Sepsis Prediction at Emergency Department Triage Using Natural Language Processing: Retrospective Cohort Study.

Background: Despite its high lethality, sepsis can be difficult to detect on initial presentation to the emergency department (ED). Machine learning-based tools may provide avenues for earlier detection and lifesaving intervention.

Objective: The study aimed to predict sepsis at the time of ED triage using natural language processing of nursing triage notes and available clinical data.

A case of acute colonic pseudo-obstruction, sigmoid volvulus, and massive pneumoperitoneum in a young female patient.

Introduction And Importance: Acute colonic pseudo-obstruction (ACPO) is an uncommon phenomenon that is especially rare in young patients and can result in bowl ischemia and perforation if left untreated. Furthermore, pneumoperitoneum is almost always a concerning imaging finding and in the context of recent colonic resection may be a sign of anastomotic leakage.

Case Presentation: We describe a case of a young female patient with postpartum ACPO who subsequently underwent a hemicolectomy with colorectal anastomosis.

Association of the Home Health Value-Based Purchasing Model With Quality, Utilization, and Medicare Payments After the First 5 Years.

Importance: The original Home Health Value-Based Purchasing (HHVBP) model provided financial incentives to home health agencies for quality improvement in 9 randomly selected US states.

Objective: To evaluate quality, utilization, and Medicare payments for home health patients in HHVBP states compared with those in comparison states.

Design, Setting, And Participants: This cohort study was conducted in 2021 with secondary data from January 2013 to December 2020.

The Use of a Self-triage Tool to Predict COVID-19 Cases and Hospitalizations in the State of Georgia.

Introduction: The coronavirus 2019 (COVID-19) pandemic has created significant burden on healthcare systems throughout the world. Syndromic surveillance, which collects real-time data based on a range of symptoms rather than laboratory diagnoses, can help provide timely information in emergency response. We examined the effectiveness of a web-based COVID-19 symptom checking tool (C19Check) in the state of Georgia (GA) in predicting COVID-19 cases and hospitalizations.

Prediction of emergency department resource requirements during triage: An application of current natural language processing techniques.

Objective: Accurate triage in the emergency department (ED) is critical for medical safety and operational efficiency. We aimed to predict the number of future required ED resources, as defined by the Emergency Severity Index (ESI) triage protocol, using natural language processing of nursing triage notes.

Methods: We constructed a retrospective cohort of all 265,572 consecutive ED encounters from 2015 to 2016 from 3 separate clinically heterogeneous academically affiliated EDs.