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An agent-based model of social networks for evaluating asthma control interventions on reducing the emergency department visits

Author

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  • N Celik
  • OM Araz
  • M Bastani
  • J P Saenz

Abstract

Asthma has become a leading cause of childhood disability and school absenteeism in the United States. While asthma is a manageable chronic disease, the cost of its management is on the rise, especially because asthma-related emergency department (ED) visits cost five times more than primary care visits. Nonetheless, the costs of asthma management can be significantly decreased using effective management strategies via social network analyses and finding ways to reduce the asthma triggers that may cause ED visits. In this study, a social network analysis model is developed, which evaluates the impact of asthma management interventions by the number of ED visits from asthmatic children. Simulation results show that the implementation of an early symptom identification strategy for asthmatic children and their parents decrease the average number of annual ED visits for an asthmatic crisis from 0.156 visits to 0.042 visits per 1000 patients diagnosed with asthma. In addition, the simulation results reveal that the implementation of an asthma awareness programme in schools targeting teachers and staff members reduces the annual ED visits for asthmatic crises (per 1000 patients diagnosed with the disorder) to 0.108 visits per year. Asthma awareness campaign in school children would lead to a drop in the annual ED visits for an asthmatic crisis (per 1000 patients diagnosed with the disorder) to 0.103 visits per year. The use of a public asthma awareness campaign leads to a change in the annual ED visits for an asthmatic crisis (per 1000 patients diagnosed with the disorder) from 0.156 visits to 0.144 visits per year.

Suggested Citation

  • N Celik & OM Araz & M Bastani & J P Saenz, 2017. "An agent-based model of social networks for evaluating asthma control interventions on reducing the emergency department visits," Journal of Simulation, Taylor & Francis Journals, vol. 11(2), pages 87-102, May.
  • Handle: RePEc:taf:tjsmxx:v:11:y:2017:i:2:p:87-102
    DOI: 10.1057/jos.2015.19
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    Cited by:

    1. Mona Issabakhsh & Seokgi Lee & Hyojung Kang, 2021. "Scheduling patient appointment in an infusion center: a mixed integer robust optimization approach," Health Care Management Science, Springer, vol. 24(1), pages 117-139, March.

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