ObjectiveOvercrowding is common in most emergency departments (ED). Despite the use of validated triage systems, some patients are at risk of delayed medical evaluation. The objective of this study was to assess the impact of a patient-flow physician coordinator (PFPC) on the proportion of patients offered medical evaluation within time limits imposed by the Swiss Emergency Triage Scale (SETS) and on patient flow within the emergency department of a teaching urban hospital.MethodsIn this before-after retrospective cohort study, we compared the proportions of patients who received their first medical contact within SETS-imposed time limits, mean waiting times before first medical consultation, mean length of stay, and number of patients who left without being seen by a physician, between two periods before and after introducing a PFPC. The PFPC was a senior physician charged with quickly assessing in the waiting area patients who could not immediately be seen and managing patient flow within the department.ResultsBefore introducing the PFPC position, 33,605 patients were admitted, versus 36,288 after. Introducing a PFPC enabled the department to increase the proportion of patients seen within the SETS-imposed time limits from 60.1% to 69.0% (p <0.0001). Waiting times until first medical consultation were reduced on average by 27.7 minutes (95% confidence interval [95% CI]: 25.9–29.5, p < .0001). No significant differences were observed as to length of stay or number of patients who left without being seen between the two study periods.ConclusionsIntroducing a physician dedicated to managing patient flow enabled waiting times until first medical consultation to be reduced, yet had no significant benefit for patient flow within the ED, nor did it reduce the number of patients who left without being seen.

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Opioid use and associated morbidity and mortality have increased in several countries during the past 20 years. We performed a study whose objective was to assess the frequency and causes of opioid‐related emergency division (ED) visits in an adult tertiary Swiss University Hospital over 9 weeks in 2018. We primarily assessed opioid‐related adverse drug reactions (ADR), secondary overdose, misuse, abuse, and insufficient pain relief. Current opioid use was identified in 1037 (8.3%) of the 12 470 included ED visits. In 64 opioid users, an ADR was identified as a contributing cause of the ED visit, representing 6.2% of opioid users, and 0.5% of the total ED visits. Moreover, we identified an overdose in 16 opioid users, misuse or abuse in 19 opioid users, and compatible withdrawal symptoms in 7 opioid users. After pooling all these events, we conclude that the ED visits could be related to opioid use in 10.2% of opioid users. Finally, in 201 opioid users, insufficient pain relief (pain not responding to the current pharmacological treatment) was identified as a contributing cause of ED visits. In these cases, other factors than simply pharmacological nonresponse may have been involved. In the context of an ever‐increasing opioid use to better control chronic pain situations, these results should reinforce emergency network epidemiological surveillance studies at a national level.

Background While several studies aimed to identify risk factors for severe COVID-19 cases to better anticipate intensive care unit admissions, very few have been conducted on self-reported patient symptoms and characteristics, predictive of RT-PCR test positivity. We therefore aimed to identify those predictive factors and construct a predictive score for the screening of patients at admission. Methods This was a monocentric retrospective analysis of clinical data from 9081 patients tested for SARS-CoV-2 infection from August 1 to November 30 2020. A multivariable logistic regression using least absolute shrinkage and selection operator (LASSO) was performed on a training dataset (60% of the data) to determine associations between self-reported patient characteristics and COVID-19 diagnosis. Regression coefficients were used to construct the Coronavirus 2019 Identification score (COV19-ID) and the optimal threshold calculated on the validation dataset (20%). Its predictive performance was finally evaluated on a test dataset (20%). Results A total of 2084 (22.9%) patients were tested positive to SARS-CoV-2 infection. Using the LASSO model, COVID-19 was independently associated with loss of smell (Odds Ratio, 6.4), fever (OR, 2.7), history of contact with an infected person (OR, 1.7), loss of taste (OR, 1.5), muscle stiffness (OR, 1.5), cough (OR, 1.5), back pain (OR, 1.4), loss of appetite (OR, 1.3), as well as male sex (OR, 1.05). Conversely, COVID-19 was less likely associated with smoking (OR, 0.5), sore throat (OR, 0.9) and ear pain (OR, 0.9). All aforementioned variables were included in the COV19-ID score, which demonstrated on the test dataset an area under the receiver-operating characteristic curve of 82.9% (95% CI 80.6%–84.9%), and an accuracy of 74.2% (95% CI 74.1%–74.3%) with a high sensitivity (80.4%, 95% CI [80.3%–80.6%]) and specificity (72.2%, 95% CI [72.2%–72.4%]). Conclusions The COV19-ID score could be useful in early triage of patients needing RT-PCR testing thus alleviating the burden on laboratories, emergency rooms, and wards.

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