Literature DB >> 27733927

Integrated modelling of medical emergency response process for improved coordination and decision support.

George Milis1, Panayiotis Kolios1, Gaby Van Melick2, Toni Staykova3, Ira Helsloot2, Georgios Ellinas1, Christos Panayiotou1, Marios Polycarpou1.   

Abstract

The medical emergency response comprises a domain with complex processes, encompassing multiple heterogeneous entities, from organisations involved in the response to human actors to key information sources. Due to the heterogeneity of the entities and the complexity of the domain, it is important to fully understand the individual processes in which the components are involved and their inter-operations, before attempting to design any technological tool for coordination and decision support. This work starts with the gluing together and visualisation of the interactions of involved entities into a conceptual model, along the identified five workspaces of emergency response. The modelling visualises the domain processes, in a way that reveals the necessary communication and coordination points, the required data sources and data flows, as well as the required decision support needs. Work continues with the identification and modelling of the event-driven discrete-time-based dynamics of the emergency response processes and their compositions, using Petri nets as the modelling technique. Subsequently, an integrated model of the process is presented, which facilitates the parallelisation of the tasks undertaken in an emergency incident.

Entities:  

Keywords:  Petri nets; coordination modelling; data flows; data sources; decision making; decision support; emergency services; event-driven discrete-time-based dynamics; health care; medical emergency response process

Year:  2016        PMID: 27733927      PMCID: PMC5048341          DOI: 10.1049/htl.2016.0039

Source DB:  PubMed          Journal:  Healthc Technol Lett        ISSN: 2053-3713


  2 in total

Review 1.  Patient safety in emergency medical services: a systematic review of the literature.

Authors:  Blair L Bigham; Jason E Buick; Steven C Brooks; Merideth Morrison; Kaveh G Shojania; Laurie J Morrison
Journal:  Prehosp Emerg Care       Date:  2012 Jan-Mar       Impact factor: 3.077

2.  Naturalistic decision making.

Authors:  Gary Klein
Journal:  Hum Factors       Date:  2008-06       Impact factor: 2.888

  2 in total
  1 in total

Review 1.  The influences of the COVID-19 pandemic on medical service behaviors.

Authors:  Wen-Han Chang
Journal:  Taiwan J Obstet Gynecol       Date:  2020-09-11       Impact factor: 1.705

  1 in total

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