Quantifying the Impact of Resuscitation-Team Activation in Hospital Emergency Departments

Xiaochen Xian, Devashish Das, Kalyan S. Pasupathy, Eric T. Boie, Mustafa Sir

Research output: Contribution to journalArticlepeer-review

Abstract

Hospital emergency department (ED) operations are affected when critically ill or injured patients arrive. Such events often lead to the initiation of specific protocols, referred to as Resuscitation-team Activation (RA), in the ED of Mayo Clinic, Rochester, MN where this study was conducted. RA events lead to the diversion of resources from other patients in the ED to provide care to critically ill patients; therefore, it has an impact on the entire ED system. This paper presents a data-driven and flexible statistical learning model to quantify the impact of RA on the ED. The model learns the pattern of operations in the ED from historical patient arrival and departure timestamps and quantifies the impact of RA by measuring the deviation of the departure of patients during RA from normal processes. The proposed method significantly outperforms baseline methods based on measuring the average time patients spend in the ED.

Original languageEnglish (US)
Article number9099613
Pages (from-to)3029-3037
Number of pages9
JournalIEEE Journal of Biomedical and Health Informatics
Volume24
Issue number10
DOIs
StatePublished - Oct 2020

Keywords

  • Emergency department
  • functional regression
  • interruptive events
  • large-scale service systems
  • resuscitation

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Health Information Management

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