Results 241 to 250 of about 97,192 (289)

Skilled Nursing Facility Network Capacity and Hospital Length of Stay.

open access: yesJAMA Netw Open
Prusynski RA   +5 more
europepmc   +1 more source

A combination of deterministic and stochastic approaches to optimize bed capacity in a hospital unit

open access: yesComputer Methods and Programs in Biomedicine, 2008
Random number of arrivals and random length of stays make the number of patients in a hospital unit behave as a stochastic process. This makes the determination of the optimum size of the bed capacity more difficult. The number of admissions per day, service level and occupancy level are key control parameters that affect the optimum size of the ...
Ali Kokangul
exaly   +5 more sources

An Objective Method for Bed Capacity Planning in a Hospital Department

open access: yesMethods of Information in Medicine, 2007
Summary Objectives: To propose an objective approach in order to determine the number of beds required for a hospital department by considering how recruitment fluctuates over time. To compare this approach with classical bed capacity planning techniques. Methods: Asimulated data-based
Thierry Chaussalet
exaly   +4 more sources

Flexing bed stock: A hospital capacity management case study

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014
As hospitals struggle to meet rising demand for their services, efficient capacity management is critical to the success of their efforts. A popular strategy employed by hospitals to meet the variability in demand for their services is to 'flex' their capacity, i.e. to vary the number of available staffed beds to suit demand on a regular basis.
Sankalp Khanna, Justin Boyle
exaly   +3 more sources

A network flow approach to optimizing hospital bed capacity decisions

Health Care Management Science, 2006
The delivery of cost-effective and quality hospital-based health care remains an important and ongoing challenge for the American health care industry. Despite numerous advances in medical procedures and technologies, a growing array of outpatient health care options, limits on inpatient reimbursements, and almost two decades of hospital contraction ...
Murray J Coté
exaly   +3 more sources

Annual Bed Statistics Give a Misleading Picture of Hospital Surge Capacity

Annals of Emergency Medicine, 2006
I describe how annual hospital surge capacity is affected by within-year variation in patient volume and bed supply.Surge capacity was measured as the percentage and total number of hospital beds that are not occupied by patients. Administrative data were used to calculate these bed statistics for 78 hospitals in New Jersey--statewide and by emergency ...
Derek Delia
exaly   +3 more sources

Modelling for the planning and management of bed capacities in hospitals

Journal of the Operational Research Society, 2002
Summary: The internal dynamics of a hospital represent a complex non-linear structure. Planning and management of bed capacities must be evaluated within an environment of uncertainty, variability and limited resources. A common approach is to plan and manage capacities based on simple deterministic spreadsheet calculations.
Harper, P.R., Shahani, A.K.
openaire   +3 more sources

A simple method to optimize hospital beds capacity

International Journal of Medical Informatics, 2005
The number of acute hospital beds is determined by health authorities using methods based on ratios and/or target bed occupancy rates. These methods fail to consider the variability in hospitalization demands over time. On the other hand, the implementation of sophisticated models requires the decision concerning the number of beds to be made by an ...
Jean-Michel Nguyen   +6 more
openaire   +2 more sources

Forecast-Based Newsvendor Models for Hospital Bed Capacity Management

IEEE Robotics and Automation Letters, 2021
Hospitals worldwide share common challenges in finding the optimal number of patient beds in advance, which is referred to as the bed capacity management problem. Effective management cannot be achieved without an appropriate understanding of the stochastic nature of patient demands.
Xueru Xu, Li Luo 0001, Xiang Zhong
openaire   +1 more source

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