Search

Introduction: A solution for emergency department (ED) congestion remains elusive. As reliance on imaging grows, computed tomography (CT) turnaround time has been identified as a major bottleneck. In this study we sought to identify factors associated with significantly delayed CT in the ED.Methods: We performed a retrospective analysis of all CT imaging completed at an urban, tertiary care ED from May 1–July 31, 2021. During that period, 5,685 CTs were performed on 4,344 patients, with a median time from CT order to completion of 108 minutes (Quartile 1 [Q1]: 57 minutes, Quartile 3 [Q3]: 182 minutes, interquartile range [IQR]: 125 minutes). Outliers were defined as studies that took longer than 369 minutes to complete (Q3 + 1.5 × IQR). We systematically reviewed outlier charts to determine factors associated with delay and identified five factors: behaviorally non-compliant or medically unstable patients; intravenous (IV) line issues; contrast allergies; glomerular filtration rate (GFR) concerns; and delays related to imaging protocol (eg, need for IV contrast, request for oral and/or rectal contrast). We calculated confidence intervals (CI) using the modified Wald method. Inter-rater reliability was assessed with a kappa analysis.Results: We identified a total of 182 outliers (4.2% of total patients). Fifteen (8.2%) cases were excluded for CT time-stamp inconsistencies. Of the 167 outliers analyzed, 38 delays (22.8%, 95% confidence interval [CI] 17.0–29.7) were due to behaviorally non-compliant or medically unstable patients; 30 (18.0%, 95% CI 12.8–24.5) were due to IV issues; 24 (14.4%, 95% CI 9.8–20.6) were due to contrast allergies; 21 (12.6%, 95% CI 8.3–18.5) were due to GFR concerns; and 20 (12.0%, 95% CI 7.8–17.9) were related to imaging study protocols. The cause of the delay was unknown in 55 cases (32.9%, 95%CI 26.3–40.4).Conclusion: Our review identified both modifiable and non-modifiable factors associated with significantly delayed CT in the ED. Patient factors such as behavior, allergies, and medical acuity cannot be controlled. However, institutional policies regarding difficult IV access, contrast administration in low GFR settings, and study protocols may be modified, capturing up to 42.6% of outliers.

Objectives: To assess whether time-to-disposition is significantly different when a patient is seen by a provider during the early half or late half of a shift.Background: Time-to-disposition is an important metric for emergency department throughput. We hypothesized that providers view the shift end as a key timepoint and attempt to leave as few dispositions as possible to the oncoming team, thereby making quicker decisions later in the shift. This study evaluates disposition distribution relative to when patients are assigned a provider during the course of a shift.Methods: 50,802 cases were analyzed over the one-year study interval. 31,869 patients were seen in the early half of a shift (hours 1-4) and 18,933 were seen in the later half (hours 5+). We ran a linear mixed model that adjusted for age, gender, emergency severity index score, time of day, weekend arrivals, quarter of arrival and shift type.Results: Median time-to-disposition for the early group was 3.25 hours (IQR 1.90-5.04), and 2.62 hours (IQR 1.51-4.31) for the late group. From our mixed model, we conclude that in the later parts of the shift, providers take on average 15.1% less time to make a disposition decision than in the earlier parts of the shift.Conclusion: Patients seen during the latter half of a shift were more likely to have a shorter time-to-disposition than similar patients seen in the first half of a shift. This may be influenced by many factors, such as providers spending the early hours of a shift seeing new patients which generate new tasks and delay dispositions, and viewing the end of shift as a landmark with a goal to maximize dispositions prior to sign-out.

