Publications by authors named "Amit M Mehta"
Article Synopsis
- The study aimed to evaluate the effectiveness of the Epic Sepsis Predictive Model (ESPMv1) alert system in emergency departments by tracking its performance in identifying patients at risk for sepsis over the course of a year.
- Out of nearly 146,000 patient encounters, the ESPMv1 alert was triggered in only 4.9% of cases, detecting sepsis in 2253 encounters while missing it in many others, leading to low sensitivity (14.7%) but high specificity (95.3%).
- The findings suggest that the alert system offers minimal help to physicians in diagnosing sepsis, as most cases were treated without alert notifications, indicating the tool's limited diagnostic utility
Providing timely and effective care in the emergency department (ED) requires the management of individual patients as well as the flow and demands of the entire department. Strategic changes to work processes, such as adding a flow coordination nurse or a physician in triage, have demonstrated improvements in throughput times. However, such global strategic changes do not address the real-time, often opportunistic workflow decisions of individual clinicians in the ED.
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