Differences in cardiac testing resource utilization using two different risk stratification schemes.

OBJECTIVE: Assess whether changing an emergency department (ED) chest pain pathway from utilizing the Thrombolysis in Myocardial Infarction (TIMI) score for risk stratification to an approach utilizing the History, EKG, Age, Risk, Troponin (HEART) score was associated with reductions in healthcare resource utilization. METHODS: A retrospective, quasi-experimental study using difference-in-differences and interrupted time series specifications evaluated all ED patients with a chest pain encounter from 8/2015 to 7/2019 at a large academic medical center. We included patients age ≥ 18 with negative troponin testing discharged from the ED. Our standardized care pathway utilized TIMI for risk stratification until 09/2017 and HEART thereafter. We evaluated patients undergoing hospital-based cardiac diagnostic testing (CDT), length of stay (LOS), and 30-day Major Adverse Cardiovascular Events (MACE) at the intervention site before and after the pathway change and compared these outcomes to a similar control site within the health system for the difference-in-differences specification. RESULTS: During the study period, 6.3% (450 of 7117) of patients in the TIMI cohort and 7.2% (546 of 7623) in the HEART cohort among 400,965 total ED visits underwent CDT. In a multivariable analysis, transition to the HEART pathway was associated with greater odds of receiving CDT (odds ratio 2.88 [95% CI 1.21 to 6.86]), a reduction in LOS of 34 min (95% CI 2.2 to 67.6), and no significant difference in 30-day MACE. CONCLUSION: The transition from TIMI to HEART was associated with mixed consequences for healthcare resource utilization, including increased CDT but reduced length of stay.

ED-based COVID-19 vaccination campaign finds higher vaccination rates for individuals from racial and ethnic minority groups compared with clinic setting.

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.

Effect of resident complement on timeliness of stroke team activation in an academic emergency department.

OBJECTIVES: Investigations of the impact of residents on emergency department (ED) timeliness of care typically focus only on global ED flow metrics. We sought to describe the association between resident complement/supervisory ratios and timeliness of ED care of a specific time-sensitive condition, acute stroke. METHODS: We matched ED stroke patient arrivals at 1 academic stroke center against resident and attending staffing and constructed a Cox proportional hazards model of door-to-activation (DTA) time (ie, ED arrival ["door"] to stroke team activation). We considered multiple predictors, including calculated ratios of residents supervised by each attending physician. RESULTS: Among 462 stroke activation patients in 2014-2015, DTA ranged from 1 to 217 minutes, 72% within 15 minutes. The median number of emergency and off-service residents supervised per attending were 1.7 (interquartile range [IQR], 1.3-2.3) and 0.7 (IQR, 0-1), respectively. A 1-resident increase in off-service residents was associated with a 24% decrease (hazard ratio [HR], 0.76; 95% confidence interval [CI], 0.64-0.90) in the probability of stroke team activation at any given time. An independent 1-resident increase in the number of emergency residents was associated with a 13% increase (HR, 1.13; 95% CI, 1.01-1.25) in timely activation. CONCLUSION: Timeliness of care for acute stroke may be impacted by how academic EDs configure the complement and supervisory structures of residents. Higher supervisory demands imposed by increasing the proportion of rotating off-service residents may be associated with slower stroke recognition and DTA times, but this effect may be offset when more emergency residents are present.

Operational factors associated with emergency department patient satisfaction: Analysis of the Academy of Administrators of Emergency Medicine/Association of Academic Chairs of Emergency Medicine national survey.

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.

Emergency department front-end split-flow experience: 'physician in intake'.

Background: Emergency 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. Methods: We 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'. Results: Among 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%). Conclusions: In this cross section of primarily academic EDs, implementing a physician-driven front-end intake process was feasible and associated with improvement in operational metrics.

Clinical operations of academic versus non-academic emergency departments: a descriptive comparison of two large emergency department operations surveys.

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.

Delayed Recognition of Acute Stroke by Emergency Department Staff Following Failure to Activate Stroke by Emergency Medical Services.

