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[HTML][HTML] Overcrowding in emergency department: causes, consequences, and solutions—a narrative review
M Sartini, A Carbone, A Demartini, L Giribone, M Oliva… - Healthcare, 2022 - mdpi.com
Overcrowding in Emergency Departments (EDs) is a phenomenon that is now widespread
globally and causes a significant negative impact that goes on to affect the entire hospital …
globally and causes a significant negative impact that goes on to affect the entire hospital …
An overview of health forecasting
IN Soyiri, DD Reidpath - Environmental health and preventive medicine, 2013 - Springer
Health forecasting is a novel area of forecasting, and a valuable tool for predicting future
health events or situations such as demands for health services and healthcare needs. It …
health events or situations such as demands for health services and healthcare needs. It …
Emergency department and hospital crowding: causes, consequences, and cures
P McKenna, SM Heslin, P Viccellio… - Clinical and …, 2019 - pmc.ncbi.nlm.nih.gov
Overcrowding with associated delays in patient care is a problem faced by emergency
departments (EDs) worldwide. ED overcrowding can be the result of poor ED department …
departments (EDs) worldwide. ED overcrowding can be the result of poor ED department …
Evaluating the accuracy of a state-of-the-art large language model for prediction of admissions from the emergency room
BS Glicksberg, P Timsina, D Patel… - Journal of the …, 2024 - academic.oup.com
Background Artificial intelligence (AI) and large language models (LLMs) can play a critical
role in emergency room operations by augmenting decision-making about patient …
role in emergency room operations by augmenting decision-making about patient …
Evaluating Lean in healthcare
Purpose–The purpose of this paper is to present findings relating to how Lean is
implemented in English hospitals. Design/methodology/approach–Lean implementation …
implemented in English hospitals. Design/methodology/approach–Lean implementation …
Using data mining to predict hospital admissions from the emergency department
B Graham, R Bond, M Quinn, M Mulvenna - Ieee Access, 2018 - ieeexplore.ieee.org
Crowding within emergency departments (EDs) can have significant negative
consequences for patients. EDs therefore need to explore the use of innovative methods to …
consequences for patients. EDs therefore need to explore the use of innovative methods to …
Performance evaluation of Emergency Department patient arrivals forecasting models by including meteorological and calendar information: A comparative study
VK Sudarshan, M Brabrand, TM Range… - Computers in Biology and …, 2021 - Elsevier
The volume of daily patient arrivals at Emergency Departments (EDs) is unpredictable and is
a significant reason of ED crowding in hospitals worldwide. Timely forecast of patients …
a significant reason of ED crowding in hospitals worldwide. Timely forecast of patients …
Modified genetic algorithm-based feature selection combined with pre-trained deep neural network for demand forecasting in outpatient department
A well-performed demand forecasting can provide outpatient department (OPD) managers
with essential information for staff scheduling and rostering, considering the non-reservation …
with essential information for staff scheduling and rostering, considering the non-reservation …
Forecasting daily emergency department visits using calendar variables and ambient temperature readings
I Marcilio, S Hajat, N Gouveia - Academic emergency medicine, 2013 - Wiley Online Library
Objectives This study aimed to develop different models to forecast the daily number of
patients seeking emergency department (ED) care in a general hospital according to …
patients seeking emergency department (ED) care in a general hospital according to …
A workflow for visual diagnostics of binary classifiers using instance-level explanations
J Krause, A Dasgupta, J Swartz… - … IEEE Conference on …, 2017 - ieeexplore.ieee.org
Human-in-the-loop data analysis applications necessitate greater transparency in machine
learning models for experts to understand and trust their decisions. To this end, we propose …
learning models for experts to understand and trust their decisions. To this end, we propose …