Emergency medical services (EMS) providers often face significant challenges in their work, including collecting, integrating, and making sense of a variety of information. Despite their criticality, EMS work is one of the very few medical domains with limited technical support. To design and implement effective decision support, it is essential to examine and gain a holistic understanding of the fine-grained process of sensemaking in the field. To that end, we
reviewed 25 video recordings of EMS simulations to understand the nuances of EMS sensemaking work, including 1) the types of information and situation that are collected and made sense of in the field; 2) the work practices and temporal patterns of EMS sensemaking work; and 3) the challenges in EMS sensemaking and decision-making process. Based on the results, we discuss implications for technology opportunities to support rapid information
acquisition and sensemaking in time-critical, high-risk medical settings such as EMS.
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Data Work and Decision Making in Emergency Medical Services: A Distributed Cognition Perspective
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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- Award ID(s):
- 1948292
- PAR ID:
- 10328380
- Date Published:
- Journal Name:
- Proceedings of the ACM on Human-Computer Interaction
- Volume:
- 5
- Issue:
- CSCW2
- ISSN:
- 2573-0142
- Page Range / eLocation ID:
- 1 to 32
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3479500
