Bellew, Shawna D.

AbstractObjectivesRapid response teams (RRTs) respond to signs of deterioration to avoid morbidity and mortality. Early RRT activation (eRRT) in patients admitted from the emergency department (ED) is associated with significantly increased mortality. Predicting these events may represent an opportunity to identify patients who would benefit from further resuscitation, aid disposition decision‐making, or improve communication between ED and inpatient providers. We aimed to create a clinical prediction instrument to quantify the risk of eRRT.MethodsWe performed an observational cohort study of patients admitted to a non–intensive care unit (ICU) setting who triggered eRRT from January 2009 to December of 2012 compared to those who did not trigger eRRT. Age, sex, ED vital sign measurements, and final ED diagnosis by ICD‐9 code were evaluated in a multivariable logistic regression model. The performance of prediction models was assessed using discrimination summarized by area under a receiver operating curve (AUC) and calibration with the Hosmer and Lemeshow goodness‐of‐fit test. The final model was used to create a simplified scoring system.ResultsThe eRRT group consisted of 474 patients who were compared to 2,575 patients in the reference group. Age and sex did not add significant discrimination to the model and were eliminated from the simplified, final model. This model, which included vital signs and diagnosis category, was found to have an AUC of 0.754 (95% confidence interval [CI] = 0.730 to 0.778) and was used to create a simplified scoring system. The odds ratio for the association of a 1‐unit increase in risk score with eRRT was 1.37 (95% CI = 1.32 to 1.41; p < 0.001). When internally validated, the score was found to have an AUC of 0.759 (95% CI = 0.735 to 0.753). Calculated scores ranged from −3 to 18, which corresponded to predicted probabilities of eRRT ranging from 5.1% to 72.2%.ConclusionsIn summary, the PeRRT score is a simple tool that can be referenced by emergency providers at the bedside to quantify the risk of early RRT activation and potential deterioration, helping to answer the question, “How likely is my patient to trigger an RRT activation in the next twelve hours?” Given that patients who trigger eRRT have an elevated risk of morbidity and mortality, higher scores should result in resuscitative intervention, further observation in the ED, consideration of ICU admission, or direct enhanced communication between ED and inpatient providers. A prospective multicenter study is required to further validate this instrument.

Background Atrial fibrillation (AF) is a common, growing, and costly medical condition. We aimed to evaluate the impact of a management algorithm for symptomatic AF that used an emergency department observation unit on hospital admission rates and patient outcomes. Methods and Results This retrospective cohort study compared 563 patients who presented consecutively in the year after implementation of the algorithm, from July 2013 through June 2014 (intervention group), with 627 patients in a historical cohort (preintervention group) who presented consecutively from July 2011 through June 2012. All patients who consented to have their records used for chart review were included if they had a primary final emergency department diagnosis of AF . We observed no significant differences in age, sex, vital signs, body mass index, or CHADS 2 (congestive heart failure, hypertension, age, diabetes mellitus, and prior stroke or transient ischemic attack) score between the preintervention and intervention groups. The rate of inpatient admission was significantly lower in the intervention group (from 45% to 36%; P <0.001). The groups were not significantly different with regard to rates of return emergency department visits (19% versus 17%; P =0.48), hospitalization (18% versus 16%; P =0.22), or adverse events (2% versus 2%; P =0.95) within 30 days. Emergency department observation unit admissions were 40% ( P <0.001) less costly than inpatient hospital admissions of ≤1 day's duration. Conclusions Implementation of an emergency department observation unit AF algorithm was associated with significantly decreased hospital admissions without increasing the rates of return emergency department visits, hospitalization, or adverse events within 30 days.