Total factor productivity growth and spatial–temporal evolution of China’s health system: a three-stage DEA-Malmquist approach

In recent years, the deepening of healthcare reform in China has raised high demands for the accurate measurement of hospital total factor productivity (TFP), where existing systems often overstate performance by neglecting social welfare. This study constructs a novel evaluation framework incorporating medical quality and safety, analyzing input–output data from 31 Chinese provinces (2012–2022) using a three-stage DEA-Malmquist model under traditional and improved scenarios. It identifies significant divergence between the two perspectives and reveals the impact of external shocks like the COVID-19 pandemic. The core findings are that TFP is markedly overestimated by conventional methods, the Technological Progress (TC) index is the primary driver of this decline, and the pandemic has exposed systemic vulnerabilities by interrupting technological momentum. Future research and policy practice should focus on coordinating the deployment of medical technology with its broader social impacts, clarifying the pathways for high-quality development, and promoting regular TFP assessments that incorporate undesirable outputs.