Skåne Emergency Department Assessment of Patient Load (SEAL)-A Model to Estimate Crowding Based on Workload in Swedish Emergency Departments

Emergency department (ED) crowding is an increasing problem in many countries. The purpose of this study was to develop a quantitative model that estimates the degree of crowding based on workload in Swedish EDs. At five different EDs, the head nurse and physician assessed the workload on a scale fr...

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Veröffentlicht in:PloS one 2015-06, Vol.10 (6), p.e0130020-e0130020
Hauptverfasser: Wretborn, Jens, Khoshnood, Ardavan, Wieloch, Mattias, Ekelund, Ulf
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Sprache:eng
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Zusammenfassung:Emergency department (ED) crowding is an increasing problem in many countries. The purpose of this study was to develop a quantitative model that estimates the degree of crowding based on workload in Swedish EDs. At five different EDs, the head nurse and physician assessed the workload on a scale from 1 to 6 at randomized time points during a three week period in 2013. Based on these assessments, a regression model was created using data from the computerized patient log system to estimate the level of crowding based on workload. The final model was prospectively validated at the two EDs with the largest census. Workload assessments and data on 14 variables in the patient log system were collected at 233 time points. The variables Patient hours, Occupancy, Time waiting for the physician and Fraction of high priority (acuity) patients all correlated significantly with the workload assessments. A regression model based on these four variables correlated well with the assessed workload in the initial dataset (r2 = 0.509, p < 0.001) and with the assessments in both EDs during validation (r2 = 0.641; p < 0.001 and r2 = 0.624; p < 0.001). It is possible to estimate the level of crowding based on workload in Swedish EDs using data from the patient log system. Our model may be applicable to EDs with different sizes and characteristics, and may be used for continuous monitoring of ED workload. Before widespread use, additional validation of the model is needed.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0130020