A Generalized Loss Network Model with Overflow for Capacity Planning of a Perinatal Network

TL;DR

This paper introduces a generalized loss network model for capacity planning in perinatal networks, enabling accurate estimation of required cots by analyzing overflow and rejection probabilities with a two-moment approximation.

Contribution

It develops a flexible, generalized model for perinatal network capacity planning that accounts for overflow and rejection, applicable to various network configurations.

Findings

Derived expressions for rejection and overflow probabilities.

Estimated the number of cots needed based on model predictions.

Validated the model's applicability to different perinatal networks.

Abstract

We develop a generalized loss network framework for capacity planning of a perinatal network in the UK. Decomposing the network by hospitals, each unit is analyzed with a GI/G/c/0 overflow loss network model. A two-moment approximation is performed to obtain the steady state solution of the GI/G/c/0 loss systems, and expressions for rejection probability and overflow probability have been derived. Using the model framework, the number of required cots can be estimated based on the rejection probability at each level of care of the neonatal units in a network. The generalization ensures that the model can be applied to any perinatal network for renewal arrival and discharge processes.