Center for Health System Sustainability

The United States spends more on health care than any other country, yet its fragmented financing structure masks the full financial burden that individuals bear through taxes, premiums, and out-of-pocket payments. A sizeable number of people contribute to the health care financing of others while they themselves remain uninsured. This cross-sectional study used 2023 Current Population Survey Annual Social and Economic Supplement data to quantify health care contributions among US tax filers, by income quintile, payment type, and sociodemographic characteristics. Although total contributions were higher at each successive income quintile, out-of-pocket spending fell disproportionately on lower-income and sicker people. Uninsured tax filers younger than age sixty-five contributed approximately 64 percent of what their insured counterparts paid, despite lacking coverage. Virtually all tax filers contributed to US health care financing through its public financing streams, yet many remained exposed to significant financial risk or lacked coverage altogether. This reflects the fragmented structure of US health care financing, where financial contributions are not aligned with coverage or protection from medical costs.

Health systems face financial pressures as populations age and economic growth slows, with implications for who pays for health care and for what drives expenditure growth.

For more than two decades, debates about why US health care spending is so high have been shaped by the insight articulated by Gerard Anderson, Uwe Reinhardt, and Peter Hussey: that the United States does not use more health care than other high-income countries but pays much higher prices for it. The original “It’s the Prices, Stupid” argument was fundamentally about price levels, not price growth. That central insight remains as true today as when it was first articulated: across services, drugs, and inputs, the United States consistently pays substantially higher prices than its peers for comparable services, drugs, and inputs.

Background: The Global Fund to Fight AIDS, Tuberculosis, and Malaria is one of the world’s largest global health donor agencies, playing a key role by filling recipient countries’ domestic health financing gaps; however, little is known about how well it achieves value for money. Given the current uncertainty regarding global health development assistance, it is critical to understand how to prioritize external donor funding allocations in an effort to maximize health impact.

Methods: In this study, we evaluated 66 recipient countries’ efficiency relative to peers in achieving improvement in health outcomes for TB, malaria, and HIV given their 2017–2019 Global Fund expenditures for (1) health products, (2) program activities, and (3) program management. Using a combination of frontier analysis, linear regression, and cluster analysis, we examined how macroeconomic conditions, epidemiological context, health system factors, and Global Fund spending decisions explain variation in country program performance.

Results: For malaria and HIV, we found a negative relationship between Global Fund spending on program activity and health product costs respectively and countries’ efficiency at translating funds to health impact. For malaria and HIV, there was also significant variation in efficiency across countries according to their economic capacity, disease burden, and most prominent spending area.

Conclusions: Our results suggest possible structural inefficiencies in country program management, dampening the health impact of frontline programs. The lack of broad patterns to predict performance signals the importance of tailoring spending strategies to country-specific contexts.

Researchers and policy-makers have long compared health system performance. International comparisons raise awareness of health systems’ relative strengths and shortcomings, prompting policy debates and informing policy decisions. Yet determining how these international comparisons can be used to improve health system performance is challenging. Health systems can differ in many ways, including how they are governed, how they are funded, how they generate and deploy resources, and how they deliver services. While the international health community widely agrees that these functions influence health system performance, understanding of how much they matter, which ones matter most, and how they are affected by the context in which they operate remains limited. To gain relevant and meaningful insights from health systems comparisons that offer lessons for policy, we must agree on how to compare health systems. In this article, we argue that doing so requires collecting better, more granular data on a broad range of health system characteristics and using those data to choose the most appropriate health system comparators.