Objectives: In this study, we examine APP productivity to determine if a similar pattern applies to that of residents and attendings, with the hypothesis that hourly productivity decreases after the first few hours of the shift.Background: APP productivity follows a similar pattern to previously described behaviors in both residents and attendings. This further confirms the results of prior studies that productivity is a dynamic process that needs to be considered when adjusting staffing models. Additionally, this pattern by APPs at a community hospital provides additional validation of this model outside of academic institutions or training environments.Methods: This is a retrospective cohort study from 7/1/21 through 6/30/21 at a single suburban community hospital in the northeast. APPs work ten hour shifts from 10AM to 8PM, nearly every day. APPs also provide coverage for approximately 5 shifts per month from 3PM to 11PM. Timestamps of initial patient contact are automatically logged by the electronic health record, and then analyzed to determine in which hour of the shift this occurred. A mixed linear model was performed with the hour as a categorical variable, and day of the week, month and year as covariates. Data was grouped by individual shifts.Results: A total of 345 10-hour shifts were worked by five APPs over the one year studied. There were 64 additional afternoon shifts which were excluded due to the shorter length and lower frequency. Two APPs worked the vast majority of the shifts, and the other three provided per-diem coverage. A mean of 13.3 patients (SD 2.7) were seen per shift. In the first hour, APPs saw an average of 2.67 patients (95% CI 2.59-2.76). Each hour demonstrated a statistically significant decrease relative to the first hour (p< 0.001), with the highest magnitude over the second (-0.58 (95% CI -0.69 — -0.47)) and third (-0.98 (95% CI -1.09 — -0.86)) hours. This downward trend continued throughout the rest of the shift; however, the magnitude of this difference after the sixth hour was not significant. There was no effect by day of week, month or year.Conclusion: APP productivity follows a similar pattern to previously described behaviors in both residents and attendings. This further confirms the results of prior studies that productivity is a dynamic process that needs to be considered when adjusting staffing models. Additionally, this pattern by APPs at a community hospital provides additional validation of this model outside of academic institutions or training environments.

Objectives: The purpose of this study is to determine Emergency Medicine (EM) resident productivity (as measured by patients per hour) over the course of the COVID-19 pandemic compared to the prior training environment.Background: The coronavirus disease 2019 (COVID-19) pandemic disrupted medical education throughout the United States. As a result, many EM residents began residency with atypical clinical experiences. In addition, Emergency Department (ED) patient volumes decreased during the early months of the pandemic.Methods: This is a retrospective observational cohort study conducted at an urban, academic medical center with an established EM residency program. Data was collected from electronic medical records between July 1, 2017 and October 31, 2021. EM residents completing full, consecutive years of residency were included in the sample. Classes prior to 2020 were defined as a control group. Due to the structure of the residency, only shifts at the academic medical center during first and second year of residency (PGY1 and PGY2) were included. Productivity was defined as total primary patient encounters divided by aggregate scheduled shift hours. To allow comparison of the most recent data, analysis was performed on the first four months (July-October) of each academic year. The data was analyzed using descriptive statistics, including standard deviation and t-tests.Results: A total of 63 residents were included in this analysis of the first four months of each training year from 2017-2021. Prior to COVID-19, PGY1 residents evaluated 0.75±0.23 patients per hour and PGY2 residents evaluated 1.46±0.11 patients per hour (p

Objectives: To validate and expand upon prior data suggesting that visits shared with a midlevel or resident influence EP behavior as measured by resource use and propensity to admit a patient.Background: Variability exists in Emergency Physicians’ (EP) resource utilization as measured by ordering practices, propensity to admit patients, and whether a visit is shared with a resident or midlevel provider (nurse practitioner or physician assistant).Methods: This is a retrospective study of routinely gathered operational data from two community, suburban hospitals within an academic emergency network. We analyzed 34 EPs with 141,433 patient visits from July 1, 2016 to June 30, 2019. We collected individual EP data on advanced imaging (CT, US, MRI), admission rates, and whether a visit was shared with a midlevel or resident for each patient encounter. To investigate whether there might be distinct groups of practice patterns relating these resources, we used a Gaussian Mixture Model (GMM), a classification method used to determine the likelihood of distinct subgroups within a larger population. The total number of groups and covariance structure were determined by Bayesian Information Criteria.Results: Our GMM revealed three distinct groups of physicians based on their ordering practices. The largest group is characterized by a homogenous pattern of neither high or low resource utilization (n=19, 58% female, median years’ experience: 9 [IQR 2-16]; rates of Advanced Imaging: 44%, Admission: 21%, Midlevel/Resident staffing 35% with a modest group of low-resource users (n=10, 0% female, median years’ experience: 7 [IQR 5-11]; rates of Advanced Imaging: 31%, Admission: 17%, Midlevel/Resident staffing 32%), and far fewer members of a high-resource use group (n=5, 20% female, median years’ experience: 15 [IQR 5-16]; rates of Advanced Imaging: 49%, Admission: 22%, Midlevel/Resident staffing 35%) [Figure 1]. This variation suggests that use of advanced imaging and propensity to admit may be influenced by whether a patient visit is shared with a midlevel or resident provider.Conclusion: At two community EDs, three distinct subgroups of EP ordering practices exist based on advanced imaging use, propensity to admit a patient, and whether a visit was shared with a midlevel or resident. This data validates prior work showing that resource utilization and admission rates are related, while demonstrating that more nuanced patterns of EP ordering practices exist based on whether a visit is shared with a midlevel or resident provider. Further investigation is needed to understand the impact of EP characteristics and behavior on throughput and quality of care.

