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An overflow loss network model for capacity planning of a perinatal network
Author(s) -
Asaduzzaman Md,
Chaussalet Thierry J.
Publication year - 2011
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/j.1467-985x.2010.00669.x
Subject(s) - computer science , markov chain , decomposition , network model , basis (linear algebra) , unit (ring theory) , state (computer science) , mathematics , artificial intelligence , algorithm , machine learning , mathematics education , biology , ecology , geometry
Summary. A model framework is developed to solve capacity planning problems that are faced by many perinatal networks in the UK. We propose a loss network model with overflow based on a continuous time Markov chain for a perinatal network with specific application to a network in London. We derive the steady state expressions for overflow and rejection probabilities for each neonatal unit of the network on the basis of a decomposition approach. Results obtained from the model are very close to observed values. Using the model, decisions on numbers of cots can be made for specific levels of admission acceptance probabilities for each level of care at each neonatal unit of the network and specific levels of overflow to temporary care.