research-article

Data Work and Decision Making in Emergency Medical Services: A Distributed Cognition Perspective

Authors:

Pradeepti Upadhyayula,

Mustafa Ozkaynak,

Richard Harris,

Kathleen AdelgaisAuthors Info & Claims

Proceedings of the ACM on Human-Computer Interaction, Volume 5, Issue CSCW2

Article No.: 356, Pages 1 - 32

https://doi.org/10.1145/3479500

Published: 18 October 2021 Publication History

Abstract

Emergency medical services (EMS) teams are first responders providing urgent medical care to severely ill or injured patients in the field. Despite their criticality, EMS work is one of the very few medical domains with limited technical support. This paper describes a study conducted to examine technology opportunities for supporting EMS data work and decision-making. We transcribed and analyzed 25 simulation videos. Using the distributed cognition framework, we examined EMS teams' work practices that support information acquisition and sharing. Our results showed that EMS teams leveraged various mechanisms (e.g., verbal communication and external cognitive aids) to distribute cognitive labor in managing, collecting, and using patient data. However, we observed a set of prominent challenges in EMS data work, including lack of detailed documentation in real time, situation recall issues, situation awareness problems, and challenges in decision making and communication. Based on the results, we discuss implications for technology opportunities to support rapid information acquisition, integration, and sharing in time-critical, high-risk medical settings.

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Index Terms

Data Work and Decision Making in Emergency Medical Services: A Distributed Cognition Perspective
1. Human-centered computing
  1. Collaborative and social computing
    1. Empirical studies in collaborative and social computing

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cover image Proceedings of the ACM on Human-Computer Interaction

Proceedings of the ACM on Human-Computer Interaction Volume 5, Issue CSCW2

CSCW2

October 2021

5376 pages

EISSN:2573-0142

DOI:10.1145/3493286

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Published: 18 October 2021

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