Association of Geographic Distance and Hospital Characteristics With Use of Interhospital Transfer by Air: A Multicenter Retrospective Study.

Objective: Interhospital transfer by air (IHTA) represents the majority of helicopter air ambulance transports in the United States, but the evaluation of what factors are associated with utilization has been limited. We aimed to assess the association of geographic distance and hospital characteristics (including patient volume) with the use of IHTA.

Methods: This was a multicenter, retrospective study of helicopter flight request data from 2018 provided by a convenience sample of 4 critical care transport medicine programs in 3 US census regions.

Causal Association of Physician-in-Triage with Improved Pediatric Sepsis Care: A Single-Center, Emergency Department Experience.

Unlabelled: Approximately 75,000 children are hospitalized for sepsis yearly in the United States, with 5%-20% mortality estimates. Outcomes are closely related to the timeliness of sepsis recognition and antibiotic administration.

Methods: A multidisciplinary sepsis task force formed in the Spring of 2020 aimed to assess and improve pediatric sepsis care in the pediatric emergency department (ED).

Simulation device for shoulder reductions: overview of prototyping, testing, and design instructions.

Background: Shoulder dislocations are common occurrences, yet there are few simulation devices to train medical personnel on how to reduce these dislocations. Reductions require a familiarity with the shoulder and a nuanced motion against strong muscle tension. The goal of this work is to describe the design of an easily replicated, low-cost simulator for training shoulder reductions.

Critical Care Transport of the Temporary Portable Ventricular Support Device.

Objective: Cardiogenic shock is a critical emergency for which ventricular support devices (VSDs), such as the Impella (AbioMed Inc, Danvers, MA), are placed. Many referring facilities cannot provide cardiac intensive care. This requires a regional approach to the care of patients with VSD.

Development and Validation of Machine Learning Models to Predict Admission From Emergency Department to Inpatient and Intensive Care Units.

Study Objective: This study aimed to develop and validate 2 machine learning models that use historical and current-visit patient data from electronic health records to predict the probability of patient admission to either an inpatient unit or ICU at each hour (up to 24 hours) of an emergency department (ED) encounter. The secondary goal was to provide a framework for the operational implementation of these machine learning models.

Methods: Data were curated from 468,167 adult patient encounters in 3 EDs (1 academic and 2 community-based EDs) of a large academic health system from August 1, 2015, to October 31, 2018.

Point-of-Care Laboratory Data Collection During Critical Care Transport.

Objective: Critical care transport involves a high level of intensive clinical care in a resource-limited environment. These patients require multiple assessments guiding specialty treatments, including blood product administration, intravenous electrolyte replacement, ventilator management, and extracorporeal membrane oxygenation. This study aims to measure the usage of point-of-care (POC) laboratory data during critical care transport.

A Method for Grouping Emergency Department Visits by Severity and Complexity.

Introduction: Triage functions to quickly prioritize care and sort patients by anticipated resource needs. Despite widespread use of the Emergency Severity Index (ESI), there is still no universal standard for emergency department (ED) triage. Thus, it can be difficult to objectively assess national trends in ED acuity and resource requirements.

Hirschsprung's Disease: A Rare Adult Diagnosis.

Case Presentation: Approximately 94% of patients with Hirschsprung's disease (HD) are diagnosed before the age of five. In our case, a young adult with years of constipation presented to the emergency department with significant abdominal distention. He was ultimately diagnosed with HD, which was identified using computed tomography (CT).

Real-World Integration of a Sepsis Deep Learning Technology Into Routine Clinical Care: Implementation Study.

Background: Successful integrations of machine learning into routine clinical care are exceedingly rare, and barriers to its adoption are poorly characterized in the literature.

Objective: This study aims to report a quality improvement effort to integrate a deep learning sepsis detection and management platform, Sepsis Watch, into routine clinical care.

Methods: In 2016, a multidisciplinary team consisting of statisticians, data scientists, data engineers, and clinicians was assembled by the leadership of an academic health system to radically improve the detection and treatment of sepsis.

NHAMCS Validation of Emergency Severity Index as an Indicator of Emergency Department Resource Utilization.

Introduction: Triage systems play a vital role in emergency department (ED) operations and can determine how well a given ED serves its local population. We sought to describe ED utilization patterns for different triage levels using the National Hospital Ambulatory Medical Care Survey (NHAMCS) database.

Methods: We conducted a multi-year secondary analysis of the NHAMCS database from 2009-2011.

Validation of the modified Sgarbossa criteria for acute coronary occlusion in the setting of left bundle branch block: A retrospective case-control study.

Background: The modified Sgarbossa criteria were proposed in a derivation study to be superior to the original criteria for diagnosing acute coronary occlusion (ACO) in left bundle branch block (LBBB). The new rule replaces the third criterion (5 mm of excessively discordant ST elevation [STE]) with a proportion (at least 1 mm STE and STE/S wave ≤-0.25).