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BACKGROUND Patient satisfaction is a focus for emergency department (ED) and hospital administrators. ED patient satisfaction studies have tended to be single site and focused on patient and clinician factors. Inclusion of satisfaction scores in a large, national operations database provided an opportunity to conduct an investigation that included diverse operational factors. METHODS We performed a retrospective analysis of the 2019 Academy of Administrators in Academic Emergency Medicine/Association of Academic Chairs of Emergency Medicine (AAAEM/AACEM) benchmarking survey to identify associations between operational factors and patient satisfaction. We identified 59 database variables as potential predictors of Press Ganey likelihood-to-recommend and physician overall scores. Using random forest modeling, we identified the top eight predictors in the models and described their associations. RESULTS Forty-three (57.3%) academic departments responding to the AAAEM/AACEM survey reported patient satisfaction scores for 78 EDs. Likelihood to recommend ranged from 30.0 to 93.0 (median = 74.8) and was associated with ED length of stay, boarding, use of hallway spaces, hospital annual admissions, faculty base clinical hours, proportion of patients leaving before treatment complete (LBTC), and provider in triage hours per day. Physician overall score ranged from 53.3 to 93.4 (median = 81.9) and was associated with faculty base clinical hours, x-ray utilization, annual ED arrivals, LBTC, use of hallway spaces, arrivals per attending hour, and CT utilization. CONCLUSIONS ED patient satisfaction was associated with intrinsic and extrinsic factors, some being potentially manageable within the ED but others being relatively fixed or outside the control of ED operations. For likelihood to recommend, patient flow was dominant, with erosion of satisfaction observed with increased boarding and longer LOS. Factors associated with physician overall score were more varied. The use of hallway spaces and base clinical hours greater than 1,500 per year were associated with both lower likelihood-to-recommend and lower physician overall scores.

Background Emergency department visits associated with Coronavirus Disease 2019 (COVID-19) continue to indicate racial and ethnic inequities. We describe the sociodemographic characteristics of individuals receiving COVID-19 vaccination in the emergency department and compare with an outpatient clinic population and emergency department (ED) patients who were eligible but not vaccinated. Methods We conducted a retrospective analysis of electronic health record data at an urban academic ED from May to July 2021. The primary aim was to characterize the ED-vaccinated population, compared with ED patients who were eligible but unvaccinated and the physically adjacent outpatient vaccination clinic population. Results A total of 627 COVID-19 vaccinations were administered in the ED. Overall, 49% of ED patients during that time had already received at least one vaccine dose prior to ED arrival. Hispanic, non-Hispanic Black patients, and patients on non-commercial insurance had higher odds of being vaccinated in the ED as compared with outpatient clinic setting. Among eligible ED patients, men and patients who were uninsured/self-pay were more likely to accept ED vaccination. Conclusions This ED COVID-19 vaccination campaign demonstrated a higher likelihood to vaccinate individuals from racial/ethnic minority groups, those with high social vulnerability, and non-commercial insurance, when compared with a co-located outpatient vaccination clinic.

The growth and promulgation of Advanced Practice Providers (APPs) across the entire spectrum of healthcare delivery has been profound, and APPs are increasingly common members of emergency department (ED) care teams. Emergency APP workforce growth is outpacing that of emergency physicians with little to suggest that this trend will subside. The evolution of the deployment of APPs in emergency care has been dramatic; initially, emergency APPs were deployed to lower acuity patients or environments-minor injury and illness and in conjunction with an emergency physician-hence the now antiquated description of APPs as "physician extenders."

