden, Eirik Abildsnes, Martin Hauge, Monica Trentin, Luca Ragazzoni, et al. (2021). Elicitation, analysis and mitigation of systemic pandemic risks. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 581–596). Blacksburg, VA (USA): Virginia Tech.
Abstract: The Covid-19 pandemic has disrupted the health care system and affected all sectors of society, including critical infrastructures. In turn, the impact on society's infrastructures has impacted back on the health care sector. These interactions have created a system of associated risks and outcomes, where the outcomes of risks are risks themselves and where the resulting consequences are complex vicious cycles. Traditional risks assessment methods cannot cope with interdependent risks. This paper describes a novel risk systemicity approach to elicit and mitigate the systemic risks of a major pandemic. The approach employed the internet-based software strategyfinder[TM] in workshops to elicit relevant risk information from sixteen appropriately selected experts from the health care sector and major sectors impacted by and impacting back on the health care sector. The risk information was processed with powerful analytical tools of strategyfinder to allow the experts to prioritise portfolios of strategies attacking the vicious cycles.
|
|
|
Tobias Andersson Granberg, Carl-Oscar Jonson, Erik Prytz, Krisjanis Steins, & Martin Waldemarsson. (2020). Sensor Requirements for Logistics Analysis of Emergency Incident Sites. 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. 952–960). Blacksburg, VA (USA): Virginia Tech.
Abstract: Using sensors to collect data at emergency incident sites can facilitate analysis of the logistic operations. This can be used to improve planning and preparedness for new operations. Furthermore, real-time information from the sensors can serve as operational decision support. In this work in progress, we investigate the requirements on the sensors, and on the sensor data, to facilitate such an analysis. Through observations of exercises, the potential of using sensors for data collection is explored, and the requirements are considered. The results show that the potential benefits are significant, especially for tracking patients, and understanding the interaction between the response actors. However, the sensors need to be quite advanced in order to capture the necessary data.
|
|