Abstract
Introduction: Since the 1990s, the emergency department (ED) unscheduled return visit (URV), or “bounce-back,” has been used as a quality of care measurement. During that time, resident training was also scrutinized and uncovered a need for closer resident supervision, especially of second-year residents. Over the years, bounce-backs have continued to be analyzed with vigor, but research on residency training and supervision has lagged with few studies concurrently investigating residency supervision and bounce-backs. Other literature on resident supervision suggests that with adequate attending supervision, resident performance is equivalent to attending performance. With that in mind, it was hypothesized that resident bounce-back rates will be equivalent to attending bounce-back rates, and there will be no change among residency years. The primary objective of this study was to determine the rate at which patients are seen as a bounce-back visit within 72 hours of their initial visit to a community hospital ED during the study time frame. The secondary aims were to evaluate if the ED bounce-back rate is impacted by training level (residents or attending) and to describe bounce-back patient characteristics, including primary complaint/disease, age, comorbidities and issues with compliance.
Methods: A retrospective chart review of 1000 charts was conducted from September 2015 to September 2017. Charts were randomly selected by the Quality & Patient Safety (QPS) team and, after applying inclusion/exclusion criteria, 732 charts were analysed. Inclusion criteria included age ≥ 18 years, patients treated by an Emergency Medicine (EM) resident during their initial visit and patients with a “discharge” disposition. Exclusion criteria included patients seen as a scheduled return visit (e.g., two-day return for blood pregnancy recheck, wound check, etc.). Demographics, initial visit variables, comorbidities and bounce-back data were collected based on electronic record query or chart review. Data was analysed using means, standard deviations, medians and ranges for continuous variables. Logistic regression modelling techniques were used to examine factors that affect whether the patient had a bounce-back visit.
Results: The rate of URVs within 72 hours of the patient's initial visit was 4.65%. PGY1 and PGY2's bounce-back rate was 3.8% and 3.6%, respectively, and PGY3 and PGY4's bounce-back rate was 5.7% and 5.6%, respectively (p-value=.63). There was no statistically significant change among residency years. Most bounce-back characteristics analysed including primary complaint, age, and comorbidities demonstrated no statistical significance in the increased rate of bounce-back except for patients with a history of tobacco abuse, alcohol abuse and chronic pain. Current smokers were 6.5 times more likely to bounce back than former smokers (odds ratio=6.485, 95% confidence interval = 2.089 to 20.133, p-value=0.0012) and those with chronic pain were 2.5 times more likely to bounce back than those without chronic pain (odds ratio=2.518, 95% confidence interval =1.029 to 6.164, p=0.0431).
Conclusion: EM residency training year does not increase the frequency of bounce-backs in a community hospital ED. Finally, patients with substance abuse and chronic pain were more likely to bounce back.
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