Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Urine carries rich information of human metabolism, while urine examination facilitates the diagnosis, classification and efficacy observation for acute kidney injury (AKI) and chronic kidney disease (CKD). Urine sediment has characteristics of convenience, screening, qualitation, localization, which provides important basis for distinguishing the source of RBC, assisting in the diagnosis of renal glomerular diseases, urinary infection and various causes of renal parenchymal injury. The urine sediment microscopy based on renal tubular epithelial cell (RTEC) and granular tubular (GC) counts mainly includes urinary sediment score (USS), tubular scoring index (CSI), urine microscopy score (UMS), and continuous urine sediment microscopy score (MicrExUrSed), which can provide laboratory information for early diagnosis, etiological differentiation, staging evaluation, and prognosis assessment of AKI.

Objective:To establish a set of artificial intelligence (AI) verification rules for blood routine analysis.Methods:Blood routine analysis data of 18 474 hospitalized patients from the First Hospital of Jilin University during August 1st to 31st, 2019, were collected as training group for establishment of the AI verification rules,and the corresponding patient age, microscopic examination results, and clinical diagnosis information were collected. 92 laboratory parameters, including blood analysis report parameters, research parameters and alarm information, were used as candidate conditions for AI audit rules; manual verification combining microscopy was considered as standard, marked whether it was passed or blocked. Using decision tree algorithm, AI audit rules are initially established through high-intensity, multi-round and five-fold cross-validation and AI verification rules were optimized by setting important mandatory cases. The performance of AI verification rules was evaluated by comparing the false negative rate, precision rate, recall rate, F1 score, and pass rate with that of the current autoverification rules using Chi-square test. Another cohort of blood routine analysis data of 12 475 hospitalized patients in the First Hospital of Jilin University during November 1sr to 31st, 2023, were collected as validation group for validation of AI verification rules, which underwent simulated verification via the preliminary AI rules, thus performance of AI rules were analyzed by the above indicators. Results:AI verification rules consist of 15 rules and 17 parameters and do distinguish numeric and morphological abnormalities. Compared with auto-verification rules, the true positive rate, the false positive rate, the true negative rate, the false negative rate, the pass rate, the accuracy, the precision rate, the recall rate and F1 score of AI rules in training group were 22.7%, 1.6%, 74.5%, 1.3%, 75.7%, 97.2%, 93.5%, 94.7%, 94.1, respectively.All of them were better than auto-verification rules, and the difference was statistically significant ( P<0.001), and with no important case missed. In validation group, the true positive rate, the false positive rate, the true negative rate, the false negative rate, the pass rate, the accuracy, the precision rate, the recall rate and F1 score were 19.2%, 8.2%, 70.1%, 2.5%, 72.6%, 89.2%, 70.0%, 88.3%, 78.1, respectively, Compared with the auto-verification rules, The false negative rate was lower, the false positive rate and the recall rate were slightly higher, and the difference was statistically significant ( P<0.001). Conclusion:A set of the AI verification rules are established and verified by using decision tree algorithm of machine learning, which can identify, intercept and prompt abnormal results stably, and is moresimple, highly efficient and more accurate in the report of blood analysis test results compared with auto-vefication.