Cost-effectiveness
A decision-tree model was used to estimate the incremental cost-effectiveness of replacing the NICE screening method with the FMF screening method. This model was applied to the cohort of pregnant women outlined above. The maternal and pregnancy characteristics of the included cohort are presented in Table 1. Model pathways for each screening outcome were defined based on initial screening test result, prescription of aspirin, rates of PE, and rates of preterm PE. The model structure is outlined in Figure S1.
All transition probabilities were calculated based on the statistical analysis of primary data described above. Aspirin prescription rates were based on observed data for the NICE screening method and based on scientific literature for the FMF screening method.9Aspirin patient adherence was not accounted for in the model due to the retrospective nature of the study.
Health outcomes were expressed for the mother only in terms of quality-adjusted life-years (QALYs). The prevalence of health events of interest was based on primary data, while health utility values were based on available secondary data. All relevant inputs for the calculation of QALYs are outlined in Table 2.
Costs were estimated from the provider perspective and included the costs of the PE screening, third trimester ultrasound for fetal growth surveillance, aspirin prophylaxis, delivery costs, the postpartum stay of the mother and the baby, the costs of stillbirth and admission of a preterm neonate to NICU. Again, relevant probabilities were based on primary data, while unit costs were based on the NHS England 2022/23 National Tariff Workbook and the British National Formulary. Unit cost inputs are provided in Table S1.
Incremental cost-effectiveness ratios were estimated to represent the additional cost per QALY gained from adopting the FMF screening algorithm. A probabilistic sensitivity analysis was also conducted, where variation in parameters was simultaneously modelled based on assumed distributions 1,000 times. Table S1 shows the parameters varied in the sensitivity analysis. All costs are reported in 2022 British Pounds. All cost-effectiveness analysis was conducted in R using the “rdecision” package.