Triage Decisions
Triage Nurse Prediction of Hospital Admission

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Introduction

Numerous factors affect patient flow in the emergency department. One important factor that has a negative impact on flow is ED patients waiting for an inpatient bed. It currently takes approximately 5 hours from triage to a request for an inpatient bed in our emergency department. Knowledge of patients requiring admission early in their ED evaluation could speed up the process of securing a bed. The objective of this study was to determine if an ED triage nurse (TRN) can determine at triage if a patient will be admitted to an inpatient unit. A secondary objective was to measure the confidence of the TRN prediction.

Methods

A prospective, non-consecutive study was conducted during an 18-day period in 2010 in a community hospital emergency department treating 76,000 patients. Experienced TRNs were trained in the evaluation tool. Immediately after the initial TRN evaluation, a determination was made in writing by the TRN regarding the likelihood of hospital admission and level of confidence in this decision. Patients who did not enter the emergency department through triage (ambulance) or were younger than 18 years were excluded.

Results

A total of 3514 patients approached triage. Of these patients, 1866 were eligible for the study and 1164 (62%) were enrolled. We excluded 25 subjects because of missing data, resulting in 1139 subjects. Missed subjects had the same baseline characteristics. A total of 287 (25.2%) hospital admissions occurred. TRN predicted 217 admissions, with a sensitivity of 75.6% (95% confidence interval [CI] 71.3-79.5) and a specificity of 84.5% (95% CI 83.1-85.8). The TRN reported being extremely confident in the prediction 50.1% of the time. In these cases, the TRN demonstrated an admission sensitivity of 81.6% (95% CI 76.5-85.8) and specificity of 93.1% (95% CI 91.8-94.3).

Conclusions

The TRN demonstrated a high sensitivity and specificity in admission prediction at triage and could potentially save many hours in requesting an inpatient bed. This increased efficiency could result in a more rapid ED throughput and decreased ED boarding.

Section snippets

Methods

A prospective, non-consecutive study was conducted for 18 consecutive days from March to April 2010 in a community hospital emergency department with 76,000 visits per year and a 28.6% admission rate. Experienced triage nurses were trained in the evaluation tool before starting the study. Thirty-six triage nurses were involved in the study. We require our triage nurses to have at least 1 year of ED experience, complete a triage class, work in triage one-on-one with our clinical nurse specialist

Results

During the study period, the triage nurses encountered a total of 3514 patients. Excluded were 1105 (31%) patients that arrived by ambulance and 543 (15%) patients younger than 18 years, leaving 1866 patients eligible for the study. Of these patients, 1164 (62%) were enrolled by triage nurses. We excluded 25 subjects for missing data, resulting in 1139 subjects analyzed in the dataset. Of these patients, 45% were male, and the mean age was 45 years (SD 18.7). The Emergency Severity Index

Discussion

Throughput of patients in the emergency department is an important contributor to ED and hospital overcrowding. The “boarding” of patients admitted in the emergency department results in decreased quality of care for these patients and all other ED patients, a long through-put for all ED patients, and decreased ED patient satisfaction.6 In our institution, the mean time from triage to requesting an inpatient bed is 5 hours. The time from bed request to actually moving to the inpatient bed is

Implications for ED Nurses

The results of our study indicate that triage nurses can accurately predict hospital admission. The ability to predict admission could be the first step in the process of decreasing lengths of stay in the emergency department. Where should we go from here? When the triage nurse predicts admission, an effort should be made to expedite care in the emergency department by alerting the admission placement department, notifying the admitting doctor early in the process, and initiating diagnostic

Limitations

Our study did not include patients who arrived by ambulance. These patients have a higher likelihood of admission and, if included in the study, would actually increase the sensitivity and specificity of the nurse predictions. This series of triage patients was non-consecutive, which may have resulted in selection bias. However, we compared the demographic data of the non-enrolled patients with the enrolled patients, and they were similar (Table 1). Variation likely existed among the triage

Conclusions

The triage prediction tool used by emergency nurses in this study demonstrated a high sensitivity and specificity in admission prediction at triage and could potentially save many hours in requesting an inpatient bed, which could result in a more rapid ED throughput and decreased ED boarding.

Blythe Stover-Baker is an Advanced Clinical Nurse, Department of Emergency Medicine, York Hospital—WellSpan Health, York, PA.

References (8)

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Blythe Stover-Baker is an Advanced Clinical Nurse, Department of Emergency Medicine, York Hospital—WellSpan Health, York, PA.

Barbara Stahlman is a Clinical Research Associate, Department of Emergency Medicine, York Hospital—WellSpan Health, York, PA.

Marc Pollack is an Attending Physician, Department of Emergency Medicine, York Hospital—WellSpan Health, York, PA.

Section Editors: Andi L. Foley, RN, MSN, CEN, and Patricia Kunz Howard, PhD, RN, CEN, CPEN, NE-BC, FAEN

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