Impact assessment of neonatal care interventions on regional neonatal care capacity
A simulation study based on clinical data in the Netherlands
Josephine H.L. Wagenaar (Erasmus MC, TU Delft - DesIgning Value in Ecosystems)
Alexander Dietz (Student TU Delft)
Yilin Huang (TU Delft - System Engineering)
Irwin K.M. Reiss (Erasmus MC)
Jasper V. Been (Erasmus MC)
Jessie Spaan (Erasmus MC)
René F. Kornelisse (Erasmus MC)
Hendrik Rob Taal (Erasmus MC)
Saba Hinrichs-Krapels (TU Delft - Policy Analysis)
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Abstract
Objective To analyse the impact of selected neonatal care interventions on regional care capacity.
Design Discrete event simulation modelling based on clinical data.
Setting
Neonatal care in the southwest of the Netherlands, consisting of one
tertiary-level neonatal intensive care unit (NICU), four hospitals with
high-care neonatal (HCN) wards and six with medium-care neonatal (MCN)
wards.
Participants
44 461 neonates admitted to at least one hospital within the specified
region or admitted outside of the region but with a residential address
inside the region between 2016 and 2021.
Interventions
The impact of three interventions was simulated: (1) home-based
phototherapy for hyperbilirubinaemia, (2) oral antibiotic switch for
culture-negative early onset infection and (3) changing tertiary-level
NICU admission guidelines.
Main outcome measure
Regional neonatal capacity defined as: (1) occupancy per ward level,
(2) required operational beds per ward level to provide care to all
inside region patients at maximum 85% occupancy, (3) proportion
rejected, defined as outside region transfers due to no capacity to
provide local care and (4) the weekly rejections in relation to
occupancy to provide a combined analysis.
Results
In the current situation, with many operational beds closed due to
nurse shortages, occupancy was extremely high at the NICU and HCNs
(respectively 91.7% (95% CI 91.4 to 92.0) and 98.1% (95% CI 98.0 to
98.2)). The number of required beds exceeded available beds, resulting
in >20% rejections for both NICU and HCN patients. Although the three
interventions individually demonstrated effect on capacity, clinical
impact was marginal. In combination, NICU occupancy was reduced below
the 85% government recommendation at the cost of an increased burden for
HCNs, highlighting the need for redistribution to MCNs.
Conclusion
Our model confirmed the severity of current neonatal capacity strain
and demonstrated the potential impact of three interventions on regional
capacity. The model showed to be a low-cost and easy-to-use method for
regional capacity impact assessment and could provide the basis for
making informed decisions for other interventions and future scenarios,
supporting data-driven neonatal capacity planning and policy
development.
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