Proceedings of the CHI Conference on Human Factors in Computing Systems 2024
DOI: 10.1145/3613904.3641982
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Investigating Why Clinicians Deviate from Standards of Care: Liberating Patients from Mechanical Ventilation in the ICU

Nur Yildirim,
Susanna Zlotnikov,
Aradhana Venkat
et al.

Abstract: Clinical practice guidelines, care pathways, and protocols are designed to support evidence-based practices for clinicians; however, their adoption remains a challenge. We set out to investigate why clinicians deviate from the "Wake Up and Breathe" protocol, an evidence-based guideline for liberating patients from mechanical ventilation in the intensive care unit (ICU). We conducted over 40 hours of direct observations of live clinical workflows, 17 interviews with frontline care providers, and 4 co-design wor… Show more

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Cited by 3 publications
(1 citation statement)
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“…Because of this complexity and uncertainty, there is significant variation in care delivery and outcomes for people receiving IMV with large inequities between rural and urban hospitals (Balas et al, 2022; Harlan et al, 2024; Kalhan et al, 2006; Mikkelsen et al, 2008; Qadir et al, 2021). By reducing unwarranted variation in care patterns, an artificial intelligence (AI) clinical decision support system (CDSS) could ameliorate uncertainty in these complex decisions (Chen et al, 2022; Gandhi et al, 2023) support personalized treatment recommendations,(Shah et al, 2021; Yildirim et al, 2024a), and overcome known barriers to optimal IMV care (Dexter and Schleyer, 2022; Fitzpatrick and Ellingsen, 2013; Yildirim et al, 2024b). Previously developed IMV CDSSs have focused on only one or a handful treatment decisions, and none provides suggestions for more than five ventilator settings simultaneously (Tehrani and Roum, 2008).…”
Section: Introductionmentioning
confidence: 99%
“…Because of this complexity and uncertainty, there is significant variation in care delivery and outcomes for people receiving IMV with large inequities between rural and urban hospitals (Balas et al, 2022; Harlan et al, 2024; Kalhan et al, 2006; Mikkelsen et al, 2008; Qadir et al, 2021). By reducing unwarranted variation in care patterns, an artificial intelligence (AI) clinical decision support system (CDSS) could ameliorate uncertainty in these complex decisions (Chen et al, 2022; Gandhi et al, 2023) support personalized treatment recommendations,(Shah et al, 2021; Yildirim et al, 2024a), and overcome known barriers to optimal IMV care (Dexter and Schleyer, 2022; Fitzpatrick and Ellingsen, 2013; Yildirim et al, 2024b). Previously developed IMV CDSSs have focused on only one or a handful treatment decisions, and none provides suggestions for more than five ventilator settings simultaneously (Tehrani and Roum, 2008).…”
Section: Introductionmentioning
confidence: 99%