Objectives: To evaluate the cost savings of an acetaminophen route pathway in patients presenting to the emergency department.Background: The use of intravenous acetaminophen (IVA) has been increasing since it was approved by the Food and Drug Administration in 2010. However, the cost of IVA is orders of magnitude more than the oral version with significant cost variation based on hospital formulary. Despite the cost difference, multiple studies have shown that the IV version is not more effective than enteral forms. By implementing an Acetaminophen Route Pathway (ARP), we hypothesize a reduction in unnecessary use of IVA and significant cost savings.Methods: A prospective, before-after controlled study was conducted. ED ARP was designed by expert/consensus opinion and rolled out with a discussion at faculty and resident staff meetings followed by reminder emails. The electronic medical record logged every instance of IVA administration 12 months before and after implementation of an ED ARP (with a 90 day washout period) along with total ED volumes. The absolute number of doses as well as per patient utilization of IVA were calculated. Fisher’s exact test was used to assess for significance.Results: During the pre ARP phase (03/01/18-02/28/19), a total of 54,533 presented to the ED with 2,703 doses of IVA given (4.96%). In the post ARP phase (06/01/19-05/31/20), a total of 48,278 presented to the ED with 582 doses of IVA given (1.21%). At $689.29 per dose, this corresponds to a cost of $1,863,151 ($34.16 per ED patient registered) in the before group compared with $401,166.80 ($8.31 per ED patient registered) in the after group. This corresponds to more than $1.2 million dollar in savings, when adjusted for the lower volume post ARP. Fisher’s exact test was significant at p

Introduction: Nearly 14% of US adults currently smoke cigarettes. Cigarette smoking causes more than 480,000 deaths each year in the United States. Emergency department (ED) patients are frequently asked for their use of tobacco. Manual selection of pre-formed discharge instructions is the norm for most ED. Providing tobacco cessation discharge instructions to ED patients presents another avenue to combat the tobacco use epidemic we face. The objective of the study is to evaluate the effectiveness of an automated discharge instruction system in increasing the frequency of discharging current tobacco users with instructions for tobacco cessation.Methods: The study was done at an urban academic tertiary care center. A before and after study was used to test the hypothesis that use of an automated discharged instruction system would increase the frequency that patients who use tobacco were discharged with tobacco cessation instructions. Patients that were admitted, left against medical advice, eloped or left without being seen were excluded. The before phase was from 09/21/14-10/21/14 and the after phase was from the same dates one year later, 09/21/15-10/21/15. This was done to account for confounding by time of year, ED volume and other factors. A Fisher’s Exact Test was calculated to compare these two groups.Results: Tobacco cessation DC instructions were received 2/486 (0.4%) of tobacco users in the pre-implementation period compared to 357/371 (96%) in the post-implementation period (p < 0.05).Conclusions: The automated discharge instructions system increases the proportion of tobacco users who receive cessation instructions. Given the public health ramifications of tobacco use, this could prove to be a significant piece in decreasing tobacco use in patients who go to the emergency department.

