Developing and Evaluating Large Language Model-Generated Emergency Medicine Handoff Notes.

Importance: An emergency medicine (EM) handoff note generated by a large language model (LLM) has the potential to reduce physician documentation burden without compromising the safety of EM-to-inpatient (IP) handoffs.

Objective: To develop LLM-generated EM-to-IP handoff notes and evaluate their accuracy and safety compared with physician-written notes.

Design, Setting, And Participants: This cohort study used EM patient medical records with acute hospital admissions that occurred in 2023 at NewYork-Presbyterian/Weill Cornell Medical Center.

Aspiring to clinical significance: Insights from developing and evaluating a machine learning model to predict emergency department return visit admissions.

Return visit admissions (RVA), which are instances where patients discharged from the emergency department (ED) rapidly return and require hospital admission, have been associated with quality issues and adverse outcomes. We developed and validated a machine learning model to predict 72-hour RVA using electronic health records (EHR) data. Study data were extracted from EHR data in 2019 from three urban EDs.

Improved Utilization of Serial Testing Without Increased Admissions after Implementation of High-Sensitivity Troponin I: a Controlled Retrospective Cohort Study.

Background: Guidelines recommend high-sensitivity cardiac troponin (hs-cTn) for diagnosis of myocardial infarction. Use of hs-cTn is increasing across the U.S.

A Collaborative Emergency Medicine and Radiology Pulmonary Nodule Program: Identification of Associated Efficacy and Outcomes.

Purpose: Incidental radiologic findings are commonplace, but the episodic nature of emergency department (ED) care makes it challenging to ensure that patients obtain appropriate follow-up. Rates of follow-up range from 30% to 77%, with some studies demonstrating that more than 30% have no follow-up at all. The aim of this study is to describe and analyze the outcomes of a collaborative emergency medicine and radiology initiative to establish a formal workflow for the follow-up of pulmonary nodules identified during ED care.

Social Determinants of Health Screening and Management: Lessons at a Large, Urban Academic Health System.

Background: In October 2022 a multisite social determinants of health screening initiative was expanded across seven emergency departments of a large, urban hospital system. The aim of the initiative was to identify and address those underlying social needs that frequently interfere with a patient's health and well-being, often resulting in increased preventable system utilization.

Methods: Building on an established Patient Navigator Program, an existing screening process, and long-standing community-based partnerships, an interdisciplinary workgroup was formed to develop and implement the initiative.

Pain, Analgesic Use, and Patient Satisfaction With Spinal Versus General Anesthesia for Hip Fracture Surgery : A Randomized Clinical Trial.

Background: The REGAIN (Regional versus General Anesthesia for Promoting Independence after Hip Fracture) trial found similar ambulation and survival at 60 days with spinal versus general anesthesia for hip fracture surgery. Trial outcomes evaluating pain, prescription analgesic use, and patient satisfaction have not yet been reported.

Objective: To compare pain, analgesic use, and satisfaction after hip fracture surgery with spinal versus general anesthesia.

Laboratory Interventions to Eliminate Unnecessary Rapid COVID-19 Testing During a Reagent Shortage.

Objectives: In the fall of 2020, US medical centers were running out of rapid coronavirus disease 2019 (COVID-19) tests. The aim of this study is to evaluate the impact of an intervention to eliminate rapid test misutilization and to quantify the effect of the countermeasures to control rapid test ordering using a test utilization dashboard.

Methods: Interventions were made to preserve a severely limited supply of rapid diagnostic tests based on real-time analysis of a COVID-19 test utilization dashboard.

In severe COVID-19, high-flow vs. conventional oxygen therapy reduced intubation and time to clinical recovery at 28 d.

Ospina-Tascón GA, Calderón-Tapia LE, García AF, et al. JAMA. 2021;326:2161-71.

Emergency Department Utilization Among Maintenance Hemodialysis Patients: A Systematic Review.

Rationale & Objective: To evaluate predictors of emergency department (ED) utilization by adult patients receiving hemodialysis (HD) and interventions to reduce ED utilization by HD patients.

Study Design: We searched Ovid MEDLINE, Ovid Embase, and the Cochrane Library for randomized controlled trials and observational studies published until April 2020.

Setting & Participants: We included studies that investigated predictors of ED utilization and/or interventions to reduce ED utilization in HD patients.

