Fewer emergency department alarms is associated with reduced use of medications for acute agitation.

BACKGROUND AND OBJECTIVES: Patient monitoring systems provide critical information but often produce loud, frequent alarms that worsen patient agitation and stress. This may increase the use of physical and chemical restraints with implications for patient morbidity and autonomy. This study analyzes how augmenting alarm thresholds affects the proportion of alarm-free time and the frequency of medications administered to treat acute agitation. METHODS: Our emergency department's patient monitoring system was modified on June 28, 2022 to increase the tachycardia alarm threshold from 130 to 150 and to remove alarm sounds for several arrhythmias, including bigeminy and premature ventricular beats. A pre-post study was performed lasting 55 days before and 55 days after this intervention. The primary outcome was change in number of daily patient alarms. The secondary outcomes were alarm-free time per day and median number of antipsychotic and benzodiazepine medications administered per day. The safety outcome was the median number of patients transferred daily to the resuscitation area. We used quantile regression to compare outcomes between the pre- and post-intervention period and linear regression to correlate alarm-free time with the number of sedating medications administered. RESULTS: Between the pre- and post-intervention period, the median number of alarms per day decreased from 1332 to 845 (-37%). This was primarily driven by reduced low-priority arrhythmia alarms from 262 to 21 (-92%), while the median daily census was unchanged (33 vs 32). Median hours per day free from alarms increased from 1.0 to 2.4 (difference 1.4, 95% CI 0.8-2.1). The median number of sedating medications administered per day decreased from 14 to 10 (difference - 4, 95% CI -1 to -7) while the number of escalations in level of care to our resuscitation care area did not change significantly. Multivariable linear regression showed a 60-min increase of alarm-free time per day was associated with 0.8 (95% CI 0.1-1.4) fewer administrations of sedating medication while an additional patient on the behavioral health census was associated with 0.5 (95% CI 0.0-1.1) more administrations of sedating medication. CONCLUSION: A reasonable change in alarm parameter settings may increase the time patients and healthcare workers spend in the emergency department without alarm noise, which in this study was associated with fewer doses of sedating medications administered.

Analysis of health inequities in transfers of admitted patients from an academic emergency department to partner community hospital.

BACKGROUND: Many academic medical centers (AMC) transfer patients who require admission but not tertiary care to partner community hospitals from their emergency departments (ED). These transfers alleviate ED boarding but may worsen existing healthcare disparities. We assessed whether disparities exist in the transfer of patients from one AMC ED to a community hospital General Medical Service. METHODS: We performed a retrospective cohort study on all patients screened for transfer between April 1 and December 31, 2021. During the screening process, the treating ED physician determines whether the patient meets standardized clinical criteria and a patient coordinator requests patient consent. We collected patient demographics data from the electronic health record and performed logistic regression at each stage of the transfer process to analyze how individual characteristics impact the odds of proceeding with transfer. RESULTS: 5558 patients were screened and 596 (11%) ultimately transferred. 1999 (36%) patients were Black or Hispanic, 698 (12%) had a preferred language other than English, and 956 (17%) were on Medicaid or uninsured. A greater proportion of Black and Hispanic patients were deemed eligible for interhospital transfer compared to White patients and a greater proportion of Hispanic patients completed transfer to the community hospital (p < 0.017 after Bonferroni correction). After accounting for other demographic variables, patients older than 50 (OR 1.21, 95% CI 1.04-1.40), with a preferred language other than English (OR 1.27, 95% CI 1.00-1.62), and from a priority neighborhood (OR 1.38, 95% CI 1.18-1.61) were more likely to be eligible for transfer, while patients who were male (OR 1.50, 95% CI 1.10-2.05) and younger than 50 (OR 1.85, 95% CI 1.20-2.78) were more likely to consent to transfer (p < 0.05). CONCLUSION: Health disparities exist in the screening process for our interfacility transfer program. Further investigation into why these disparities exist and mitigation strategies should be undertaken.

Evaluation of a COVID-19 emergency department observation protocol.

