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

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.

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).

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).

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.