Emergency Department Patient Navigator Program Demonstrates Reduction in Emergency Department Return Visits and Increase in Follow-up Appointment Adherence.

Background: An estimated 56% of emergency department (ED) visits are avoidable. One motivation for return visits is patients' perception of poor access to timely outpatient care. Efforts to facilitate access may help reduce preventable ED visits.

Deep significance clustering: a novel approach for identifying risk-stratified and predictive patient subgroups.

Objective: Deep significance clustering (DICE) is a self-supervised learning framework. DICE identifies clinically similar and risk-stratified subgroups that neither unsupervised clustering algorithms nor supervised risk prediction algorithms alone are guaranteed to generate.

Materials And Methods: Enabled by an optimization process that enforces statistical significance between the outcome and subgroup membership, DICE jointly trains 3 components, representation learning, clustering, and outcome prediction while providing interpretability to the deep representations.

Socioeconomic variation in characteristics, outcomes, and healthcare utilization of COVID-19 patients in New York City.

Objectives: There is limited evidence on how clinical outcomes differ by socioeconomic conditions among patients with coronavirus disease 2019 (COVID-19). Most studies focused on COVID-19 patients from a single hospital. Results based on patients from multiple health systems have not been reported.

Calculated decisions: ACEP ED COVID-19 management tool.

This supplement reviews the ACEP ED COVID-19 Management Tool, an emergency department classification and management tool for adult patients (aged ≥18 years) with suspected or confirmed SARS-CoV-2.

Machine Learning Highlights Downtrending of COVID-19 Patients with a Distinct Laboratory Profile.

Background: New York City (NYC) experienced an initial surge and gradual decline in the number of SARS-CoV-2-confirmed cases in 2020. A change in the pattern of laboratory test results in COVID-19 patients over this time has not been reported or correlated with patient outcome.

Methods: We performed a retrospective study of routine laboratory and SARS-CoV-2 RT-PCR test results from 5,785 patients evaluated in a NYC hospital emergency department from March to June employing machine learning analysis.

A predictive model of clinical deterioration among hospitalized COVID-19 patients by harnessing hospital course trajectories.

From early March through mid-May 2020, the COVID-19 pandemic overwhelmed hospitals in New York City. In anticipation of ventilator shortages and limited ICU bed capacity, hospital operations prioritized the development of prognostic tools to predict clinical deterioration. However, early experience from frontline physicians observed that some patients developed unanticipated deterioration after having relatively stable periods, attesting to the uncertainty of clinical trajectories among hospitalized patients with COVID-19.

MyEDCare: Evaluation of a Smartphone-Based Emergency Department Discharge Process.

Background: Poor comprehension and low compliance with post-ED (emergency department) care plans increase the risk of unscheduled ED return visits and adverse outcomes. Despite the growth of personal health records to support transitions of care, technological innovation's focus on the ED discharge process has been limited. Recent literature suggests that digital communication incorporated into post-ED care can improve patient satisfaction and care quality.

Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions.

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling.

Testing-on-a-probe biosensors reveal association of early SARS-CoV-2 total antibodies and surrogate neutralizing antibodies with mortality in COVID-19 patients.

The association of mortality with the early humoral response to SARS-CoV-2 infection within the first few days after onset of symptoms (DAOS) has not been thoroughly investigated partly due to a lack of sufficiently sensitive antibody testing methods. Here we report two sensitive and automated testing-on-a-probe (TOP) biosensor assays for SARS-CoV-2 viral specific total antibodies (TAb) and surrogate neutralizing antibodies (SNAb), which are suitable for clinical use. The TOP assays employ an RBD-coated quartz probe using a Cy5-Streptavidin-polysacharide conjugate to improve sensitivity and minimize interference.

No increase in the incidence of cardiac troponin I concentration above the 99th percentile by Siemens Centaur high-sensitivity compared to the contemporary assay.

Background: This study aimed to compare the incidence of cardiac troponin I (cTnI) concentrations above the limit of quantification (LOQ) and the sex-specific 99th percentile upper reference limits (URLs) between the Ultra contemporary cTnI assay and the high-sensitivity (hs-cTnI) assay on Siemens Centaur in patients evaluated in the emergency department (ED) and inpatient at a U.S. urban academic hospital.