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Table 1.  
Univariate Analysis of Baseline vs Intervention Cohorts
Univariate Analysis of Baseline vs Intervention Cohorts
Table 2.  
Factors That Significantly Affected ED Boarding Time per SDU Admission by Multivariable Analysis
Factors That Significantly Affected ED Boarding Time per SDU Admission by Multivariable Analysis
1.
United States Government Accountability Office. Hospital emergency departments: crowding continues to occur, and some patients wait longer than recommended time frames.http://www.gao.gov/new.items/d09347.pdf. Published April 2009. Accessed June 20, 2014.
2.
Agency for Healthcare Research and Quality. Emergency Severity Index (ESI): a triage tool for emergency department care. Version 4.http://www.ahrq.gov/professionals/systems/hospital/esi/esihandbk.pdf. Accessed June 20, 2014.
3.
Murphy  SO, Barth  BE, Carlton  EF, Gleason  M, Cannon  CM.  Does an ED flow coordinator improve patient throughput [published online June 25, 2014]? J Emerg Nurs. doi:10.1016/j.jen.2014.03.007.
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Research Letter
February 2015

A Simple Intervention to Improve Hospital Flow From Emergency Department to Inpatient Units

Author Affiliations
  • 1Department of Emergency Medicine, Harbor-UCLA (University of California, Los Angeles) Medical Center, Los Angeles
  • 2Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Los Angeles
  • 3David Geffen School of Medicine, UCLA, Los Angeles
  • 4Department of Nursing, Harbor-UCLA Medical Center, Los Angeles
  • 5Department of Surgery, Harbor-UCLA Medical Center, Los Angeles
  • 6Medical Administration, Harbor-UCLA Medical Center, Los Angeles
  • 7Los Angeles County + University of Southern California Medical Center, Los Angeles
  • 8Department of Medicine, Keck University School of Medicine, University of Southern California, Los Angeles
JAMA Intern Med. 2015;175(2):289-290. doi:10.1001/jamainternmed.2014.6689

Improving the flow of patients from the emergency department (ED) through the inpatient setting is one of the most vexing problems in hospital management. At Harbor-UCLA Medical Center, a public hospital and level 1 trauma center, patient flow from the ED to the inpatient setting is a serious and constant concern. Because ED wait times depend on the availability of inpatient beds capable of supporting the level of care required for admitted patients,1 we developed an intervention to assist physicians in identifying patients early in the day who could be transferred to a lower level of care.

Methods

We conducted a pre-post, quasiexperimental study comparing patient flow metrics after vs before the intervention. The study was deemed exempt by the institutional review board of the Los Angeles Biomedical Research Institute. On October 15, 2013, a nursing position was repurposed to create a coordinator who monitored all beds and, during weekday business hours, applied appropriate use criteria abstracted from hospital policy to patients in step-down units (SDUs). For patients who did not meet appropriate use criteria, the coordinator paged the patient’s supervising resident physician. Without the authority to initiate the transfer, the coordinator primarily served to initiate a dialogue regarding whether the transfer was possible, seeking to initiate transfers earlier in the day.

Results

From November 1, 2012, through March 14, 2014, a total of 4597 patients were admitted from the ED to a bed in the SDU (Table 1). The median hospital census during this period was 334 (interquartile range [IQR], 320-346; 85% capacity). The median emergency severity index2 level for admissions was 2 (IQR, 2-2). Overall, the median boarding time (the time spent in the ED between the admission decision and the actual physical move of the patient to an inpatient bed) for these admitted patients was 365 minutes (IQR, 220-649 minutes). The intervention cohort (October 15, 2013–March 14, 2014) consisted of 1649 patients (35.9%) compared with 2948 patients (64.1%) in the baseline cohort (November 1, 2012–October 14, 2013).