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.

An integrated web application for decision support and automation of EHR workflow: a case study of current challenges to standards-based messaging and scalability from the EMBED trial.

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.

Antibiotic Prescribing Patterns for Sinusitis Within a Direct-to-Consumer Virtual Urgent Care.

Background:Direct-to-consumer virtual visits are increasingly popular across both for-profit and nonprofit healthcare systems.Introduction:Virtual visits offer a convenient affordable way for patients to obtain medical care for simple conditions such as sinusitis and uncomplicated urinary tract infections. However, virtual visits have been associated with increased antibiotic utilization when compared with traditional in-person care.Methods:In this retrospective cohort study, antibiotic utilization for acute sinusitis was compared between patients treated through a direct-to-consumer virtual urgent care versus a matched cohort treated through traditional urgent care.Results:Fifty-seven patients were treated for acute sinusitis within the virtual care cohort, whereas 100 patients were treated in the traditional care arm. Antibiotic utilization for acute sinusitis was lower when care was delivered virtually using live-interactive video (67%) than when using traditional urgent care (92%) (p < 0.001). When care was delivered virtually, age, gender, and care delivery modality (telephone vs. video) were not associated with antibiotic utilization for acute sinusitis.Discussion:Concerns have been raised that care delivered virtually does not meet expected quality standards when compared with traditional care. Antibiotic utilization has been used as an example of this quality gap. In this study, we demonstrate that antibiotic utilization was lower in a virtual care cohort than when care was delivered by emergency medicine physicians based in an academic setting. This suggests that awareness and sensitivity to prescribing guidelines may be more important than care delivery modality as it relates to antibiotic utilization.Conclusions:It is possible to deliver care virtually for acute sinusitis without increasing antibiotic utilization.

Code Help: Can This Unique State Regulatory Intervention Improve Emergency Department Crowding?

INTRODUCTION: Emergency department (ED) crowding adversely affects multiple facets of high-quality care. The Commonwealth of Massachusetts mandates specific, hospital action plans to reduce ED boarding via a mechanism termed "Code Help." Because implementation appears inconsistent even when hospital conditions should have triggered its activation, we hypothesized that compliance with the Code Help policy would be associated with reduction in ED boarding time and total ED length of stay (LOS) for admitted patients, compared to patients seen when the Code Help policy was not followed. METHODS: This was a retrospective analysis of data collected from electronic, patient-care, timestamp events and from a prospective Code Help registry for consecutive adult patients admitted from the ED at a single academic center during a 15-month period. For each patient, we determined whether the concurrent hospital status complied with the Code Help policy or violated it at the time of admission decision. We then compared ED boarding time and overall ED LOS for patients cared for during periods of Code Help policy compliance and during periods of Code Help policy violation, both with reference to patients cared for during normal operations. RESULTS: Of 89,587 adult patients who presented to the ED during the study period, 24,017 (26.8%) were admitted to an acute care or critical care bed. Boarding time ranged from zero to 67 hours 30 minutes (median 4 hours 31 minutes). Total ED LOS for admitted patients ranged from 11 minutes to 85 hours 25 minutes (median nine hours). Patients admitted during periods of Code Help policy violation experienced significantly longer boarding times (median 20 minutes longer) and total ED LOS (median 46 minutes longer), compared to patients admitted under normal operations. However, patients admitted during Code Help policy compliance did not experience a significant increase in either metric, compared to normal operations. CONCLUSION: In this single-center experience, implementation of the Massachusetts Code Help regulation was associated with reduced ED boarding time and ED LOS when the policy was consistently followed, but there were adverse effects on both metrics during violations of the policy.

Effect of a Data-driven Intervention on Opioid Prescribing Intensity Among Emergency Department Providers: A Randomized Controlled Trial.

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.

Mortality Associated With Emergency Department Boarding Exposure: Are There Differences Between Patients Admitted to ICU and Non-ICU Settings?

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.

Door-to-Imaging Time for Acute Stroke Patients Is Adversely Affected by Emergency Department Crowding.

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.