The research team, led by Minting Huang of Aerospace Center Hospital in Beijing and Lau Nga Wun of Macao Polytechnic University, assembled a provincial panel covering all 31 of China’s province-level jurisdictions across the full twenty-year window. Rather than relying on a single analytical lens, they deployed a multi-method framework in which each tool answered a distinct question. A data envelopment analysis combined with the Malmquist index, known as DEA-Malmquist, measured how efficiently provinces converted healthcare inputs into services over time and whether changes came from technological improvement or from catching up to best practice. The Dagum Gini coefficient decomposed inequality in allocation outcomes to reveal where spatial disparities actually originated. Finally, a GM(1,1) grey prediction model, a technique designed for forecasting with limited data, projected future trajectories of supply and demand. Treating efficiency and equity as related but independent dimensions, the design allowed the authors to track each separately across a period that included both deepening healthcare system reforms and the shocks of public health emergencies.

The efficiency findings carry the sharpest edge. Total factor productivity in healthcare allocation is a ratio-style measure: when it exceeds 1, the system is producing more health services per unit of beds, personnel and expenditure than it did before; when it falls below 1, growth in inputs is outpacing growth in outputs. The study found the index fluctuating downward across the two decades, and critically, it identified the technological progress component, abbreviated Techch, as the weak link, with a value of 0.929 indicating an average annual shrinkage of the technology frontier of more than 7 percent in the periods where it declined. In efficiency analysis, this frontier represents the best achievable performance given current knowledge and practice. When the frontier itself contracts rather than expands, no amount of managerial effort by individual provinces can fully compensate, because the ceiling of what is possible is dropping.

Geography mattered enormously. The analysis revealed a regional heterogeneity best summarized as high in the East, low in the West, with the technological change gap between the eastern provinces and the rest of the country statistically distinguishable under province-level bootstrap testing, a resampling technique that guards against the possibility that observed differences are artifacts of small sample sizes. Perhaps more telling was where decreasing returns to scale concentrated: in the richer regions. In production theory, decreasing returns to scale means that adding inputs yields progressively smaller output gains, a signal that simply building more capacity no longer pays off. The fact that this pattern clustered in China’s wealthiest, most resource-dense provinces suggests that scale expansion there has reached a point of diminishing returns, and that further growth in those areas requires new technology and better organization rather than more beds.

The equity analysis told a more nuanced story. Using the Dagum Gini coefficient, a decomposition method that splits overall inequality into within-region, between-region, and trans-variation density components, the researchers examined inequality in the provincial productivity change measure itself. Trans-variation density, which captures the degree to which regional distributions overlap rather than sit cleanly apart, has long dominated the decomposition, contributing 52.96 percent of overall inequality in 2022. The authors caution that this overlap reflects one of several possible sources of disparity, but they identify the gradient gap between the Eastern and Western provinces as the root cause of overall inequality. In other words, the deepest fault line in Chinese healthcare productivity runs between the wealthy coastal belt and the interior, even as the distributions of individual provinces blur across regional boundaries.

Interestingly, the study’s conclusions note a divergence between two kinds of equity. Inequality in physical resources per head, such as beds and staff relative to population, declined over the study period, indicating genuine progress in distributing the hardware of healthcare more evenly across the country. Yet inequality in productivity change did not decline, meaning that even as provinces converged in what they possess, they diverged in how effectively they converted those resources into services. This distinction matters for policy because it implies that the remaining inequity is not primarily about where the buildings and machines are, but about the human capital, management practices, and technological adoption that determine what those assets actually deliver to patients.

The forecasting component adds a financial warning sign. The GM(1,1) grey prediction model projects that healthcare resource supply will continue expanding, but that the average hospitalization cost per visit would reach approximately 15,587 CNY in nominal terms by 2029, based on an illustrative extrapolation of the 2003 to 2022 trend. The authors frame this as pointing to a risk of rigid growth in government health expenditure, a scenario in which costs climb steadily regardless of efficiency gains, squeezing public budgets. For a system serving 1.4 billion people and aging rapidly, the gap between expanding supply and rising unit costs is precisely the combination that strains fiscal sustainability.

The authors are careful about what their study can and cannot claim. They describe the work as a descriptive assessment and explicitly state that it does not identify causal effects. The Malmquist framework measures changes in relative performance against a shifting frontier, not the impact of any specific reform or event. Still, the patterns they document point toward identifiable directions for policy. The study indicates frontier-expanding investment, meaning spending aimed at pushing out the technological frontier rather than merely adding capacity, alongside scale consolidation in provinces operating under decreasing returns to scale. It also points to cross-regional coordination to address the East-West gradient and to value-based payment reform, which ties reimbursement to outcomes rather than volume, as directions suggested by the observed patterns.

Beyond China, the findings speak to a dilemma facing many developing countries. The conventional development playbook is to build capacity fast: more hospitals, more beds, more staff. China executed that playbook at extraordinary scale over two decades, and by the measure of physical resources per person, it narrowed gaps between regions. But the study suggests that the playbook has a shelf life. Once resource stocks are broadly in place, further progress depends on the harder, less visible work of technological diffusion, institutional design and payment incentives, and those dimensions showed no such convergence. A country can equalize what it owns while still unequal in what it achieves.

The timing of the productivity slowdown, with the index below 1 from 2018 through 2022, spans both the later phase of China’s healthcare reforms and the COVID-19 pandemic years, though the descriptive design cannot attribute the decline to either. What the data do establish is a clear empirical baseline: a system whose input growth has outrun its output growth, whose technological frontier has been contracting, whose deepest inequality follows an East-West gradient rooted in productivity change rather than resource counts, and whose costs are projected to keep rising into the next decade. For policymakers in Beijing and for health economists watching from abroad, the study reframes the central question of Chinese healthcare from how much the system has, to how well it uses what it has. The answer, on current evidence, is not yet well enough, and the trajectory suggests that the next two decades will demand a fundamentally different kind of investment than the last two.

Subject of Research: Efficiency and equity of healthcare resource allocation across Chinese provinces from 2003 to 2022

Article Title: Efficiency, equity, and future trajectories of healthcare resource allocation in China: a multi-method provincial panel analysis, 2003–2022

Article References: Huang, M., Wun, L. N., Huang, S., Wu, J., Deng, T., Gong, H., Wang, Q., & Wu, Z. (2026). Efficiency, equity, and future trajectories of healthcare resource allocation in China: a multi-method provincial panel analysis, 2003–2022. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15751-0

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15751-0

Keywords: healthcare resource allocation, China, total factor productivity, DEA-Malmquist index, Dagum Gini coefficient, grey prediction model, regional disparity, health equity, health economics, health policy, provincial panel data, hospital costs