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Allen M, Spencer A, Gibson A, et al. Right cot, right place, right time: improving the design and organisation of neonatal care networks – a computer simulation study. Southampton (UK): NIHR Journals Library; 2015 May. (Health Services and Delivery Research, No. 3.20.)

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Right cot, right place, right time: improving the design and organisation of neonatal care networks – a computer simulation study.

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Chapter 5What is discrete event simulation, and why use it?

Discrete event simulation (DES) is a method of simulating the behaviour and performance of a real-life process, facility or system. DES is being used increasingly in health-care services2426 and the increasing speed and memory of computers has allowed the technique to be applied to problems of increasing size and complexity. DES models the system as a series of ‘events’ [e.g. a birth, a stay in an intensive care unit (ICU), a transfer or a discharge] that occur over time. DES assumes no change in the system between events. In DES, patients are modelled as independent entities each of which can be given associated attribute information. In the case of neonatal simulation this may include parameters such as gestational age or weight at birth, hospital of birth, singleton/twin and current location. The information may be modified as time runs in the simulation model (e.g. the location will be changed depending on the status of the units in the network, and the level of care being received will be modified as the infant progresses). The simulation also accounts for resources. In the neonatal model the key resources are cots (with the highest level of care for each cot specified) and nurses. In order to care for an infant a unit must have the necessary cot and the necessary nursing staff (applying appropriate guidelines). The model allows each unit to work to a specified level of overcapacity regarding nursing, but will monitor the time each unit is undergoing overcapacity. DES models also allow for complex rules specifying where infants may be accepted; for example, there may be two ICUs, but with different facilities (e.g. surgery) or with different limits on gestational ages. DES thus allows complex decision logic to be incorporated that is not as readily possible in other types of modelling.

Simulation allows many ‘what if?’ scenarios to be tested. This allows decision-makers to test and better understand alternative ways in which a new policy may be best met.

Copyright © Queen’s Printer and Controller of HMSO 2015. This work was produced by Allen et al. under the terms of a commissioning contract issued by the Secretary of State for Health. This issue may be freely reproduced for the purposes of private research and study and extracts (or indeed, the full report) may be included in professional journals provided that suitable acknowledgement is made and the reproduction is not associated with any form of advertising. Applications for commercial reproduction should be addressed to: NIHR Journals Library, National Institute for Health Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UK.

Included under terms of UK Non-commercial Government License.

Bookshelf ID: NBK293948

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