Towards effective capacity planning in a perinatal network centre.
OBJECTIVE
To study the arrival pattern and length of stay (LoS) in a neonatal intensive care/high dependency unit (NICU/HDU) and special care baby unit (SCBU) and the impact of capacity shortage in a perinatal network centre, and to provide an analytical model for improving capacity planning.


METHODS
The data used in this study have been collected through the South England Neonatal Database (SEND) and the North Central London Perinatal Network Transfer Audit between 1 January and 31 December 2006 for neonates admitted and refused from the neonatal unit at University College London Hospital (UCLH). Exploratory data analysis was performed. A queuing model is proposed for capacity planning of a perinatal network centre.


METHODS
Predicted number of cots required with existing arrival and discharge patterns; impact of reducing LoS.


RESULTS
In 2006, 1002 neonates were admitted to the neonatal unit at UCLH, 144 neonates were refused admission to the NICU and 35 to the SCBU. The model shows the NICU requires seven more cots to accept 90% of neonates into the NICU. The model also shows admission acceptance can be increased by 8% if LoS can be reduced by 2 days.


CONCLUSIONS
The arrival, LoS and discharge of neonates having gestational ages of <27 weeks were the key determinants of capacity. The queuing model can be used to determine the cot capacity required for a given tolerance level of admission rejection.
Asaduzzaman
Md
M
Department of Information Systems and Computing, University of Westminster, London W1W 6UW, UK.
Chaussalet
Thierry J
TJ
Adeyemi
Shola
S
Chahed
Salma
S
Hawdon
Jane
J
Wood
Daniel
D
Robertson
Nicola J
NJ
D001509:Bed Occupancy / Q000706:statistics & numerical data; D005865:Gestational Age; D015276:Health Care Rationing / Q000458:organization & administration; D006285:Health Planning / Q000379:methods*; D006302:Health Services Research / Q000379:methods; D006801:Humans; D007231:Infant, Newborn; D007363:Intensive Care Units, Neonatal / Q000458:organization & administration* / Q000706:statistics & numerical data; D007902:Length of Stay / Q000706:statistics & numerical data; D008131:London; D017146:Models, Organizational; D020380:Needs Assessment / Q000458:organization & administration; D010351:Patient Discharge / Q000706:statistics & numerical data; D012621:Seasons