Objectives: Health technology assessment (HTA) plays a central role in the coverage and reimbursement decision-making process for public health expenditure in many countries, including Thailand. However, there have been few attempts to quantitatively understand the benefits of using HTA to inform resource allocation decisions. The objective of this research was to simulate the expected net monetary benefit (NMB) from using HTA-based decision criteria compared to a first-come, first-served (FCFS) approach using data from Thailand.
Methods: A previously published simulation model was adapted to the Thai context which aimed to simulate the impact of using different decision-making criteria to adopt or reject health technologies for public reimbursement. Specifically, the simulation model provides a quantitative comparison between an HTA-based funding rule and a counterfactual (FCFS) funding rule to make decisions on which health technologies should be funded. The primary output of the model was the NMB of using HTA-based decision criteria compared to the counterfactual approach. The HTA-based decision rule in the model involved measuring incremental cost-effectiveness ratios against a cost-effectiveness threshold. The counterfactual decision rule was a FCFS (random) selection of health technologies.
Results: The HTA-based decision rule was associated with a greater NMB compared to the counterfactual. In the investigated analyses, the NMB ranged from THB24,238 million (USD725 million) to THB759,328 million (USD22,719 million). HTA-based decisions led to fewer costs, superior health outcomes (more quality-adjusted life-years).
Conclusions: The results support the hypothesis that HTA can provide health and economic benefits by improving the efficiency of resource allocation decision making.
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