English
Related papers

Related papers: Forecasting mortality associated emergency departm…

200 papers

Emergency department (ED) crowding is a well-recognized threat to patient safety and it has been repeatedly associated with increased mortality. Accurate forecasts of future service demand could lead to better resource management and has…

Systems and Control · Electrical Eng. & Systems 2023-01-24 Jalmari Tuominen , Teemu Koivistoinen , Juho Kanniainen , Niku Oksala , Ari Palomäki , Antti Roine

Emergency department (ED) crowding is a significant threat to patient safety and it has been repeatedly associated with increased mortality. Forecasting future service demand has the potential patient outcomes. Despite active research on…

Machine Learning · Computer Science 2023-09-01 Jalmari Tuominen , Eetu Pulkkinen , Jaakko Peltonen , Juho Kanniainen , Niku Oksala , Ari Palomäki , Antti Roine

Background: Emergency department (ED) overcrowding remains a major challenge, causing delays in care and increased operational strain. Hospital management often reacts to congestion after it occurs. Machine learning predictive modeling…

Machine Learning · Computer Science 2025-04-29 Orhun Vural , Bunyamin Ozaydin , Khalid Y. Aram , James Booth , Brittany F. Lindsey , Abdulaziz Ahmed

Environments such as shopping malls, airports, or hospital emergency departments often experience crowding, with many people simultaneously requesting service. Crowding is highly noisy, with sudden overcrowding "spikes". Past research has…

Physics and Society · Physics 2023-08-16 Gil Parnass , Osnat Levtzion-Korach , Renana Peres , Michael Assaf

Over the past several years, across the globe, there has been an increase in people seeking care in emergency departments (EDs). ED resources, including nurse staffing, are strained by such increases in patient volume. Accurate forecasting…

There were 25.6 million attendances at Emergency Departments (EDs) in England in 2019 corresponding to an increase of 12 million attendances over the past ten years. The steadily rising demand at EDs creates a constant challenge to provide…

Emergency Department (ED) overcrowding continues to be a public health issue as well as a patient safety issue. The underlying factors leading to ED crowding are numerous, varied, and complex. Although lack of in-hospital beds is frequently…

Overcrowding in emergency departments (ED) remains a persistent operational challenge worldwide, causing delays in care delivery and downstream congestion. ED boarding time, defined as the duration admitted patients remain in the ED while…

Machine Learning · Computer Science 2026-05-20 Orhun Vural , Abdulaziz Ahmed , Ferhat Zengul , James Booth , Bunyamin Ozaydin

Study Objective: To analyze the factors influencing Emergency Department (ED) overcrowding by examining the impacts of operational, environmental, and external variables, including weather conditions and football games. Methods: This study…

Computers and Society · Computer Science 2025-05-13 Abdulaziz Ahmed , Khalid Y Aram , Mohammed Alzeen , Orhun Vural , James Booth , Brittany F. Lindsey , Bunyamin Ozaydin

Background: The stochastic behavior of patient arrival at an emergency department (ED) complicates the management of an ED. More than 50% of hospitals ED capacity tends to operate beyond its normal capacity and eventually fails to deliver…

Computers and Society · Computer Science 2019-01-10 Avishek Choudhury

Emergency department (ED) crowding has been an increasing problem worldwide. Prior research has identified factors that contribute to ED crowding. However, the relationships between these remain incompletely understood. This study's…

This study presents a deep learning-based framework for predicting emergency department (ED) boarding counts six hours in advance using only operational and contextual data, without patient-level information. Data from ED tracking systems,…

Machine Learning · Computer Science 2025-07-14 Orhun Vural , Bunyamin Ozaydin , James Booth , Brittany F. Lindsey , Abdulaziz Ahmed

We study the estimation of the probability distribution of individual patient waiting times in an emergency department (ED). Our feature-rich modelling allows for dynamic updating and refinement of waiting time estimates as patient- and…

Applications · Statistics 2020-06-02 Siddharth Arora , James W. Taylor , Ho-Yin Mak

Emergency Departments (EDs) are a fundamental element of the Portuguese National Health Service, serving as an entry point for users with diverse and very serious medical problems. Due to the inherent characteristics of the ED; forecasting…

Computers and Society · Computer Science 2023-06-27 Francisco M. Caldas , Cláudia Soares

The intensive care unit (ICU) manages critically ill patients, many of whom face a high risk of mortality. Early and accurate prediction of in-hospital mortality within the first 24 hours of ICU admission is crucial for timely clinical…

Concerts, protests, and sporting events are occurring with increasing frequency and magnitude. The extreme physical conditions common to these events are known to cause injuries and loss-of-life due to the emergence of collective motion…

Physics and Society · Physics 2018-09-25 Arianna Bottinelli , Jesse L. Silverberg

Asymmetric information in healthcare implies that patients could have difficulty trading off non-health and health related information. I document effects on patient demand when predicted wait time is disclosed to patients in an emergency…

General Economics · Economics 2023-09-26 Stephenson Strobel

Worldwide, many millions of people die suddenly and unexpectedly each year, either with or without a prior history of cardiovascular disease. Such events are sparse (once in a lifetime), many victims will not have had prior investigations…

Machine Learning · Computer Science 2023-09-06 Yola Jones , Fani Deligianni , Jeff Dalton , Pierpaolo Pellicori , John G F Cleland

Urgent care clinics and emergency departments around the world periodically suffer from extended wait times beyond patient expectations due to inadequate staffing levels. These delays have been linked with adverse clinical outcomes.…

Machine Learning · Computer Science 2022-05-27 Paula Maddigan , Teo Susnjak

The electrocardiogram (ECG) is a widely-used medical test, typically consisting of 12 voltage versus time traces collected from surface recordings over the heart. Here we hypothesize that a deep neural network can predict an important…

‹ Prev 1 2 3 10 Next ›