Background Academic and non-academic emergency departments (EDs) are regularly compared in clinical operations benchmarking despite suggestion that the two groups may differ in their clinical operations characteristics. and outcomes. We sought to describe and compare clinical operations characteristics of academic versus non-academic EDs. Methods We performed a descriptive, comparative analysis of academic and non-academic adult and general EDs with 40,000+ annual encounters, using the Academy of Academic Administrators of Emergency Medicine (AAAEM)/Association of Academic Chairs of Emergency Medicine (AACEM) and Emergency Department Benchmarking Alliance (EDBA) survey results. We defined academic EDs as primary teaching sites for emergency medicine (EM) residencies and non-academic EDs as sites with minimal resident involvement. We constructed the academic and non-academic cohorts from the AAAEM/AACEM and EDBA surveys, respectively, and analyzed metrics common to both surveys. Results Eighty and 454 EDs met inclusion criteria for academic and non-academic EDs, respectively. Academic EDs had more median annual patient encounters (73,001 vs 54,393), lower median proportion of pediatric patients (6.3% vs 14.5%), higher median proportion of EMS patients (27% vs 19%), and were more commonly designated as Level I or II Trauma Centers (94% vs 24%). Median patient arrival-to-provider times did not differ (26 vs 25 min). Median length-of-stay was longer (277 vs 190 min) for academic EDs, and left-before-treatment-complete was higher (5.7% vs 2.9%). MRI utilization was higher for academic EDs (2.2% patients with at least one MRI vs 1.0 MRIs performed per 100 patients). Patients-per-hour of provider coverage was lower for academic EDs with and without consideration for advanced practice providers and residents. Conclusions Demographic and operational performance measures differ between academic and non-academic EDs, suggesting that the two groups may be inappropriate operational performance comparators. Causes for the differences remain unclear but the differences appear not to be attributed solely to the academic mission.

Computerized clinical decision support (CDS) faces challenges to interoperability and scalability. Centralized, web-based solutions offer a mechanism to share the cost of CDS development, maintenance, and implementation across practices. Data standards have emerged to facilitate interoperability and rapid integration of such third-party CDS. This case report describes the challenges to implementation and scalability of an integrated, web-based CDS intervention for EMergency department-initiated BuprenorphinE for opioid use Disorder which will soon be evaluated in a trial across 20 sites in five healthcare systems. Due to limitations of current standards, security concerns, and the need for resource-intensive local customization, barriers persist related to centralized CDS at this scale. These challenges demonstrate the need and importance for future standards to support two-way messaging (read and write) between electronic health records and web applications, thus allowing for more robust sharing across health systems and decreasing redundant, resource-intensive CDS development at individual sites.

Background: Direct-to-consumer virtual visits are increasingly popular across both for-profit and nonprofit healthcare systems. Introduction: Virtual visits offer a convenient affordable w...

Author(s): Tennyson, Joseph C.; Michael, Sean S.; Youngren, Marguerite; Reznek, Martin | Abstract: Introduction: Early recognition and pre-notification by emergency medical services (EMS) improves the timeliness of emergency department (ED) stroke care; however, little is known regarding the effects on care should EMS providers fail to pre-notify. We sought to determine if potential stroke patients transported by EMS, but for whom EMS did not provide pre-notification, suffer delays in ED door-to-stroke-team activation (DTA) as compared to the other available cohort of patients for whom the ED is not pre-notified–those arriving by private vehicle.Methods: We queried our prospective stroke registry to identify consecutive stroke team activation patients over 12 months and retrospectively reviewed the electronic health record for each patient to validate registry data and abstract other clinical and operational data. We compared patients arriving by private vehicle to those arriving by EMS without pre-notification, and we employed a multivariable, penalized regression model to assess the probability of meeting the national DTA goal of ≤15 minutes, controlling for a variety of clinical factors.Results: Our inclusion criteria were met by 200 patients. Overall performance of the regression model was excellent (area under the curve 0.929). Arrival via EMS without pre-notification, compared to arrival by private vehicle, was associated with an adjusted risk ratio of 0.55 (95% confidence interval, 0.27-0.96) for achieving DTA ≤ 15 minutes. Conclusion: Our single-center data demonstrate that potential stroke patients arriving via EMS without pre-notification are less likely to meet the national DTA goal than patients arriving via other means. These data suggest a negative, unintended consequence of otherwise highly successful EMS efforts to improve stroke care, the root of which may be ED staff over-reliance on EMS for stroke recognition.