OBJECTIVES: Caring for patients with COVID-19 has resulted in a considerable strain on hospital capacity. One strategy to mitigate crowding is the use of ED-based observation units to care for patients who may have otherwise required hospitalization. We sought to create a COVID-19 Observation Protocol for our ED Observation Unit (EDOU) for patients with mild to moderate COVID-19 to allow emergency physicians (EP) to gather more data for or against admission and intervene in a timely manner to prevent clinical deterioration. METHODS: This was a retrospective cohort study which included all patients who were positive for SARS-CoV-2 at the time of EDOU placement for the primary purpose of monitoring COVID-19 disease. Our institution updated the ED Observation protocol partway into the study period. Descriptive statistics were used to characterize demographics. We assessed for differences in demographics, clinical characteristics, and outcomes between admitted and discharged patients. Multivariate logistic regression models were used to assess whether meeting criteria for the ED observation protocols predicted disposition. RESULTS: During the time period studied, 120 patients positive for SARS-CoV-2 were placed in the EDOU for the primary purpose of monitoring COVID-19 disease. The admission rate for patients in the EDOU during the study period was 35%. When limited to patients who met criteria for version 1 or version 2 of the protocol, this dropped to 21% and 25% respectively. Adherence to the observation protocol was 62% and 60% during the time of version 1 and version 2 implementation, respectively. Using a multivariate logistic regression, meeting criteria for either version 1 (OR = 3.17, 95% CI 1.34-7.53, p < 0.01) or version 2 (OR = 3.18, 95% CI 1.39-7.30, p < 0.01) of the protocol resulted in a higher likelihood of discharge. There was no difference in EDOU LOS between admitted and discharged patients. CONCLUSION: An ED observation protocol can be successfully created and implemented for COVID-19 which allows the EP to determine which patients warrant hospitalization. Meeting protocol criteria results in an acceptable admission rate.

Impact of iodinated contrast allergies on emergency department operations.

OBJECTIVES: Adverse reactions to intravenous (IV) iodinated contrast media are classified by the American College of Radiology (ACR) Manual on Contrast Media as either allergic-like (ALR) or physiologic (PR). Premedication may be beneficial for patients who have prior documented mild or moderate ALR. We sought to perform a retrospective analysis of patients who received computed tomography (CT) imaging in our emergency department (ED) to establish whether listing of an iodinated contrast media allergy results in a delay in care, increases the use of non-contrast studies, and to quantify the incidence of listing iodinated contrast allergies which do not necessitate premedication. METHODS: We performed a retrospective analysis of CT scans performed in our academic medical center ED during a 6-month period. There were 12,737 unique patients of whom 454 patients had a listed iodinated contrast allergy. Of these, 106 received IV contrast and were categorized as to whether premedication was necessary. Descriptive statistics were used to evaluate patient demographics, clinical characteristics, and operational outcomes. A multivariate linear regression model was used to predict time from order to start (OTS time) of CT imaging while controlling for co-variates. RESULTS: Non-allergic patients underwent contrast-enhanced CT imaging at a significantly higher rate than allergic patients (45.9% vs. 23.3%, p < 0.01). The OTS time for allergic patients who underwent contrast-enhanced CT imaging was 360 min and significantly longer than the OTS time for non-allergic patients who underwent contrast-enhanced CT imaging (118 min, p < 0.001). Of the 106 allergic patients who underwent contrast-enhanced CT imaging, 27 (25.5%) did not meet ACR criteria for necessitating premedication. The average OTS time for these 27 patients was 296 min, significantly longer than the OTS for non-allergic patients (118 min, p < 0.01) and did not differ from the OTS time for the 79 patients who did meet premedication criteria (382 min, p = 0.23). A multivariate linear regression showed that OTS time was significantly longer if a contrast allergy was present (p < 0.001). CONCLUSION: A chart-documented iodinated contrast allergy resulted in a significant increase in time to obtain a contrast-enhanced CT study. This delay persisted among patients who did not meet ACR criteria for premedication. Appropriately deferring premedication could potentially reduce the ED length-of-stay by over 4 h for these patients.

