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5 Fireside Chat - Using Artificial Intelligence to Predict the Occurrence of Sepsis
Pages 17-19

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From page 17...
... Sepsis Watch, however, has been integrated into the everyday operations of the Duke University emergency department to help improve patient care for those indi­viduals who are at risk for developing sepsis.2 Sepsis Watch, as Elish described, involves a deep learning model that appears to be working smoothly, and clinicians feel it has improved patient care for sepsis, though the associated clinical trial was just concluding at the time of this workshop. Wucker cited a line from the Sepsis Watch research publication3 that said, "AI interventions must always be thought of as sociotechnical systems in which social context, relationships, and power dynamics are central, not an afterthought," and she asked Elish to explain the concept of sociotechnical systems and how that concept played out in Sepsis Watch.
From page 18...
... Elish noted that the treating physician does not directly see the Sepsis Watch model output, nor does the model produce a pop-up notice in the electronic health record. This workflow, she said, may seem Byzantine, but it was intentionally designed this way because the clinician leading this project had tried previously to develop sepsis care advisories that included such pop-ups, and the nurses routinely ignored them because of alert fatigue.
From page 19...
... The Sepsis Watch paper notes that ground truth is hard to find regarding sepsis, and Wucker encouraged Elish to talk about why ground truth is important and what to do when it cannot be quantified. Elish replied that the ground truth issue stems at least in part from the lack of a uniform definition of sepsis.


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