Introduction: The National Institutes of Health Stroke Scale (NIHSS) is widely used for rapid assessment of neurologic deficits in acute stroke. Multiple components of the scale require intact language function, which may be difficult for English-speaking providers to assess in non-English speaking patients (NESP). We sought to characterize patterns of NIHSS scoring in English-speaking patients (ESP) and NESP. Methods: This was a retrospective study of consecutive stroke alert cases who presented to the emergency department at our primarily English-speaking comprehensive stroke center. Baseline characteristics and clinical data including NIHSS components were compared between ESP and NESP. Chi-squared/Fisher’s exact statistics were used to compare frequencies and T-tests were used to compare means. Relative risks were calculated for language effects on NIHSS components, controlling for gender, age, race, and stroke diagnosis. Results: A total of 1166 patients were included, of which 87.5% were ESP and 12.5% were NESP. There were no significant differences between groups in total NIHSS scores or in frequencies of stroke diagnosis, tissue plasminogen activator treatment, or endovascular treatment. For individual NIHSS components, NESP were more likely than ESP to score for level of consciousness questions (34.9% vs 22.3%, adjusted RR 1.91, CL 1.39-2.62, p=0.0005), level of consciousness commands (21.9% vs 10.1%, adjusted RR 3.62, CL 2.42-5.43, p Conclusions: Despite similarities in total NIHSS scoring between NESP and ESP, scoring of individual components heavily dependent on language function and comprehension differed between groups. NESP were more likely to be assessed as aphasic, unable to answer questions, and unable to follow commands. Disparities in NIHSS scoring trends raise questions for further investigation into possible underlying pathophysiologic mechanisms, potential provider biases from language barriers that may influence clinical assessment, and the role of more inclusive screening tools and interventions to help mitigate these gaps.

Background and Purpose: Women are more likely to experience delays in evaluation and treatment for acute stroke. As national guidelines increasingly emphasize the importance of rapid stroke intervention, it is important to further investigate this gender disparity. We sought to evaluate whether door-to-stroke activation time varied by patient gender among patients for whom stroke team activation occurred in the emergency department (ED). Methods: This was a retrospective analysis of a prospectively collected registry of all patients for whom the stroke team was activated in the ED of an urban, academic, regional stroke center over 1 year. Our primary outcome was door to stroke activation time (DTA), with the primary predictor of interest being patient gender. We assessed for differences in DTA using multivariable Cox proportional hazards and logistic regression models. Results: There were 211 patient encounters included in the study, 117 women and 94 males. Median DTA was 8 minutes longer for women, and women were less likely to have DTA ≤ 15 minutes (odds ratio 0.26 [95% confidence interval 0.12 to 0.58]). Conclusion: A gender disparity existed in door to activation time for women presenting with suspected acute stroke, even when controlling for a variety of factors. These results provide evidence that gender may impact initial management of stroke patients.

Introduction: Serum troponin is a ubiquitous biomarker used to diagnose acute myocardial infarction (AMI). The positive predictive value (PPV) of high-sensitivity troponin for Type 1 Myocardial Infarction is approximately 15% in the United States, compared with 55% in Europe, a difference that may be explained by differences in patient selection for testing. Our objective was to examine test characteristics for contemporary troponin assays based on chief complaint in the Emergency Department (ED). Methods: In a retrospective cohort analysis, we examined all 30,833 encounters in which a troponin test was performed in any of the 14 emergency departments within a large integrated health system between 10/1/18 and 10/1/19. All hospitals used a contemporary cardiac troponin-I (cTnI) assay. We excluded patients with ST-segment elevation myocardial infarction (STEMI) since this diagnosis is made by electrocardiogram. We grouped patients by chief complaint (CC) and further stratified by pre-specified cTnI thresholds. Within each cTnI/CC category, we calculated the proportion of patients subsequently classified with a principal ICD-10 diagnosis of non-STEMI (NSTEMI). Results: For all patients selected for cTnI testing, 1.7% were diagnosed with NSTEMI. Overall, the PPV of cTnI for NSTEMI was 11%. This PPV for NSTEMI was highest among patients with chest pain (33%). Excluding patients with chest pain, the PPV for NSTEMI was 3.9%. For nearly all chief complaints, the PPV for NSTEMI increased with higher cTnI thresholds. Conclusion: In a large integrated health system, fewer than one in fifty patients undergoing cTnI testing in the ED were ultimately diagnosed with NSTEMI. The PPV of cTnI for NSTEMI was significantly higher among patients presenting with chest pain compared to other chief complaints. These data highlight the importance of selecting patients for testing and interpreting abnormalities in the context of presenting symptoms.

