Published, Version of Record (VoR)Open Access via Drexel Libraries Read and Publish Program 2025CC BY V4.0, Open
Abstract
Empirical studies in HCI Human computer interaction (HCI) Human-centered computing
In addition to aiding decision making, AI-based clinical decision-support systems may need to consider and support provider agency and collaboration between medical providers. We analyzed collaboration and agency within fast-response teams, identifying implications for designing decision-support systems that not only facilitate decision making, but also collaboration and agency. Using an Actor-Network Theory approach, we reviewed videos of 12 pediatric trauma resuscitations and conducted a secondary analysis of 27 interviews with trauma team members. We identified actants in trauma resuscitation, shifts in agency that can occur within fast-response teams during medical emergencies, and factors considered by providers when envisioning the design of decision-support systems. From our analysis, we propose implications for existing human-AI interaction guidelines when designing AI systems for fast-response medical teams. We also highlight parallels between the introduction of clinical practice guidelines and the introduction of AI-based decision-support systems, suggesting that these systems may influence the training and ''clinical gaze'' of providers.
Beyond Decision Making: Considering Collaboration and Agency in the Design of AI-Based Decision-Support Systems for Fast-Response Medical Teams
Creators
Angela Mastrianni - Drexel University
Paige Kmetz-Cutrone - Drexel University
Kathryn Chang - Drexel University
Jonathan Y Stein - Drexel University
Aleksandra Sarcevic (Corresponding Author) - Drexel University
Publication Details
Proceedings of the ACM on human-computer interaction, v 9(7), pp 1-28
Publisher
Association for Computing Machinery
Number of pages
28
Grant note
2R01LM011834-05 / National Institutes of Health (https://doi.org/10.13039/100000002)
2041772 / National Science Foundation (https://doi.org/10.13039/100000001)
Resource Type
Journal article
Language
English
Academic Unit
Information Science; College of Medicine; College of Computing and Informatics
Web of Science ID
WOS:001615063600001
Scopus ID
2-s2.0-105019250696
Other Identifier
991022123483404721
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