After adjustment by multivariable analysis, the intervention was associated with less boarding time, on average, by 100 minutes per patient admitted to a bed in the SDU (95% CI, 74-126; P < .001) (Table 2). Other factors that remained significant predictors of boarding were hour of admission, hospital census, SDU census, the number of SDU nurses working each shift, and admission to a surgical vs a medical service (Table 2). We also separately analyzed all admissions (n = 14 525), including to the wards and intensive care units, and the intervention was associated with a 30-minute decrease in boarding time per patient overall (95% CI, 17-43; P < .001).

The intervention period was also associated with a decrease in the time during which there was either dangerous hospital overcrowding (from a median of 94 to 32 h/mo in the baseline vs intervention periods) or critical hospital overcrowding (from a median of 33 to 0 h/mo from the baseline through the intervention periods). The time during which there was dangerous overcrowding per month tracked closely to the hospital census in the baseline (R2 = 0.6; P = .01) but not to the interventional period (R2 = 0.3; P = .30).

Discussion

Although many hospitals already have a bed coordinator, there is little quantitative data on the effect of having one. One recent study3 found that a bed coordinator focused only in the ED shortened the length of ED stay, but boarding time for admitted patients was not evaluated. Implementation of a coordinator who monitored all beds and initiated early patient transfers from beds in the SDU to those in the wards during the day was associated with reduced ED boarding times and time during which there was dangerous and critical hospital overcrowding.

Limitations of this study include the lack of concurrent control and the fact that it was a single-center study. Although single-centered, a large number of patients were evaluated, and the patient flow problems encountered at our hospital are common and intrinsic to hospitals generally. Thus, the results are likely generalizable, but perhaps to varying degrees, depending on the severity of the baseline patient flow problems at individual institutions.

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Article Information

Corresponding Author: Brad Spellberg, MD, Los Angeles County + University of Southern California Medical Center, 2051 Marengo St, Office C2K122, Los Angeles, CA 90033 (bspellberg@dhs.lacounty.gov).

Published Online: December 29, 2014. doi:10.1001/jamainternmed.2014.6689.

Author Contributions: Drs Fleischman and Spellberg had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Fleischman, Kaji, McKenzie, Soltero, Van Natta, Spellberg.

Acquisition, analysis, or interpretation of data: Fleischman, Kaji, Diaz, Van Natta, Spellberg.

Drafting of the manuscript: Fleischman, Kaji, Diaz, Soltero, Spellberg.

Critical revision of the manuscript for important intellectual content: Fleischman, Kaji, McKenzie, Van Natta, Spellberg.

Statistical analysis: Fleischman, Kaji, Diaz, Soltero.

Administrative, technical, or material support: Kaji, McKenzie, Van Natta, Spellberg.

Study supervision: Van Natta, Spellberg.

Conflict of Interest Disclosures: None reported.

Additional Contributions: We thank Roger J. Lewis, MD, PhD, Department of Emergency Medicine, Harbor-UCLA Medical Center, for input on experimental design and analysis, and for careful review and revisions to the manuscript; Kyle Tan, BS, Department of Emergency Medicine, Harbor-UCLA Medical Center, for developing some of the methods used to prepare the hospital census data for analysis; and Mitchell Katz, MD, Department of Health Services, Los Angeles County, for careful review and revisions to the manuscript. None received financial compensation.

References
1.
United States Government Accountability Office. Hospital emergency departments: crowding continues to occur, and some patients wait longer than recommended time frames.http://www.gao.gov/new.items/d09347.pdf. Published April 2009. Accessed June 20, 2014.
2.
Agency for Healthcare Research and Quality. Emergency Severity Index (ESI): a triage tool for emergency department care. Version 4.http://www.ahrq.gov/professionals/systems/hospital/esi/esihandbk.pdf. Accessed June 20, 2014.
3.
Murphy  SO, Barth  BE, Carlton  EF, Gleason  M, Cannon  CM.  Does an ED flow coordinator improve patient throughput [published online June 25, 2014]? J Emerg Nurs. doi:10.1016/j.jen.2014.03.007.
PubMed
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