BackgroundEmergency department (ED) crowding is a critical problem in the delivery of acute unscheduled care. Many causes are external to the ED, but antiquated operational traditions like triage also contribute. A physician intake model has been shown to be beneficial in a single-centre study, but whether this solution is generalisable is not clear. We aimed to characterise the current state of front-end intake models in a national sample of EDs and quantify their effects on throughput measures.MethodsWe performed a descriptive mixed-method analysis of ED process changes implemented by a cross section of self-selecting institutions who reported 2 years of demographic/operational data and structured process descriptions of any ‘new front-end processes to replace traditional nurse-based triage’.ResultsAmong 25 participating institutions, 19 (76%) provided data. While geographically diverse, most were urban, academic adult level 1 trauma centres. Thirteen (68%) reported implementing a new intake process. All were run by attending emergency physicians, and six (46%) also included advanced practice providers. Daily operating hours ranged from 8 to 16 (median 12, IQR 10.25–15.85), and the majority performed labs, imaging and medication administration and directly discharged patients. Considering each site’s before-and-after data as matched pairs, physician-driven intake was associated with mean decreases in arrival-to-provider time of 25 min (95% CI 13 to 37), ED length of stay 36 min (95% CI 12 to 59), and left before being seen rate 1.2% (95% CI 0.6% to 1.8%).ConclusionsIn this cross section of primarily academic EDs, implementing a physician-driven front-end intake process was feasible and associated with improvement in operational metrics.

Background: Direct-to-consumer (DTC) virtual urgent care (VUC) visits are increasingly popular across both for-profit and nonprofit healthcare systems; however, few peer-reviewed studies have described the ecology of a VUC program. Design/Setting: In this retrospective cohort study, patients (N = 2,216) received care through a VUC platform offered by a regional health system over an approximately 2-year period. Results: Seventy-one percent of patients were identified as females. The age of the patients ranged from 18 to 85 years (median 39 years, interquartile range [IQR] 32–49 years). Eighty-four percent (n = 1,906) of patients had a registered primary care provider (PCP), while 177 (8%) chose to self-pay for the VUC service. Seventy-six percent of visits occurred between Monday and Friday, and 71% (n = 1,573) visits occurred between 8 am and 6 pm. The median provider response time was 24 minutes. Visits were conducted by videoconference 84% of the time; providers and patients spent a median of 7.4 minutes (IQR 4.3, 9.9 min) together in the video room. Seventy-seven percent of visits generated a prescription, of which 70% were on antibiotics. Conclusions: Most virtual visits were initiated by existing health system patients with a primary care physician, and the majority of patients sought care during usual business hours. Most visits led to a prescription, most commonly an antibiotic. These data can help inform operational leaders who are considering how best to structure, staff, and develop key performance indicators for their own VUC programs. Additionally, these data challenge the notion that acute, episodic DTC encounters occur after-hours and are utilized by uninsured patients who lack a relationship with a primary care physician.

Background Emergency Department (ED) boarding threatens patient safety. It is unclear whether boarding differentially affects patients admitted to intensive care units (ICUs) versus non-ICU settings. Research design and subjects We performed a 2-hospital, 18-month, cross-sectional, observational, descriptive study of adult patients admitted from the ED. We used Kaplan-Meier estimation and Cox Proportional Hazards regression to describe differences in boarding time among patients who died during hospitalization versus those who survived, controlling for covariates that could affect mortality risk or boarding exposure, and separately evaluating patients admitted to ICUs versus non-ICU settings. Measures We extracted age, race, sex, time variables, admission unit, hospital disposition, and Elixhauser comorbidity measures and calculated boarding time for each admitted patient. Results Among 39,781 admissions from the EDs (21.3% to ICUs), non-ICU patients who died in-hospital had a 1.2-fold risk (95% confidence interval, 1.03-1.36; P=0.016) of having experienced longer boarding times than survivors, accounting for covariates. We did not observe a difference among patients admitted to ICUs. Conclusions Among non-ICU patients, those who died during hospitalization were more likely to have had incrementally longer boarding exposure than those who survived. This difference was not observed for ICU patients. Boarding risk mitigation strategies focused on ICU patients may have accounted for this difference, but we caution against interpreting that boarding can be safe. Segmentation by patients admitted to ICU versus non-ICU settings in boarding research may be valuable in ensuring that the safety of both groups is considered in hospital flow and boarding care improvements.

