BACKGROUND: The Kingdom of Saudi Arabia (KSA) has embarked on a Health Sector Transformation Program as part of the Kingdom's Vision 2030 initiatives with the facilitation of access to healthcare services for the millions in KSA with diabetes an essential part of the Program. Decision-making tools, such as budget impact models, are required to consider the addition of new medications like oral semaglutide that have multifaceted health benefits and address barriers related to therapeutic inertia to reduce diabetes-related complications.
OBJECTIVE: To determine the financial impact of the introduction of oral semaglutide as a treatment option for people with type 2 diabetes mellitus (T2DM) in KSA.
METHODS: From the public payer's perspective, the budget impact model estimates the costs before and after the introduction of oral semaglutide over a 5-year time horizon. The budget impact of introducing oral semaglutide (primary comparator) compared with three different classes of diabetes medicines: glucagon-like peptide-1 receptor agonists (GLP-1), sodium-glucose transport protein 2 inhibitors (SGLT 2i) and dipeptidyl peptidase 4 inhibitors (DDP-4i) have been calculated based on the projected market shares. The model includes the cost of care through the incorporation of health outcomes that have an impact on the national payer's budget in Saudi Riyals (SAR).
RESULTS: The budget impact over the five-year time horizon indicates a medication cost increase (17,424,788 SAR), and cost offsets which include a difference in diabetes management costs (-3,625,287 SAR), CV complications costs (-810,733 SAR) and weight loss savings of 453,936 SAR. The cumulative total cost difference is 12,427,858 SAR (0.66%).
CONCLUSION: The introduction of oral semaglutide 14 mg as a second-line treatment option after metformin is indicated as budget-neutral to slightly budget-inflating for the public pharmaceutical formulary of KSA. The price difference is offset by positive health outcomes and costs. This conclusion was confirmed through a probabilistic sensitivity analysis.