title: The impact of an ED-only full-capacity protocol.
abstract: OBJECTIVE
  The objective of this study was to assess the impact of an emergency department (ED)-only full-capacity protocol and diversion, controlling for patient volumes and other potential confounding factors.
  
  
  METHODS
  This was a preintervention and postintervention cohort study using data 12 months before and 12 months after the implementation of the protocol. During the implementation period, attending physicians and charge nurses were educated with clear and simple figures on the criteria for the initiation of the new protocol. A multiple logistic regression model was used to compare ambulance diversion between the 2 periods.
  
  
  RESULTS
  The proportion of days when the ED went on diversion at least once during a 24-hour period was 60.4% during the preimplementation period and 20% in the postimplementation periods (P < .001). In the multivariate logistic regression model, the use of the new protocol was significantly associated with decreased odds of diversion rate in the postimplementation period (odds ratio, 0.32; 95% confidence interval, 0.21-0.48).
  
  
  CONCLUSIONS
  Our predivert/full-capacity protocol is a simple and generalizable strategy that can be implemented within the boundaries of the ED and is significantly associated with a decreased diversion rate.
authors.affiliation: Center for Policy and Research in Emergency Medicine, Oregon Health and Science University, Portland, OR, USA. wataset@ohsu.edu
authors.forename: Taketo
authors.initials: T
authors.lastname: Watase
authors.forename: Rongwei
authors.initials: R
authors.lastname: Fu
authors.forename: Denise
authors.initials: D
authors.lastname: Foster
authors.forename: Denise
authors.initials: D
authors.lastname: Langley
authors.forename: Daniel A
authors.initials: DA
authors.lastname: Handel
mesh_terms: D000552:Ambulances; D002985:Clinical Protocols; D015331:Cohort Studies; D003441:Crowding; D004636:Emergency Service, Hospital / Q000458:organization & administration / Q000706:statistics & numerical data; D006801:Humans; D007902:Length of Stay; D016015:Logistic Models; D010360:Patient Transfer / Q000379:methods / Q000458:organization & administration / Q000706:statistics & numerical data; D013997:Time Factors