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.