Ensuring neonatal human milk provision: A framework for estimating potential demand for donor human milk

Abstract

Using donor human milk (DHM) for preterm infants, where the mother's milk is unavailable, protects infants against potentially fatal necrotising enterocolitis. When used optimally, DHM can support mothers to establish breastfeeding. Understanding the relationship between clinical choices for DHM provision and the resulting demand is important. For policymakers, it informs decision-making around the provision of DHM based on cost-benefit analyses. For milk banks, it helps plan for required capacity, donor recruitment and supply-side collections. This study presents a framework for estimating DHM potential demand for infants born preterm, which allows for various sources of secondary population data, different feeding protocols and policy options for DHM provision. A Monte Carlo Simulation (MCS) is developed which follows the framework, simulating annual births (based on historical data) and incorporating uncertainty related to infant and maternal populations. A case study on human milk banking serves as the basis for the application of the framework and the modelling approach. Our model estimates the overall demand for DHM in England and Wales, the local level demand for NHS Trusts in England and provides an indication of the associated uncertainties. Our study provides a useful tool to enrich the strategic and operational level decision-making environment, benefitting both policymakers and milk bankers by providing a better understanding of the impact of policy decisions on the future development of the milk bank infrastructure.