Assessing resource allocation based on workload: a data envelopment analysis study on clinical departments in a class a tertiary public hospital in China.

OBJECTIVE: Today, the development mode of public hospitals in China is turning from expansion to efficiency, and the management mode is turning from extensive to refined. This study aims to evaluate the efficiency of clinical departments in a Chinese class A tertiary public hospital (Hospital M) to analyze the allocation of hospital resources among these departments providing a reference for the hospital management. METHODS: The hospitalization data of inpatients from 32 clinical departments of Hospital M in 2021 are extracted from the hospital information system (HIS), and a dataset containing 38,147 inpatients is got using stratified sampling. Considering the non-homogeneity of clinical departments, the 38,147 patients are clustered using the K-means algorithm based on workload-related data labels including inpatient days, intensive care workload index, nursing workload index, and operation workload index, so that the medical resource consumption of inpatients from non-homogeneous clinical departments can be transformed into the homogeneous workload of medical staff. Taking the numbers of doctors, nurses, and beds as input indicators, and the numbers of inpatients assigned to certain clusters as output indicators, an input-oriented BCC model is built named the workload-based DEA model. Meanwhile, a control DEA model with the number of inpatients and medical revenue as output indicators is built, and the outputs of the two models are compared and analyzed. RESULTS: Clustering of 38,147 patients into 3 categories is of better interpretability. 14 departments reach DEA efficient in the workload-based DEA model, 10 reach DEA efficient in the control DEA model, and 8 reach DEA efficient in both models. The workload-based DEA model gives a relatively rational judge on the increase of income brought by scale expansion, and evaluates some special departments like Critical Care Medicine Dept., Geriatrics Dept. and Rehabilitation Medicine Dept. more properly, which better adapts to the functional orientation of public hospitals in China. CONCLUSION: The design of evaluating the efficiency of non-homogeneous clinical departments with the workload as output proposed in this study is feasible, and provides a new idea to quantify professional medical human resources, which is of practical significance for public hospitals to optimize the layout of resources, to provide real-time guidance on manpower grouping strategies, and to estimate the expected output reasonably.

Expression of Rab3b in Human Glioma: Influence on Cell Proliferation and Apoptosis.

BACKGROUND: Glioma is the most common human central nervous system tumour with a high degree of malignancy. Some Rab GTPases have significant effects on glioma. OBJECTIVE: This study aimed to investigate the effect of Rab3b (Rab GTPase3b) on human glioma cell proliferation and apoptosis by silencing Rab3b and to initially verify the value of Rab3b expression for the diagnosis and progression in human glioma. METHODS: Rab3b was silenced by siRNA transfection. Human glioma tissues and normal brain tissues adjacent to glioma were obtained by surgery. Rab3b, P53, Caspase 7, Bax, and Bim mRNA and protein expression levels were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting. Cell proliferation was detected by the cell counting kit-8 assay, and the cell cycle and apoptosis were analysed using flow cytometry. RESULTS: Rab3b mRNA and protein expression in human glioma U251 and U87 cells were significantly downregulated after Rab3b silencing. Rab3b silencing inhibited glioma cell proliferation by promoting cell cycle arrest and induced apoptosis by upregulating the expression of apoptosis-related proteins. Rab3b expression in human glioma (n = 33) was significantly higher than that in normal brain tissues adjacent to glioma (n = 15). In addition, Rab3b expression levels in high-grade gliomas (WHO III-IV, n = 19) were also significantly higher than those in low-grade gliomas (WHO I-II, n = 14). CONCLUSION: Rab3b expression levels are significantly related to the progression of gliomas. Moreover, Rab3b silencing not only significantly inhibits cell proliferation in gliomas via cell cycle arrest but also promotes cell apoptosis by upregulating the expression levels of apoptosis-related proteins; however these preliminary in vitro results warrant validation on in vivo studies.

Efficient management strategy of COVID-19 patients based on cluster analysis and clinical decision tree classification.

Early classification and risk assessment for COVID-19 patients are critical for improving their terminal prognosis, and preventing the patients deteriorate into severe or critical situation. We performed a retrospective study on 222 COVID-19 patients in Wuhan treated between January 23rd and February 28th, 2020. A decision tree algorithm has been established including multiple factor logistic for cluster analyses that were performed to assess the predictive value of presumptive clinical diagnosis and features including characteristic signs and symptoms of COVID-19 patients. Therapeutic efficacy was evaluated by adopting Kaplan-Meier survival curve analysis and cox risk regression. The 222 patients were then clustered into two groups: cluster I (common type) and cluster II (high-risk type). High-risk cases can be judged from their clinical characteristics, including: age > 50 years, chest CT images with multiple ground glass or wetting shadows, etc. Based on the classification analysis and risk factor analysis, a decision tree algorithm and management flow chart were established, which can help well recognize individuals who needs hospitalization and improve the clinical prognosis of the COVID-19 patients. Our risk factor analysis and management process suggestions are useful for improving the overall clinical prognosis and optimize the utilization of public health resources during treatment of COVID-19 patients.