Artificial Intelligence Distributionally Robust Optimisation of Maternal Blood Product Reservation Under Variable Placental Abruption Presentation Volatility: A computed Healthcare Haemorrhage Preparedness Evaluation

Placental abruption is an obstetric emergency in which the volume of blood products required is unknown at the moment of reservation, and the distribution of that requirement shifts with presentation severity, referral patterns and institutional case mix. the present analysis formulates maternal blood product reservation as a distributionally robust optimisation problem over an ambiguity set of haemorrhage-severity distributions, and evaluates the resulting reservation policy against a nominal stochastic benchmark within a computed haemorrhage-preparedness environment. The formulation couples a two-stage decision structure, in which reservations are committed before presentation and recourse transfusions are drawn after, with a Wasserstein ambiguity set whose radius is calibrated to the volatility of abruption presentation. A before-after-control-impact design was used to characterise the operating characteristics of the evaluation under a declared variance structure with between-cluster standard deviation 6.0, residual standard deviation 4.5 and intraclass correlation 0.64; power was estimated across 2000 replications per design cell for cluster counts of 8, 16, 24 and 32 and effect sizes of 3, 5 and 8 percentage points. The analysis is methodological and replication-based: no observational patient data were used, and the reported quantities are design operating characteristics rather than clinical estimates. The contribution is a formal bridge between distributionally robust optimisation and obstetric haemorrhage preparedness, together with a transparent account of the design conditions under which such a policy can be distinguished from its nominal counterpart.