Re-evaluating "Pro-Poor": a model for monitoring of the universal coverage scheme in Thailand

Abstract

The Nation of Thailand, which had a GDP per capita of approximately $6,600 (PPP) at the time and was still struggling to recover from the crippling effects of the Asian Financial Crisis, was able to implement a universal coverage program for its citizens with a fairly comprehensive benefits package in 2001. However, the current system for universal health coverage in Thailand is a patchwork of 3 separate and unequal public health insurance schemes. Given the inequity in the Thai health system that preceded the Universal Coverage Scheme, monitoring of the program for pro-poor qualities is a critical aspect of ensuring that the Scheme meets its goal of providing universal access to high-quality healthcare for all. The primary objective of this research was to construct a conceptual model for pro-poor monitoring of the Universal Coverage Scheme based upon survey of frontline stakeholders, key informant interview, participant observation, review of health system data, and a theoretical framework based on development and sociological concepts rather than the more heavily emphasized quantitative health economic analytics. The results of the research appear to show that pro-poor monitoring indicators should be expanded beyond quantitative economic measures. Although the research did indicate that UC Scheme stakeholders are concerned about economic impacts and characteristics, it also revealed their strong concerns with heavy staff workloads, underfunding of services, and quality of care provided. While the health economic evaluations of the Scheme have accentuated the successful shift of the financial burden of care from the poor, they have been less revealing about the fact that much of that burden has fallen on public health facilities and their staff. In addition, there are no econometric indicators appropriate for determining the value of receiving high quality care when medically necessary. The results appear to indicate that additional metrics should be included in the monitoring model to help address these issues.