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Mathematical modelling and simulation for planning critical care capacity

Mathematical modelling and simulation for planning critical care capacity
Mathematical modelling and simulation for planning critical care capacity
Using average number of patients expected in a year, average length of stay and a target occupancy level to calculate the number of critical care beds needed is mathematically incorrect because of nonlinearity and variability in the factors that control length of stay. For a target occupancy in excess of 80%, this simple calculation will typically underestimate the number of beds required.
More seriously, it provides no quantitative guidance information about other aspects of critical care demand such as the numbers of emergency patients transferred, deferral rates for elective patients and overall utilisation. The combination of appropriately analysing raw data and detailed mathematical modelling provides a much better method for estimating numbers of beds required. We describe this modelling approach together with evidence of its performance.
intensive care: organisation and administration, trends, utilisation
0003-2409
320-327
Costa, A.X.
3db9ec2e-4a0c-4310-b9e1-d0c1cb21e66f
Ridely, S.A.
2759ad1e-2aba-4036-b179-db5920cef0c4
Shahani, A.K.
01f30d3f-6d62-4c19-8a3e-e4d223559dc7
Harper, P.R.
e9853fed-d08b-4041-8d1e-c170fb1949f7
De Senna, V.
97754892-ac68-4e10-bacc-499275c22b39
Nielsen, M.S.
b1d9bdb4-7251-49fb-8b98-9b87e1d5bce5
Costa, A.X.
3db9ec2e-4a0c-4310-b9e1-d0c1cb21e66f
Ridely, S.A.
2759ad1e-2aba-4036-b179-db5920cef0c4
Shahani, A.K.
01f30d3f-6d62-4c19-8a3e-e4d223559dc7
Harper, P.R.
e9853fed-d08b-4041-8d1e-c170fb1949f7
De Senna, V.
97754892-ac68-4e10-bacc-499275c22b39
Nielsen, M.S.
b1d9bdb4-7251-49fb-8b98-9b87e1d5bce5

Costa, A.X., Ridely, S.A., Shahani, A.K., Harper, P.R., De Senna, V. and Nielsen, M.S. (2003) Mathematical modelling and simulation for planning critical care capacity. Anaesthesia, 58 (4), 320-327. (doi:10.1046/j.1365-2044.2003.03042.x).

Record type: Article

Abstract

Using average number of patients expected in a year, average length of stay and a target occupancy level to calculate the number of critical care beds needed is mathematically incorrect because of nonlinearity and variability in the factors that control length of stay. For a target occupancy in excess of 80%, this simple calculation will typically underestimate the number of beds required.
More seriously, it provides no quantitative guidance information about other aspects of critical care demand such as the numbers of emergency patients transferred, deferral rates for elective patients and overall utilisation. The combination of appropriately analysing raw data and detailed mathematical modelling provides a much better method for estimating numbers of beds required. We describe this modelling approach together with evidence of its performance.

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More information

Published date: 2003
Keywords: intensive care: organisation and administration, trends, utilisation
Organisations: Operational Research

Identifiers

Local EPrints ID: 29692
URI: https://eprints.soton.ac.uk/id/eprint/29692
ISSN: 0003-2409
PURE UUID: 773fc407-c29b-48d8-9544-a59dc0bc2a11

Catalogue record

Date deposited: 12 May 2006
Last modified: 15 Jul 2019 19:08

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