Robin Clouston1, Paul Atkinson2, Donaldo D Canales3, Jacqueline Fraser4, Dylan Sohi5, Scott Lee6, Michael Howlett2. 1. Department of Emergency Medicine, Dalhousie University, Saint John Regional Hospital, 400 University Avenue, Saint John, NB, E2L 4L2, Canada. robin.clouston@dal.ca. 2. Department of Emergency Medicine, Dalhousie University, Saint John Regional Hospital, 400 University Avenue, Saint John, NB, E2L 4L2, Canada. 3. Research Services, Horizon Health Network, Saint John, NB, Canada. 4. Department of Emergency Medicine, Horizon Health Network, Saint John, NB, Canada. 5. Memorial University, St John's, NL, Canada. 6. Dalhousie University, Halifax, NS, Canada.
Abstract
INTRODUCTION: Emergency department (ED) crowding compromises patient outcomes. Existing crowding measures are complex and difficult to use in real-time. This study evaluated readily available single flow variables as crowding measures. METHODS: Over 2 weeks in a tertiary Canadian ED, we recorded the following potential crowding measures during 168 consecutive two-hour study intervals: total ED patients (census), patients in beds, patients in waiting rooms, patients in treatment areas awaiting MD assessment; number of inpatients boarding, and ED occupancy. We also calculated four complex crowding scores-NEDOCS, EDWIN, ICMED, and a local modification of NEDOCS. We performed ROC analyses to assess the predictive validity of these measures against a reference standard of physician perception of crowding. RESULTS: We gathered data for 144 (63.9%) of 168 study intervals. ED census correlated strongly with crowding (AUC = 0.82, 95% CI 0.76-0.89), as did ED occupancy (AUC = 0.75, 95% CI 0.66-0.83). Their performance was similar to NEDOCS (AUC = 0.80) and to the local modification of NEDOCS (AUC = 0.83). CONCLUSION: ED occupancy as a single measure has similar predictive accuracy to complex crowding scores and is easily generalizable to diverse emergency departments. Real-time tracking of this simple indicator could be used to prompt investigation and implementation of crowding interventions.
INTRODUCTION: Emergency department (ED) crowding compromises patient outcomes. Existing crowding measures are complex and difficult to use in real-time. This study evaluated readily available single flow variables as crowding measures. METHODS: Over 2 weeks in a tertiary Canadian ED, we recorded the following potential crowding measures during 168 consecutive two-hour study intervals: total ED patients (census), patients in beds, patients in waiting rooms, patients in treatment areas awaiting MD assessment; number of inpatients boarding, and ED occupancy. We also calculated four complex crowding scores-NEDOCS, EDWIN, ICMED, and a local modification of NEDOCS. We performed ROC analyses to assess the predictive validity of these measures against a reference standard of physician perception of crowding. RESULTS: We gathered data for 144 (63.9%) of 168 study intervals. ED census correlated strongly with crowding (AUC = 0.82, 95% CI 0.76-0.89), as did ED occupancy (AUC = 0.75, 95% CI 0.66-0.83). Their performance was similar to NEDOCS (AUC = 0.80) and to the local modification of NEDOCS (AUC = 0.83). CONCLUSION: ED occupancy as a single measure has similar predictive accuracy to complex crowding scores and is easily generalizable to diverse emergency departments. Real-time tracking of this simple indicator could be used to prompt investigation and implementation of crowding interventions.
Authors: Grant D Innes; Marco L A Sivilotti; Howard Ovens; Kirstie McLelland; Adam Dukelow; Edmund Kwok; Anil Chopra; Ivy Cheng; Dan Kalla; David Mackinnon; Chad Kim Sing; Neil Barclay; Terry Ross; Alecs Chochinov Journal: CJEM Date: 2018-11-08 Impact factor: 2.410
Authors: Adrian Boyle; Paul Atkinson; Carlos Basaure Verdejo; Edward Chan; Robin Clouston; Paedar Gilligan; Karan Grewal; Ian Higginson; Paul Liston; Virginia Newcombe; Valerie Norton; Sophie Richter; George Stoica; Abel Wakai Journal: Eur J Emerg Med Date: 2019-12 Impact factor: 2.799
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