Design and Implementation of a Real-time Monitoring Platform for Optimal Sepsis Care in an Emergency Department: Observational Cohort Study.

BACKGROUND: Sepsis is the leading cause of death in US hospitals. Compliance with bundled care, specifically serial lactates, blood cultures, and antibiotics, improves outcomes but is often delayed or missed altogether in a busy practice environment. OBJECTIVE: This study aims to design, implement, and validate a novel monitoring and alerting platform that provides real-time feedback to frontline emergency department (ED) providers regarding adherence to bundled care. METHODS: This single-center, prospective, observational study was conducted in three phases: the design and technical development phase to build an initial version of the platform; the pilot phase to test and refine the platform in the clinical setting; and the postpilot rollout phase to fully implement the study intervention. RESULTS: During the design and technical development, study team members and stakeholders identified the criteria for patient inclusion, selected bundle measures from the Center for Medicare and Medicaid Sepsis Core Measure for alerting, and defined alert thresholds, message content, delivery mechanisms, and recipients. Additional refinements were made based on 70 provider survey results during the pilot phase, including removing alerts for vasopressor initiation and modifying text in the pages to facilitate patient identification. During the 48 days of the postpilot rollout phase, 15,770 ED encounters were tracked and 711 patient encounters were included in the active monitoring cohort. In total, 634 pages were sent at a rate of 0.98 per attending physician shift. Overall, 38.3% (272/711) patients had at least one page. The missing bundle elements that triggered alerts included: antibiotics 41.6% (136/327), repeat lactate 32.4% (106/327), blood cultures 20.8% (68/327), and initial lactate 5.2% (17/327). Of the missing Sepsis Core Measures elements for which a page was sent, 38.2% (125/327) were successfully completed on time. CONCLUSIONS: A real-time sepsis care monitoring and alerting platform was created for the ED environment. The high proportion of patients with at least one alert suggested the significant potential for such a platform to improve care, whereas the overall number of alerts per clinician suggested a low risk of alarm fatigue. The study intervention warrants a more rigorous evaluation to ensure that the added alerts lead to better outcomes for patients with sepsis.

Impact of Care Initiation Model on Emergency Department Orders and Operational Metrics: Cohort Study.

INTRODUCTION: Emergency departments (ED) employ many strategies to address crowding and prolonged wait times. They include front-end Care Initiation and clinician-in-triage models that start the diagnostic and therapeutic process while the patient waits for a care space in the ED. The objective of this study was to quantify the impact of a Care Initiation model on resource utilization and operational metrics in the ED. METHODS: We performed a retrospective analysis of ED visits at our institution during October 2021. Baseline characteristics were compared with Chi-square and quantile regression. We used t-tests to calculate unadjusted difference in outcome measures, including number of laboratory tests ordered and average time patients spent in the waiting room and the ED treatment room, and the time from arrival until ED disposition. We performed propensity score analysis using matching and inverse probability weighting to quantify the direct impact of Care Initiation on outcome measures. RESULTS: There were 2,407 ED patient encounters, 1,191 (49%) of whom arrived during the hours when Care Initiation was active. A total of 811 (68%) of these patients underwent Care Initiation, while the remainder proceeded directly to the main treatment area. Patients were more likely to undergo Care Initiation if they had lower acuity and lower risk of admission, and if the ED was busier as measured by the number of recent arrivals and percentage of occupied ED beds. After adjusting for patient-specific and department-level covariates, Care Initiation did not increase the number of diagnostic laboratory tests ordered. Care Initiation was associated with increased waiting room time by 1.8 hours and longer time from arrival until disposition by 1.3 hours, but with decreased time in the main treatment area by 0.6 hours, which represents a 15% reduction. CONCLUSION: Care Initiation was associated with a 15% reduction in time spent in the main ED treatment area but longer waiting room time and longer time until ED disposition without significantly increasing the number of laboratory studies ordered. While previous studies produced similar results with Care Initiation models accessing all diagnostic modalities including imaging, our study demonstrates that a more limited Care Initiation model can still result in operational benefits for EDs.