Introduction: Hallway beds in the emergency department (ED) produce lower patient satisfaction and inferior care. We sought to determine whether socioeconomic factors influence which visits are assigned to hallway beds, independent of clinical characteristics at triage.Methods: We studied 332,919 visits, across 189,326 patients, to two academic EDs from 2013-2016. We estimated a logistic model of hallway bed assignment, conditioning on payor, demographics, triage acuity, chief complaint, patient visit frequency, and ED volume. Because payor is not generally known at the time of triage, we interpreted it as a proxy for other observable characteristics that may influence bed assignment. We estimated a Cox proportional hazards model of hallway bed assignment on length of stay.Results: Median patient age was 53. 54.0% of visits were by women. 42.1% of visits were paid primarily by private payors, 37.1% by Medicare, and 20.7% by Medicaid. A total of 16.2% of visits were assigned to hallway beds. Hallway bed assignment was more likely for frequent ED visitors, for lower acuity presentations, and for psychiatric, substance use, and musculoskeletal chief complaints, which were more common among visits paid primarily by Medicaid. In a logistic model controlling for these factors, as well as for other patient demographics and for the volume of recent ED arrivals, Medicaid status was nevertheless associated with 22% greater odds of assignment to a hallway bed (odds ratio 1.22, [95% confidence interval, CI, 1.18-1.26]), compared to private insurance. Visits assigned to hallway beds had longer lengths of stay than roomed visits of comparable acuity (hazard ratio for departure 0.91 [95% CI, 0.90-0.92]).Conclusion: We find evidence of social determinants of hallway bed use, likely involving epidemiologic, clinical, and operational factors. Even after accounting for different distributions of chief complaints and for more frequent ED use by the Medicaid population, as well as for other visit characteristics known at the time of triage, visits paid primarily by Medicaid retain a disproportionate association with hallway bed assignment. Further research is needed to eliminate potential bias in the use of hallway beds.

Many patients require inter-hospital transfer (IHT) to tertiary Emergency Departments (EDs) to access specialty services. The purpose of this study is to determine operational outcomes for patients undergoing IHT to a tertiary academic ED, with an emphasis on timing and specialty consult utilization. This study was a retrospective observational cohort study at a tertiary academic hospital from 10/1/21–9/30/22. Key operational metrics, including specialty consultations, were queried from the ED Information System (EDIS). Data were analyzed for temporal variation in operational metrics and consulting patterns between transferred and non-transferred patients, stratified by time of day and week. During the study period there were 50,589 ED patient encounters, of which 3196 (6.3 %) were identified as IHTs. Transferred patients made up a larger proportion of patient arrivals in off-hours compared to daytime hours (p < 0.001). Transferred patients were more likely to be admitted to the hospital (76 % vs 35 %, p < 0.001), go directly to a procedure (6 % vs 2 %, p < 0.001), or receive a specialty consult (90 % vs 42 %, p < 0.001), regardless of the day of week or time of day. Relative risk of consults amongst transferred patients varied by service, though was particularly increased amongst surgical sub-specialties. Transferred patients represented a larger proportion of ED volume during evening and overnight hours, received more consults, and had higher likelihood of admission. Consults for transfers were disproportionately surgical subspecialties, though few patients went directly to a procedure. These findings may have operational implications in optimizing availability of specialty services across regionalized health systems. [ABSTRACT FROM AUTHOR]

