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Introduction: Emergency department unscheduled return visits within 72-h of discharge, called a "bounceback", have been used as a metric of quality of care. We hypothesize that specific demographics and dispositions may be associated with Emergency Medical Services (EMS) 72-h bouncebacks., Methods: For all patient encounters within one calendar year from a large, urban EMS agency, we recorded demographics (name, date of birth, race, gender), primary impression, disposition, and vital signs for EMS encounters. A bounceback was defined as a patient, identified by matching first name, last name and date of birth, with more than one EMS encounter within 72 h. We performed descriptive statistics for patients that did and did not have a subsequent bounceback using median (interquartile range) and Wilcoxon Rank Sum test for age and frequency (percent) and chi square test for gender, race and run disposition. For patients with a bounceback, we describe the frequency and percentage of EMS professional primary impressions on initial encounter., Results: 98,043 encounters from January 1, 2021 to December 31, 2021, were analyzed. The median age was 50 years (IQR 32-65); 49.4% (46,147) were female and 50.7% (47,376) were White patients. 3951 encounters had a subsequent bounceback, and compared to those without bouncebacks, they were more often male patients (58.7% versus 50.2%, p < 0.001) and more commonly not transported (22.3% versus 15.5%, p < 0.001). A multivariable logistic regression model estimated the odds of bounceback were lower for females [OR 0.64 (95% CI 0.61-0.68)], Asian and Latino patients compared to White patients [OR 0.33 (95% CI 0.21-0.53) and 0.42 (95% CI 0.34-0.51)], respectively, no significant difference for Black patients compared to White patients, and higher for non-transported patients [OR 1.25 (95% CI 1.16-1.34)]. The The most common EMS primary impression for initial and subsequent encounters was mental health [576 (14.7%) and 944 (17.0%), respectively]. For subsequent encounters, the primary impression was cardiac arrest or death in 67 (1.2%) of cases., Conclusion: Bouncebacks were common in this single year study of a high-volume urban EMS agency. Male and non-transported patients most often experienced bouncebacks. The most common primary impression for encounters with bounceback was mental health related. Out-of-hospital cardiac arrest occurred in 1 % of bounceback cases. Further study is necessary to understand the effect on patient-centered outcomes., (Copyright © 2022. Published by Elsevier Inc.)

Background: Obesity is a growing epidemic associated with higher rates of metabolic disease, heart disease and all-cause mortality. Heavier patients may require more advanced resources and specialized equipment. We hypothesize that increasing patient weight will be associated with longer prehospital on-scene times., Methods: We reviewed electronic patient care records for patients transported by two urban 9-1-1 emergency medical services (EMS) agencies. We collected age, sex, estimated patient weight, vital signs (systolic blood pressure, heart rate, pulse oximetry), provider impression, method of moving patient to ambulance, and on-scene times. We selected patients with time-sensitive diagnoses of stroke, ST-segment elevation myocardial infarction (STEMI), and trauma and compared on-scene times for patients who weighed above or below 300 pounds. We performed descriptive statistics, Mann-Whitney U tests for continuous variables and Chi-square tests for discrete variables. We constructed a generalized linear model to determine the effect of patient weight adjusted for covariates., Results: For a three-year period (May 1, 2018 to April 30, 2021) 48,203 patients were transported with an EMS impression of stroke, ST-segment elevation myocardial infarction (STEMI), and trauma. 23,654 (49.1%) patients were female, and the median age was 52 (IQR 34-68) years. The median weight was 175.0 (IQR 150.0-205.0) pounds. Patients above a dichotomous weight categorization of 300 pounds experienced a longer median scene time with any time-sensitive diagnosis (12.6 versus 11.9 min p < 0.001), STEMI (16.0 versus 13.1 min, p = 0.014) and blunt trauma (12.6 versus 11.9 min, p < 0.001)). They were more likely to be hypoxic (p < 0.001) and more likely to experience cardiac arrest (p < 0.001). They were less likely to walk to the ambulance (22.1% versus 32.2%, p < 0.001)., Conclusion: Patient weight above 300 pounds was associated with significantly longer on-scene time. These patients were more likely to be hypoxic, sustain a cardiac arrest, and less likely to walk to the ambulance., Competing Interests: Declaration of Competing Interest None., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Aim: We aimed to better understand variation in opioid prescribing practices by investigating physician factors at one academic suburban Emergency Department (ED)., Methods: We retrospectively reviewed the electronic medical records of all patients given opioid prescriptions in the Stanford Health Care ED from 2009 to 2018. We described the variation in opioid prescriptions over time from 2009 to 2018, then dove deeper into a single year (July 1, 2017 to July 1, 2018). We described the number and type of opioid prescriptions at discharge and variation in attending physician opioid prescribing