Towards effective capacity planning in a perinatal network centre
Md Asaduzzaman1, Thierry J Chaussalet, Shola Adeyemi
1Department of Information Systems and Computing, University of Westminster, London W1W 6UW, UK.
Summary
Neonatal intensive care unit (NICU) capacity planning can be improved using a queuing model. Reducing length of stay (LoS) by two days could increase admission acceptance by 8%.
Area of Science:
- Neonatal care
- Healthcare management
- Queuing theory
Background:
- Neonatal intensive care/high dependency units (NICU/HDUs) and special care baby units (SCBUs) face capacity challenges.
- Understanding patient flow and length of stay (LoS) is crucial for effective resource allocation.
Purpose of the Study:
- To analyze neonatal unit admission patterns and LoS.
- To assess the impact of capacity shortages on neonatal care.
- To develop an analytical model for optimizing perinatal center capacity planning.
Main Methods:
- Utilized data from the South England Neonatal Database (SEND) and North Central London Perinatal Network Transfer Audit (2006).
- Performed exploratory data analysis on neonate admissions and refusals at University College London Hospital (UCLH).
- Proposed a queuing model for capacity planning in perinatal network centers.
Main Results:
- In 2006, UCLH admitted 1002 neonates but refused 144 to NICU and 35 to SCBU.
- The queuing model indicated a need for seven additional NICU cots to achieve 90% admission acceptance.
- Reducing LoS by two days could improve admission acceptance rates by 8%.
Conclusions:
- Gestational age (<27 weeks), arrival, LoS, and discharge patterns significantly influence neonatal unit capacity.
- The developed queuing model provides a tool for determining cot capacity based on desired admission rejection tolerance.
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