Analysis of capacity management of the intensive care unit in a hospital

Kim, Seung–Chul; Horowitz, Ira; Young, Karl; Buckley, Thomas

doi:10.1016/s0377-2217(98)00135-0

Cited by 132 publications

(68 citation statements)

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“…Most ICU's have to cope with a large stochastic demand generated by emergency admissions, and simulation is often employed as the prime analytical tool (Kim, 1999 (Vanberkel et al, 2010) may assume that surgery will not be postponed due to a lack of a bed but this is a very real possibility in the HLC. In the HLC, the elective surgery is characterised by a very high proportion of the patients requiring at least a short ICU stay: a surgical procedure will only begin if an ICU bed is available.…”

Section: Modelling Icu's and The Balance Of Resourcesmentioning

confidence: 99%

“…Capacity planning studies often consider the trade-off between service level and the utilisation of one dominant resource, as when considering ICU bed provision and the implications for rejecting or diverting patients (Kim, 1999). Many models do not include crucial management responses to demand; in reality there may be opportunities to manage admissions, as in the HLC, or expedite patient transfer or discharge of patients.…”

Section: Modelling Icu's and The Balance Of Resourcesmentioning

confidence: 99%

“…This is highly variable, as illustrated by the empirical distribution of patients' ICU stay in (Litvak et al, 2008) and this provides an approximate but imperfect fit to the HLC length of stay data, as illustrated in Fig.1. However, it has been suggested that while an exponential distribution can provide a reasonable fit for emergency ICU stay it is not appropriate for elective patients (Kim, 1999). In the current application, an order 2 hyperexponential model offers some improvement but an order 3 model provides a significantly better fit, as illustrated in Fig.1.…”

Section: Referrals and Length Of Staymentioning

confidence: 99%

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Balancing operating theatre and bed capacity in a cardiothoracic centre

Bowers

2013

Health Care Manag Sci

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This paper examines the balance between operating theatre and bed capacity in a specialist facility providing elective heart and lung surgery. The capacity of the whole facility is determined by the availability of operating theatre time and Intensive Care beds: without both resources surgery has to be postponed. Although the admissions can be managed, there are significant stochastic components, notably the cancellation of theatre procedures and patients' length of stay on the Intensive Care Unit. A simulation was constructed to explore the interdependencies of resource availabilities and the daily demand. The model was developed with clinical and management staff to explore options for expanding the capacity of the whole facility. Ideally the bed and theatre capacity should be well balanced but unmatched increases in the capacity of either resource can still be beneficial. The study provides an example of a capacity planning problem in which there is uncertainty in the demand and availabilities of two symbiotic resources.

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Section: Modelling Icu's and The Balance Of Resourcesmentioning

confidence: 99%

Section: Modelling Icu's and The Balance Of Resourcesmentioning

confidence: 99%

Section: Referrals and Length Of Staymentioning

confidence: 99%

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Balancing operating theatre and bed capacity in a cardiothoracic centre

Bowers

2013

Health Care Manag Sci

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“…A simulation model had been presented by Kim S. C. et al [15][16][17] for balancing the number of beds available and deterministic arrivals in ICU after a surgical intervention in hospitals for each day. Hojati M. et al [18] considered a two-stage procedure for solving the employee scheduling problem in fast food restaurant services employing heterogeneous, part-time employees with limited availability.…”

Section: Introductionmentioning

confidence: 99%

Repair Shop Job Scheduling With Parallel Operators and Multiple Constraints Using Simulated Annealing

Shivasankaran¹,

Kumar²,

Nallakumarasamy³

et al. 2013

IJCIS

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Scheduling problems are generally treated as NP -complete combinatorial optimization problems which is a multi-objective and multi constraint one. Repair shop Job sequencing and operator allocation is one such NP -complete problem. For such problems, an efficient technique is required that explores a wide range of solution space. This paper deals with Simulated Annealing Technique, a Meta -heuristic to solve the complex Car Sequencing and Operator Allocation problem in a car repair shop. The algorithm is tested with several constraint settings and the solution quality exceeds the results reported in the literature with high convergence speed and accuracy. This algorithm could be considered as quite effective while other heuristic routine fails.

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“…Several other consequences of congested wards can be identified, all being a threat to the provided quality of care. First, patients might have to be transferred to another hospital in case of an emergency [108,292,347,524]. Second, patients may (temporarily) be placed in less appropriate units, so-called misplacements [112,156,157,217,242,247,524].…”

Section: Strategic Planningmentioning

confidence: 99%

Integrated decision making in healthcare : an operations research and management science perspective

Hulshof¹

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Analysis of capacity management of the intensive care unit in a hospital

Cited by 132 publications

References 1 publication

Balancing operating theatre and bed capacity in a cardiothoracic centre

Balancing operating theatre and bed capacity in a cardiothoracic centre

Repair Shop Job Scheduling With Parallel Operators and Multiple Constraints Using Simulated Annealing

Integrated decision making in healthcare : an operations research and management science perspective

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