Supporting evidence-informed policy: a multidimensional impact analysis of health technology assessment in Thailand.

Introduction: Health Technology Assessment (HTA) is widely used for evidence-informed priority setting in Thailand and has been integrated into pharmaceutical reimbursement decision-making through the National List of Essential Medicines (NLEM). However, its broader contributions have not been systematically assessed. Methods: We retrospectively analyzed 68 completed economic evaluations conducted between 2010 and 2018 using an adapted Payback Framework across five dimensions of impact: informing policy, knowledge production, capacity building, health sector benefit, and an economic dimension assessed separately for approved and rejected items using Net Monetary Benefit (NMB). Results: The principal finding concerns the economic dimension. Among 21 approved technologies, 12 (57.1%) had negative NMB at the national cost-effectiveness threshold, suggesting that adoption would not have been supported on cost-effectiveness grounds alone. Nevertheless, each of these approvals included a structured non-cost-effectiveness justification in committee deliberations, all of which mapped to recognized multi-criteria decision analysis domains, including severity, unmet clinical need, rarity, lack of alternatives, and standard-of-care positioning. This provides empirical evidence that deliberative multi-criteria reasoning operates in routine reimbursement practice in an institutionalized LMIC HTA-to-reimbursement pathway. Among 47 rejected items, 85.1% had positive modeled NMB under a non-adoption sign convention, indicating that non-adoption was consistent with efficient resource use at the threshold. The four categorical dimensions, on a 0-4 ordinal scale, characterized the cohort along complementary axes: informing policy (mean 3.34), health sector benefit (mean 2.54), capacity building (mean 1.97), and knowledge production (mean 1.87). Discussion: These findings suggest that HTA in Thailand contributes to disciplined, transparent multi-criteria priority setting. Aggregate NMB was concentrated in a few large-population, lifetime-horizon studies (14 accounting for 93.6% of the lifetime-horizon total), best interpreted as a descriptive summary rather than a uniform signal. The analytic approach may other insights for other low- and middle-income countries institutionalizing HTA within structured reimbursement systems.