Abstract
OBJECTIVE: To analyse the impact of selected neonatal care interventions on regional care capacity.DesignDiscrete 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.