Modeling Patient Flows Using a Queuing Network with Blocking

Koizumi, Naoru; Kuno, Eri; Smith, Tony

doi:10.1007/s10729-005-5216-3

Cited by 121 publications

(117 citation statements)

References 26 publications

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“…The LOS is easily derived from the hospital information system as both time of admission and time of discharge are logged on individual patient level. Length of stay is affected by congestion and delay in the care chain (Koizumi et al 2005), which means that careful interpretation is required, see Sect. 3.2.…”

Section: Length Of Staymentioning

confidence: 99%

Dimensioning hospital wards using the Erlang loss model

Bekker²,

et al. 2009

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How many beds must be allocated to a specific clinical ward to meet production targets? When budgets get tight, what are the effects of downsizing a nursing unit? These questions are often discussed by medical professionals, hospital consultants, and managers. In these discussions the occupancy rate is of great importance and often used as an input parameter. Most hospitals use the same target occupancy rate for all wards, often 85%. Sometimes an exception is made for critical care and intensive care units. In this paper we demonstrate that this equity assumption is unrealistic and that it might result in an excessive number of refused admissions, particularly for smaller units. Queuing theory is used to quantify this impact. We developed a decision support system, based on the Erlang loss model, which can be used to evaluate the current size of nursing units. We validated this model with hospital data over the years [2004][2005][2006]. Finally, we demonstrate the efficiency of merging departments.

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Section: Length Of Staymentioning

confidence: 99%

Dimensioning hospital wards using the Erlang loss model

Bekker²,

et al. 2009

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“…Korpororal et al [11] analyzed the congestion level in penitetiary in Netherlands. Koizumi et al [10] uses decomposition algorithm in mental health. Health care publications involving analysis of blocking are rare.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Restricted Queueing Networks - A Blocking Approach

Sreekala¹,

Manoharan²

2016

JSSA

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In this paper we consider an open restricted queueing network with Poisson arrivals and exponential service times at stations and present an approximation method for analysis, made by node-by-node decomposition employing the concept of effective arrival rate and effective service rate. The steady state characteristics of the network system and of individual stations are obtained. Congestion due to blocking has been a severe problem in several health care studies, but among studies that apply queueing theory, those analyzing the blocking mechanism are still limited. This study applies to a health care system of infertility clinic considered as an open queueing network with blocking caused due to the capacity of the waiting space between stations. The method is illustrated with the help of an example network to study the efficiency of the approximation method. Finally a simulation study is performed to assess the transient behaviour of the network system. The blocking approach presented here for a simple model of a healthcare system can be easily adapted to any general open restricted queueing network.

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“…A queuing theory model with blocking was developed in [115] to analyze the congestion in a mental health system. The model encompasses the interaction of the community, acute hospitals, extended acute hospitals, residential facilities and support housing.…”

Section: Geriatric Care and Mental Health Carementioning

confidence: 99%

Interacting hospital departments and uncertain patient flows : theoretical models and applications

Vanberkel¹

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Cover design: The weave of white dots forming the asymmetric pattern abstractly represent an uncertain flow of patients. The weave culminates in the middle of multiple heterogeneous particles which together form the single image on the back cover. This image abstractly represents multiple departments interacting to form a single hospital. All design elements are part of the University of Twente's branding strategy.

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Modeling Patient Flows Using a Queuing Network with Blocking

Cited by 121 publications

References 26 publications

Dimensioning hospital wards using the Erlang loss model

Dimensioning hospital wards using the Erlang loss model

Analysis of Restricted Queueing Networks - A Blocking Approach

Interacting hospital departments and uncertain patient flows : theoretical models and applications

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