Objective Little is known about accuracy of provider self-perception of opioid prescribing. We hypothesized that an intervention asking emergency department (ED) providers to self-identify their opioid prescribing practices compared to group norms-and subsequently providing them with their actual prescribing data-would alter future prescribing compared to controls. Methods This was a prospective, multicenter randomized trial in which all attending physicians, residents, and advanced practice providers at four EDs were randomly assigned either to no intervention or to a brief data-driven intervention during which providers were: 1) asked to self-identify and explicitly report to research staff their perceived opioid prescribing in comparison to their peers and 2) then given their actual data with peer group norms for comparison. Our primary outcome was the change in each provider's proportion of patients discharged with an opioid prescription at 6 and 12 months. Secondary outcomes were opioid prescriptions per hundred total prescriptions and normalized morphine milligram equivalents prescribed. Our primary comparison stratified intervention providers by those who underestimated their prescribing and those who did not underestimate their prescribing, both compared to controls. Results Among 109 total participants, 51 were randomized to the intervention, 65% of whom underestimated their opioid prescribing. Intervention participants who underestimated their baseline prescribing had larger-magnitude decreases than controls (Hodges-Lehmann difference = -2.1 prescriptions per hundred patients at 6 months [95% confidence interval {CI} = -3.9 to -0.5] and -2.2 per hundred at 12 months [95% CI = -4.8 to -0.01]). Intervention participants who did not underestimate their prescribing had similar changes to controls. Conclusions Self-perception of prescribing was frequently inaccurate. Providing clinicians with their actual opioid prescribing data after querying their self-perception reduced future prescribing among providers who underestimated their baseline prescribing. Our findings suggest that guideline and policy interventions should directly address the potential barrier of inaccurate provider self-awareness.

Elixhauser and APACHE risk-adjustment methods are widely used in studies of administrative data but have not been directly compared in the same dataset. This was an 18-month cross-sectional, observational, registry-based study of all adult patients admitted from the emergency department to an inpatient critical care setting at one academic referral center and one community hospital. After extracting demographics, comorbidities from the preceding year, and calculating APACHE-IV scores at admission, we developed three competing logistic regression models to predict in-hospital mortality using APACHE-IV, Elixhauser comorbidities, and a combined approach. We identified 8,480 critical care admissions during the study period (84% at the academic hospital), with 12.6% overall mortality. Areas under the curve were 0.808 [95% confidence interval (CI): 0.777, 0.831] for APACHE-IV, 0.736 (95% CI: 0.715, 0.761) for Elixhauser, and 0.826 (95% CI: 0.803, 0.852) for the combined model. APACHE-IV scoring, with or without the addition of Elixhauser comorbidity measures, outperformed the Elixhauser method alone in predicting in-hospital mortality among patients admitted to a critical care unit via the emergency department. Observational studies in this population should consider employing APACHE-based risk adjustment for short-term mortality prediction, in preference to comorbidity-based risk-adjustment alone.

Background and Purpose— National guidelines call for door-to-imaging time (DIT) within 25 minutes for suspected acute stroke patients. Studies examining factors that affect DIT have focused primarily on stroke-specific care processes and patient-specific factors. We hypothesized that emergency department (ED) crowding is associated with longer DIT. Methods— We conducted a retrospective investigation of 1 year of consecutive patients in our prospective Code Stroke registry, which included all ED stroke team activations. The registry and electronic health records were abstracted for 27 potential predictors of DIT, including patient, stroke care process, and ED operational factors. We fit a multivariate logistic regression model and calculated odds ratios and 95% confidence intervals. Second, we constructed a random forest recursive partitioning model to cross-validate our findings and explore the proportional importance of each category of predictor. Our primary outcome was the binary variable of DIT within the 25-minute goal. Results— A total of 463 patients met inclusion criteria. In the regression model, ED occupancy rate emerged as a predictor of DIT, with odds ratio of 0.83 (95% confidence interval, 0.75–0.91) of DIT within 25 minutes per 10% absolute increase in ED occupancy rate. The secondary analysis estimated that ED operational factors accounted for nearly 14% of the algorithm’s prediction of DIT. Conclusions— ED crowding is associated with reduced odds of meeting DIT goals for acute stroke. In addition to improving stroke-specific processes of care, efforts to reduce ED overcrowding should be considered central to optimizing the timeliness of acute stroke care.