Efficiency assessment and demand forecasting in China’s primary healthcare system: a comprehensive SBM-DDF-GML analysis

Background: With the serious aging of society, the demand for high-quality primary healthcare has increased. However, inadequate primary healthcare capacity and suboptimal resource allocation are hindering its development. Consequently, establishing a comprehensive and scientific evaluation system for the efficiency of primary healthcare plays a crucial role. Methods: Based on the perspective of measuring the input-output efficiency of primary healthcare, this study identifies the potential number of unreasonable hospitalizations and proposes a comprehensive method combining the Slacks-Based Measure, Directional Distance Function, and Global Malmquist-Luenberger (SBM-DDF-GML) to conduct static and dynamic efficiency analyses of primary healthcare institutions across China from 2010 to 2022. Additionally, we forecast future primary healthcare demand using a random forest model. Results: From 2010 to 2022, the average SBM-DDF efficiency score of China's primary healthcare institutions was 0.92. During this period, the eastern and western regions demonstrate higher average efficiency values compared to the central areas, which reflects regional imbalances. Furthermore, demand forecasts suggest that primary healthcare demand will rise by 2029. with projected outpatient visits reaching 1.07 billion. Conclusion: Given persistent regional disparities, strengthening regional collaboration, and optimizing resource distribution may provide valuable insights for policymakers. These measures will help bridge efficiency gaps and ensure equitable healthcare delivery.