ArticleJournal of medical systems2014
Time series modelling and forecasting of emergency department overcrowding.
Article in Journal of medical systems, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
36 citing papers in PubMed, 153 citations in OpenAlex.
- AI-powered models for overcrowding prediction at TUMS hospitals.Scientific reports · 2025Article
- Predicting Waiting Times for Medical Tasks in a Pediatric Hospital Using Machine Learning: Comprehensive, Retrospective, Real-World Study.JMIR medical informatics · 2025Article
- An Artificial Intelligence-Based Framework for Predicting Emergency Department Overcrowding: Development and Evaluation Study.JMIR medical informatics · 2025Article
- Forecasting Surgical Bed Utilization: Architectural Design of a Machine Learning Pipeline Incorporating Predicted Length of Stay and Surgical Volume.Journal of medical systems · 2025Article
- Artificial intelligence-driven forecasting and shift optimization for pediatric emergency department crowding.JAMIA open · 2025Article
- Statistical Analysis and Forecasts of Performance Indicators in the Romanian Healthcare System.Healthcare (Basel, Switzerland) · 2025Article
- Enhanced forecasting of emergency department patient arrivals using feature engineering approach and machine learning.BMC medical informatics and decision making · 2024Article
- Feasibility of forecasting future critical care bed availability using bed management data.BMJ health & care informatics · 2024Article
- Artificial intelligence and discrete-event simulation for capacity management of intensive care units during the Covid-19 pandemic: A case study.Journal of business research · 2023Article
- A systematic review of the modelling of patient arrivals in emergency departments.Quantitative imaging in medicine and surgery · 2023Review
- Article
- An emergency room influx and trauma cases prediction in a Brazilian ophthalmological hospital by an ophthalmologist without code experience.Arquivos brasileiros de oftalmologia · 2022Article
- Forecasting of Daily Outpatient Visits Based on Genetic Programming.Iranian journal of public health · 2022Article
- Machine learning based forecast for the prediction of inpatient bed demand.BMC medical informatics and decision making · 2022Article
- Towards accurate prediction of patient length of stay at emergency department: a GAN-driven deep learning framework.Journal of ambient intelligence and humanized computing · 2022Article
- Effectiveness of cascading time series models based on meteorological factors in improving health risk prediction.Environmental science and pollution research international · 2022Article
- Dynamics of the Third Wave of COVID-19 from the Perspective of the Emergency Department in a Large Regional Hospital-Single Center Observational Study.Healthcare (Basel, Switzerland) · 2021Article
- How New Mexico Leveraged a COVID-19 Case Forecasting Model to Preemptively Address the Health Care Needs of the State: Quantitative Analysis.JMIR public health and surveillance · 2021Article
- Prediction of Obstetric Patient Flow and Horizontal Allocation of Medical Resources Based on Time Series Analysis.Frontiers in public health · 2021Article
- Forecasting emergency department overcrowding: A deep learning framework.Chaos, solitons, and fractals · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Efficient management of patient flow (demand) in emergency departments (EDs) has become an urgent issue for many hospital administrations. Today, more and more attention is being paid to hospital management systems to optimally manage patient flow and to improve management strategies, efficiency and safety in such establishments. To this end, EDs require significant human and material resources, but unfortunately these are limited. Within such a framework, the ability to accurately forecast demand in emergency departments has considerable implications for hospitals to improve resource allocation and strategic planning. The aim of this study was to develop models for forecasting daily attendances at the hospital emergency department in Lille, France. The study demonstrates how time-series analysis can be used to forecast, at least in the short term, demand for emergency services in a hospital emergency department. The forecasts were based on daily patient attendances at the paediatric emergency department in Lille regional hospital centre, France, from January 2012 to December 2012. An autoregressive integrated moving average (ARIMA) method was applied separately to each of the two GEMSA categories and total patient attendances. Time-series analysis was shown to provide a useful, readily available tool for forecasting emergency department demand.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.