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Designing computerized approaches to support complex teamwork requires an understanding of how activity-related information is relayed among team members. In this paper, we focus on verbal communication and describe a speech-based model that we developed for tracking activity progression during time-critical teamwork. We situated our study in the emergency medical domain of trauma resuscitation and transcribed speech from 104 audio recordings of actual resuscitations. Using the transcripts, we first studied the nature of speech during 34 clinically relevant activities. From this analysis, we identified 11 communicative events across three different stages of activity performance-before, during, and after. For each activity, we created sequential ordering of the communicative events using the concept of narrative schemas. The final speech-based model emerged by extracting and aggregating generalized aspects of the 34 schemas. We evaluated the model performance by using 17 new transcripts and found that the model reliably recognized an activity stage in 98% of activity-related conversation instances. We conclude by discussing these results, their implications for designing computerized approaches that support complex teamwork, and their generalizability to other safety-critical domains.more » « less
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We describe an initial analysis of speech during team-based medical scenarios and its potential to indicate process delays in an emergency medical setting. We analyzed the speech of trauma resuscitation teams in cases with delayed intravenous/intraosseous (IV/IO) line placement, a significant contributor to delays during life-saving interventions. The insights gained from this analysis will inform the design of a clinical decision support system (CDSS) that will use multiple sensor modalities to alert medical teams to errors in real time. We contribute to the literature by determining how the intention of each speech line and the sentence can support real-time, automatic detection of delays during time-critical team activities.more » « less
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We describe an experiment conducted with three domain experts to understand how well they can recognize types and performance stages of activities using speech data transcribed from verbal communications during dynamic medical teamwork. The insights gained from this experiment will inform the design of an automatic activity recognition system to alert medical teams to process deviations in real time. We contribute to the literature by (1) characterizing how domain experts perceive the dynamics of activity-related speech, and (2) identifying the challenges associated with system design for speech-based activity recognition in complex team-based work settings.more » « less
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Abstract Introduction Non‐routine events (NREs) are atypical or unusual occurrences in a pre‐defined process. Although some NREs in high‐risk clinical settings have no adverse effects on patient care, others can potentially cause serious patient harm. A unified strategy for identifying and describing NREs in these domains will facilitate the comparison of results between studies.
Methods We conducted a literature search in PubMed, CINAHL, and EMBASE to identify studies related to NREs in high‐risk domains and evaluated the methods used for event observation and description. We applied The Joint Commission on Accreditation of Healthcare Organization (JCAHO) taxonomy (cause, impact, domain, type, prevention, and mitigation) to the descriptions of NREs from the literature.
Results We selected 25 articles that met inclusion criteria for review. Real‐time documentation of NREs was more common than a retrospective video review. Thirteen studies used domain experts as observers and seven studies validated observations with interrater reliability. Using the JCAHO taxonomy, “cause” was the most frequently applied classification method, followed by “impact,” “type,” “domain,” and “prevention and mitigation.”
Conclusions NREs are frequent in high‐risk medical settings. Strengths identified in several studies included the use of multiple observers with domain expertise and validation of the event ascertainment approach using interrater reliability. By applying the JCAHO taxonomy to the current literature, we provide an example of a structured approach that can be used for future analyses of NREs.