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Automated Escalation and Incident Management in Healthcare During Mass Casualties and Pandemic Events

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Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. AI, Product and Service (HCII 2021)

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Abstract

We present Hypercare – a system for automated escalation and incident management in healthcare, which allows clinicians to create escalation logic in the hospitals. We present eight common escalation use cases and the results of a heuristic evaluation of the front-end of the system. We have completed designing the front-end and creating backend API endpoints of this application. The API endpoints have been collaboratively documented and tested using Postman. Examples for creating an escalation ladder and fetching active escalations are provided.

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Acknowledgements

This research has been funded by Mitacs Accelerate.

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Authors and Affiliations

  1. Ontario Tech University, Oshawa, 2000 Simcoe St N, Oshawa, ON, L1G 0C5, Canada

    Md. Yousuf Hossain & Loutfouz Zaman

  2. Hypercare, 313 Queen St W Summit Room, Toronto, ON, M5V 25, Canada

    Umar Azhar, Yvonne To & Joseph Choi

Authors
  1. Md. Yousuf Hossain
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  2. Umar Azhar
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  3. Yvonne To
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  4. Joseph Choi
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  5. Loutfouz Zaman
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Corresponding author

Correspondence to Loutfouz Zaman .

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Editors and Affiliations

  1. Purdue University, West Lafayette, IN, USA

    Vincent G. Duffy

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Hossain, M.Y., Azhar, U., To, Y., Choi, J., Zaman, L. (2021). Automated Escalation and Incident Management in Healthcare During Mass Casualties and Pandemic Events. In: Duffy, V.G. (eds) Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. AI, Product and Service. HCII 2021. Lecture Notes in Computer Science(), vol 12778. Springer, Cham. https://doi.org/10.1007/978-3-030-77820-0_6

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  • DOI: https://doi.org/10.1007/978-3-030-77820-0_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-77819-4

  • Online ISBN: 978-3-030-77820-0

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