Multiple cancers, including colorectal cancer (CRC), are more frequent and often more aggressive in individuals with obesity. Here, we showed that macrophages accumulated within tumors of patients with obesity and CRC and in obese CRC mice and that they promoted accelerated tumor growth. These changes were initiated by oleic acid accumulation and subsequent tumor cell–derived acid production and were driven by macrophage signaling through the acid-sensing receptor GPR65. We found a similar role for GPR65 in hepatocellular carcinoma (HCC) in obese mice. Tumors in patients with obesity and CRC or HCC also exhibited increased GPR65 expression, suggesting that the mechanism revealed here may contribute to tumor growth in a range of obesity-associated cancers and represent a potential therapeutic target. Editor's summary: Obesity is a risk factor for the development of several types of cancer, but how obesity contributes to tumorigenesis remains incompletely understood. Using a mouse model of colon cancer, Bagchi et al. found that tumor-associated macrophages (TAMs) accumulate and drive tumor growth in obese mice. Obesity-associated accumulation of oleic acid enhanced tumor acidity and suppressed TAM inflammatory responses. During obesity, TAMs up-regulated the acid-sensing receptor GPR65, which promoted growth of both colon and liver tumors. Together, these findings identify tumor acidity and GPR65-mediated TAM adaptations as drivers of tumor growth in obesity-associated cancers. —Claire Olingy [ABSTRACT FROM AUTHOR]

Introduction: Resident productivity is an important educational and operational measure in emergency medicine (EM). The ability to continue effectively seeing new patients throughout a shift is fundamental to an emergency physician’s development, and residents are integral to the workforce of many academic emergency departments (ED). Our previous work has demonstrated that residents make gains in productivity over the course of intern year; however, it is unclear whether this is from experience as a physician in general on all rotations, or specific to experience in the ED. Methods: This was a retrospective cohort study, conducted in an urban academic hospital ED, with a three-year EM training program in which first-year residents see new patients ad libitum. We evaluated resident shifts for the total number of new patients seen. We constructed a generalized estimating equation to predict productivity, defined as the number of new patients seen per shift, as a function of the week of the academic year, the number of weeks spent in the ED, and their interaction. Off-service residents’ productivity in the ED was analyzed in a secondary analysis. Results: We evaluated 7,779 EM intern shifts from 7/1/2010 to 7/1/2016. Interns started at 7.16 (95% confidence interval [CI] [6.87 – 7.45]) patients per nine-hour shift, with an increase of 0.20 (95% CI [0.17 – 0.24]) patients per shift for each week in the ED, over 22 weeks, leading to 11.5 (95% CI [10.6 – 12.7]) patients per shift at the end of their training in the ED. The effects of the week of the academic year and its interaction with weeks in the ED were not significant. We evaluated 2,328 off-service intern shifts, in which off-service residents saw 5.43 (95% CI [5.02 – 5.84]) patients per nine-hour shift initially, with 0.46 additional patients per week in the ED (95% CI [0.25 – 0.68]). The weeks of the academic year were not significant. Conclusion: Intern productivity in EM correlates with time spent training in the ED, and not with experience on other rotations. Accordingly, an EM intern’s productivity should be evaluated relative to their aggregate time in the ED, rather than the time in the academic year.

Background: Syncope has myriad etiologies, ranging from benign to immediately life threatening. This frequently leads to over testing. Chest x-rays are among these commonly performed tests despite their uncertain diagnostic yield. Objectives: To quantify the distribution of normal and abnormal chest x-rays in patients presenting with a chief complaint of syncope, stratified by those who did or did not have an adverse event at thirty days. Methods: Prospective cohort of consecutive patients presenting to an urban tertiary care academic medical center with a chief complaint of syncope from 2003-2006.  The frequency and findings for each CXR were reviewed, as well as ED and hospital discharge diagnoses as well as thirty-day outcome. Results: There were 575 total subjects, 39.7% were male, and the mean age was 57.2 (SD 24.6).  Of the 575 total subjects, 403 (70.1%) had chest x-rays performed, and 116 (20.2%) had an adverse event after their syncope.  Of the 116 people who had an adverse event, 15 (12.9%) had a positive CXR, 81 (69.8%) had a normal CXR, and 20 (17.2%) did not have a CXR as part of the initial evaluation.  Among the 459 people who did not have an adverse event 3 (0.7%) had a positive CXR, 304 (66.2%) had a normal CXR, and 152 (33.1%) did not have a CXR performed. Conclusions:  Among patient who had an adverse event after their syncope, the majority of patients had a normal CXR.  More data is needed to validate this conclusion.