Triage DecisionsTriage Nurse Prediction of Hospital Admission
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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(April 2009)
Cited by (21)
The effect of emergency department nurse experience on triage decision making
2022, Human Factors in HealthcareProvider-in-triage prediction of hospital admission after brief patient interaction
2021, American Journal of Emergency MedicineCitation Excerpt :Using these variables and natural language analysis, some authors have described successful attempts to create algorithms and more complex neural networks to predict admission [9-11]. When individual providers attempt to predict admission, there is significant variability between paramedics, triage nurses, family members and physicians [12-14]. In prior work, we have shown that physicians' ability to predict admission by real-time chart review alone is moderate and is worse than the ability to predict discharge (sensitivity 51.8%, specificity 89.1%) [15].
Reliability and validity of three international triage systems within a private health-care group in the Middle East
2020, International Emergency NursingCitation Excerpt :It may be that the highest and lowest severities are the easiest to recognise and would seldom be incorrectly categorised. Reliability and validity studies of the CTAS, the MTS and the ESI have shown similar findings and variations between these systems, using both vignettes and actual patient triage evaluations [16,18–30]. The accuracy across all four ECs was consistently good to very good and was apparent in the distribution of triage category allocations.
Can Triage Nurses Accurately Predict Patient Dispositions in the Emergency Department?
2016, Journal of Emergency NursingCitation Excerpt :Several studies have examined the ability of a triage nurse to predict patient disposition. The studies have found only moderate sensitivity and positive predictive values ranging from 54% to 76%.7–9 Furthermore, evidence indicates that triage nurses were more successful in predicting admissions for higher-acuity patients, as well as predicting discharges for patients with injuries or febrile illnesses.10
A Pragmatic Randomized Evaluation of a Nurse-Initiated Protocol to Improve Timeliness of Care in an Urban Emergency Department
2016, Annals of Emergency MedicineCitation Excerpt :The department being evaluated once had a triage physician, but the position’s funding was discontinued before the evaluation. Triage nurses in a 2012 study demonstrated a 76% sensitivity and 85% specificity when predicting patient admission,25 implying potential untapped utility in streaming patients accordingly. To our knowledge, this is the first study to combine the Revised Standards for Quality Improvement Reporting Excellence26 with the Consolidated Standards of Reporting Trials27 pragmatic trials extension to evaluate nurse-initiated protocols.
Emergency department boarding times for patients admitted to intensive care unit: Patient and organizational influences
2014, International Emergency Nursing
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
Submissions to this column are encouraged and may be sent to
Andi L. Foley, RN, MSN, CEN[email protected]
or
Patricia Kunz Howard, PhD, RN, CEN, CPEN, NE-BC, FAEN[email protected]