A four-stage DEA-based efficiency evaluation of public hospitals in China after the implementation of new medical reforms.

This study applied the non-parametric four-stage data envelopment analysis method (Four-Stage DEA) to measure the relative efficiencies of Chinese public hospitals from 2010 to 2016, and to determine how efficiencies were affected by eight factors. A sample of public hospitals (n = 84) was selected from Chongqing, China, including general hospitals and traditional Chinese medicine hospitals graded level 2 or above. The Four-Stage-DEA method was chosen since it enables the control of the impact of environment factors on efficiency evaluation results. Data on the number of staff, government financial subsidies, the number of beds and fixed assets were used as input whereas the number of out-patients and emergency department patients and visits, the number of discharged patients, medical and health service income and hospital bed utilization rate were chosen as study outputs. As relevant environmental variables, we selected GDP per capita, permanent population, population density, number of hospitals and number of available sickbeds in local medical institutions. The relative efficiencies (i.e. technical, pure technical, scale) of sample hospitals were also calculated to analyze the change between the first stage and fourth stage every year. The study found that Four-Stage-DEA can effectively filter the impact of environmental factors on evaluation results, which sets it apart from other models commonly used in existing studies

How do functional traits influence tree demographic properties in a subtropical monsoon forest?

Functional traits are good predictors of plant responses and adaptations to ever-changing environments. However, forecasting forest community dynamics is challenging because the relationships among different tree demographic properties (growth, mortality and recruitment) and how functional traits are associated with tree demography remain largely unknown. Here, in a 20-ha subtropical forest permanent plot, we quantified the rates of tree growth, mortality and recruitment across 53 dominant tree species (diameter at breast height; DBH ≥ 1 cm) from 2005 to 2020. Functional traits that are closely related to plant photosynthesis, nutrients, hydraulics and drought tolerance were measured. We found that tree growth rate (GR) varied independently from rates of tree mortality and recruitment. Hydraulic conductivity was positively correlated with GR (explaining 27% variation—the strongest relationship observed) whereas wood density was negatively correlated with GR. Leaf life span was negatively related to tree mortality. Species with high carbon assimilation rate, nutrient concentration and hydraulic conductivity had high recruitment rates. Leaf turgor loss point was unrelated to plant demography. Principal component analysis revealed that species with quick resource acquisition rates had high rates of growth and recruitment. Our results illustrate that the correlations among tree demographic properties were weak in this subtropical forest with monsoonal climate. Most notably, against expectations, there was no observed trade-off between growth and mortality. Individual functional traits explained up to 27% of each demographic rate. Variation in recruitment rate was aligned with traits indexing the leaf economic spectrum and also plant hydraulic variation. A better understanding of the role of disturbances on trait–demography relationships would help build a deeper and more nuanced understanding of the ecology of subtropical monsoon forests. Read the free Plain Language Summary for this article on the Journal blog