Clinical decision support: a 25 year retrospective and a 25 year vision

B Middleton, DF Sittig, A Wright - Yearbook of medical …, 2016 - thieme-connect.com
Objective: The objective of this review is to summarize the state of the art of clinical decision
support (CDS) circa 1990, review progress in the 25 year interval from that time, and provide …

A systematic review of research design and modeling techniques in inpatient bed management

L He, SC Madathil, A Oberoi, G Servis… - Computers & Industrial …, 2019 - Elsevier
The proper allocation of limited hospital bed resources is a complex problem caused by
uncertainties in patient length of stay, fluctuations in demands, unexpected admission …

[HTML][HTML] Predicting intensive care unit length of stay and mortality using patient vital signs: machine learning model development and validation

K Alghatani, N Ammar, A Rezgui… - JMIR medical …, 2021 - medinform.jmir.org
Background: Patient monitoring is vital in all stages of care. In particular, intensive care unit
(ICU) patient monitoring has the potential to reduce complications and morbidity, and to …

Real-time prediction of inpatient length of stay for discharge prioritization

S Barnes, E Hamrock, M Toerper… - Journal of the …, 2016 - academic.oup.com
Objective Hospitals are challenged to provide timely patient care while maintaining high
resource utilization. This has prompted hospital initiatives to increase patient flow and …

Temporal pointwise convolutional networks for length of stay prediction in the intensive care unit

E Rocheteau, P Liò, S Hyland - Proceedings of the conference on health …, 2021 - dl.acm.org
The pressure of ever-increasing patient demand and budget restrictions make hospital bed
management a daily challenge for clinical staff. Most critical is the efficient allocation of …

Hospital length of stay prediction methods: a systematic review

V Lequertier, T Wang, J Fondrevelle, V Augusto… - Medical care, 2021 - journals.lww.com
Objective: This systematic review sought to establish a picture of length of stay (LOS)
prediction methods based on available hospital data and study protocols designed to …

[HTML][HTML] An overview of hospital capacity planning and optimisation

P Humphreys, B Spratt, M Tariverdi, RL Burdett… - Healthcare, 2022 - mdpi.com
Health care is uncertain, dynamic, and fast growing. With digital technologies set to
revolutionise the industry, hospital capacity optimisation and planning have never been …

Optimization of Tree‐Based Machine Learning Models to Predict the Length of Hospital Stay Using Genetic Algorithm

A Mansoori, M Zeinalnezhad… - Journal of healthcare …, 2023 - Wiley Online Library
The length of hospital stay (LOS) is a significant indicator of the quality of patient care,
hospital efficiency, and operational resilience. Considering the importance of LOS in …

Multiobjective bed management considering emergency and elective patient flows

P Landa, M Sonnessa, E Tànfani… - … in Operational Research, 2018 - Wiley Online Library
In recent years, hospitals have increasingly been faced with a growing proportion of their
inpatient work coming from the fluctuating and unpredictable demand of emergency …

Scheduling the hospital-wide flow of elective patients

D Gartner, R Kolisch - European Journal of Operational Research, 2014 - Elsevier
In this paper, we address the problem of planning the patient flow in hospitals subject to
scarce medical resources with the objective of maximizing the contribution margin. We …