Six-month post-intensive care outcomes during high and low bed occupancy due to the COVID-19 pandemic: A multicenter prospective cohort study. [PDF]
IntroductionThe COVID-19 pandemic can be seen as a natural experiment to test how bed occupancy affects post-intensive care unit (ICU) patient's functional outcomes. To compare by bed occupancy the frequency of mental, physical, and cognitive impairments
Ana Castro-Avila +6 more
doaj +4 more sources
Stressed systems: Stroke unit bed occupancy and impact on reperfusion therapy in acute ischemic stroke [PDF]
ObjectivesWe observed a decrease in the number of patients who were offered reperfusion therapy. We aimed to investigate if whether hospital system pressure measured as the percentage of stroke bed occupancy influenced decisions on treatment and ...
Rolf A. Blauenfeldt +4 more
doaj +3 more sources
Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England [PDF]
Background Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients ...
Quentin J. Leclerc +10 more
doaj +3 more sources
Recursive neural networks in hospital bed occupancy forecasting [PDF]
Background Efficient planning of hospital bed usage is a necessary condition to minimize the hospital costs. In the presented work we deal with the problem of occupancy forecasting in the scale of several months, with a focus on personnel’s holiday ...
Ekaterina Kutafina +3 more
doaj +7 more sources
Accelerometer-Based Bed Occupancy Detection for Automatic, Non-Invasive Long-Term Cough Monitoring [PDF]
We present a new machine learning based bed occupancy detection system that uses only the accelerometer signal captured by a bed-attached consumer smartphone.
Madhurananda Pahar +3 more
doaj +4 more sources
Dynamic fair balancing of COVID-19 patients over hospitals based on forecasts of bed occupancy. [PDF]
This paper introduces mathematical models that support dynamic fair balancing of COVID-19 patients over hospitals in a region and across regions. Patient flow is captured in an infinite server queueing network.
Dijkstra S +3 more
europepmc +4 more sources
Time series forecasting of bed occupancy in mental health facilities in India using machine learning [PDF]
Machine learning models are vital for forecasting and optimizing healthcare parameters, especially in the context of rising mental health issues in India and globally. With increasing demand for mental health services, effective resource management, like
G. Avinash +3 more
doaj +3 more sources
Random Survival Forests for Predicting the Bed Occupancy in the Intensive Care Unit. [PDF]
Predicting the bed occupancy of an intensive care unit (ICU) is a daunting task. The uncertainty associated with the prognosis of critically ill patients and the random arrival of new patients can lead to capacity problems and the need for reactive ...
Ruyssinck J +9 more
europepmc +7 more sources
The association between bed occupancy rates and hospital quality in the English National Health Service. [PDF]
We study whether hospitals that exhibit systematically higher bed occupancy rates are associated with lower quality in England over 2010/11–2017/18. We develop an economic conceptual framework to guide our empirical analysis and run regressions to inform
Bosque-Mercader L, Siciliani L.
europepmc +2 more sources
Hospital bed occupancy rate is an independent risk factor for COVID-19 inpatient mortality: a pandemic epicentre cohort study. [PDF]
Introduction COVID-19 first struck New York City in the spring of 2020, resulting in an unprecedented strain on our healthcare system and triggering multiple changes in public health policy governing hospital operations as well as therapeutic approaches ...
Castagna F +9 more
europepmc +2 more sources