patterns using independent t-tests and a Fischer's exact test., Results: From 2009 to 2018, 657,037 patient visits occurred; 92,612 (14.1%) opioid prescriptions were written. Opioid prescriptions increased from 2009, peaked in 2015, then decreased. Individual providers wrote opioid prescriptions for 1 to 17% of their discharged patients. There was no significant difference in opioid prescribing based on provider gender (p = 0.456), fellow or attending status (p = 0.390), residency completed at Stanford Hospital (p = 0.593), residency completed within California (p = 0.493), or residency completed after 2010 (p = 0.589). Of the 371 providers who wrote opioid prescriptions from 2009 through 2018, 120 wrote prescriptions for patients who had already received at least three opioid prescriptions in the same year from the same department., Conclusion: This study could inform policymakers by describing patterns of variation in opioid prescribing over time and between providers. Although we did see significant differences in prescribing patterns from one provider to the next, those were not explained by the factors we examined. Further studies could investigate factors such as provider experience with pain and addiction, bias regarding particular pathologies, and concern around patient satisfaction scores., Competing Interests: Declaration of Competing Interest None of the authors report any conflicts of interest., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Aim: The COVID-19 pandemic has significantly impacted Emergency Medical Services (EMS) operations throughout the country. Some studies described variation in total volume of out-of-hospital cardiac arrests (OHCA) during the pandemic. We aimed to describe the changes in volume and characteristics of OHCA patients and resuscitations in one urban EMS system., Methods: We performed a retrospective cohort analysis of all recorded atraumatic OHCA in Marion County, Indiana, from January 1, 2019 to June 30, 2019 and from January 1, 2020 to June 30, 2020. We described patient, arrest, EMS response, and survival characteristics. We performed paired and unpaired t-tests to evaluate the changes in those characteristics during COVID-19 as compared to the prior year. Data were matched by month to control for seasonal variation., Results: The total number of arrests increased from 884 in 2019 to 1034 in 2020 (p = 0.016). Comparing 2019 to 2020, there was little difference in age [median 62 (IQR 59-73) and 60 (IQR 47-72), p = 0.086], gender (38.5% and 39.8% female, p = 0.7466, witness to arrest (44.3% and 39.6%, p = 0.092), bystander AED use (10.1% and 11.4% p = 0.379), bystander CPR (48.7% and 51.4%, p = 0.242). Patients with a shockable initial rhythm (19.2% and 15.4%, p = 0.044) both decreased in 2020, and response time increased by 18 s [6.0 min (IQR 4.5-7.7) and 6.3 min (IQR 4.7-8.0), p = 0.008]. 47.7% and 54.8% (p = 0.001) of OHCA patients died in the field, 19.7% and 19.3% (p = 0.809) died in the Emergency Department, 21.8% and 18.5% (p = 0.044) died in the hospital, 10.8% and 7.4% (p = 0.012) were discharged from the hospital, and 9.3% and 5.9% (p = 0.005) were discharged with Cerebral Performance Category score ≤ 2., Conclusion: Total OHCA increased during the COVID-19 pandemic when compared with the prior year. Although patient characteristics were similar, initial shockable rhythm, and proportion of patients who died in the hospital decreased during the pandemic. Further investigation will explore etiologies of those findings., Competing Interests: Declaration of Competing Interest None of the authors report any conflicts of interest., (Copyright © 2021 Elsevier Inc. All rights reserved.)

We generated a novel scoring system to improve the test characteristics of D-dimer in patients with suspected PE (pulmonary emboli). Electronic Medical Record data were retrospectively reviewed on Emergency Department (ED) patients 18 years or older for whom a D-dimer and imaging were ordered between June 4, 2012 and March 30, 2016. Symptoms (dyspnea, unilateral leg swelling, hemoptysis), age, vital signs, medical history (cancer, recent surgery, medications, history of deep vein thrombosis or PE, COPD, smoking), laboratory values (quantitative D-dimer, platelets, and mean platelet volume (MPV)), and imaging results (CT, VQ) were collected. Points were designated to factors that were significant in two multiple regression analyses, for PE or positive D-dimer. Points predictive of PE were designated positive values and points predictive of positive D-dimer, irrespective of presence of PE, were designated negative values. The DAGMAR (D-dimer Assay-Guided Moderation of Adjusted Risk) score was developed using age and platelet adjustment and points for factors associated with PE and elevated D-dimer. Of 8486 visits reviewed, 3523 were unique visits with imaging, yielding 2253 (26.5%) positive D-dimers. 3501 CT scans and 156 VQ scans were completed, detecting 198 PE. In our cohort, a DAGMAR Score < 2 equated to overall PE risk < 1.2%. Specificity improved (38% to 59%) without compromising sensitivity (94% to 96%). Use of the DAGMAR Score would have reduced CT scans from 2253 to 1556 and lead to fewer false negative results. By considering factors that affect D-dimer and also PE, we improved specificity without compromising sensitivity., (Copyright © 2018 Elsevier Inc. All rights reserved.)