Objective To systematically analyze the research landscape of China’s rehabilitation industry, identify core contradictions and evolutionary pathways, and provide evidence for policy optimization and academic innovation. Methods Literature published up to December 31, 2024 was retrieved from China National Knowledge Infrastructure, Wanfang, and Chongqing VIP databases using rehabilitation industry as the subject term. Bibliometric methods such as keyword clustering, strategic coordinate analysis, temporal evolution (CiteSpace and R language) were employed to dissect research patterns, hotspot evolution, and innovation bottlenecks of the rehabilitation industry. Results Finally, 183 articles were included for analysis. China’s rehabilitation research exhibits a policy-driven, fragmented pattern (policy-focused journals accounted for 25.68% of publications; the Ministry of Civil Affairs had the highest publication volume, accounting for 2.19%. There was a structural disconnect between demand and research: on the one hand, the outbreak of elderly rehabilitation demand was marginalized in research (located in the lower left quadrant of the strategic coordinates, but keyword clustering dissolved in the “# 0 rehabilitation industry”); on the other hand, although exercise rehabilitation was a hot topic (ranked first in frequency, centrality>0.1), its maturity was insufficient (located in the lower right quadrant of the strategic coordinates). The research hotspots continued to shift towards “integration of industry and education” and “high-quality development” (temporal evolution), with the emergence of the term “rehabilitation” (strength=4.09) marking a historical focus, while technology transformation and collaboration in the public welfare market (isolation of the language rehabilitation industry) had become key breakthrough directions. Conclusion The rehabilitation industry in China urgently needs to break the dilemma of “high yield and low cooperation”, promote research and practice collaboration through three-dimensional innovation of technology education system, and support the rehabilitation needs of an aging society.
Objective To evaluate the pathways for improving the operational efficiency of medical teams, thereby providing micro-level empirical evidence for the refined management and high-quality development of public hospitals. MethodsBased on panel data from nine surgical teams in the Department of Thoracic Surgery at Sichuan Cancer Hospital from 2021 to 2024, this study employed the data envelopment analysis (DEA) with the BCC model to assess static efficiency, including technical efficiency (TE), scale efficiency (SE), and overall efficiency (OE). The Malmquist index was used to analyze the dynamic total factor productivity (TFP) and its decomposition into efficiency change (EC) and technology change (TC). Input indicators were the number of physicians and the number of open beds. Output indicators included the proportion of surgical patients, the proportion of grade Ⅳ surgeries, and the average length of stay (reciprocally transformed for positive orientation). Results The mean OE of all medical teams showed a continuous upward trend, while the mean SE exhibited a “V-shaped” pattern, initially decreasing and then increasing. The most significant growth was observed in mean TE, which was the primary driver of the OE improvement. All medical teams achieved positive TFP growth, with TC values greater than 1.000 across all teams, indicating that technological innovation was the core engine of efficiency enhancement. However, EC showed a divergent trend among the teams. Conclusion Public hospital performance appraisal policies effectively guide technological upgrading of medical teams through indicators such as “proportion of discharged patients undergoing surgery” and “proportion of grade Ⅳ surgeries”. However, issues of hospital resource mismatch and SE differentiation persist. It is necessary to establish specialized operation groups for dynamic resource monitoring and construct a “technological upgrading, scale adaptation, and management innovation” triangular balanced system to achieve a sustainable mechanism for maximizing healthcare resource input-output.