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Objective:To analyze the correlation between the grouping and weighting of two sets of disease combination systems, namely diagnosis-related groups(DRG) and diagnosis-intervention packet(DIP), and to establish a multidimensional analysis and evaluation mode by applying DRG, DIP, and clinical pathway to guide the standardized diagnosis and treatment and management of disease types.Methods:DRG grouping and DIP simulation full enrollment were applied to patients discharged from a tertiary Grade A general hospital in 2019. The correlation analysis between DRG, DIP, and clinical pathway inclusion(entry), correlation analysis between relative weight of DRG group and DIP standard score, and correlation analysis between clinical pathway entry and cost structure of the two disease groups were conducted by using chi-square test, Pearson correlation analysis, t-test, structural change value, degree of structural change, and incremental contribution rate. Results:Among the 130 395 patients, 41 460 cases entered the clinical pathway, 127 535 cases were enrolled in DRG, and 104 227 cases were enrolled in DIP. There was a correlation between the enrollment of DRG, DIP, and clinical pathway( P<0.05), and there was also a correlation between the relative weight of DRG groups and the enrollment of clinical pathway. The relative weight of the DRG disease group was positively correlated with the DIP standard score( r2=0.761 7, P<0.001). There was a significant difference in hospitalization costs between patients with and without clinical pathway access for some diseases( P<0.05), and different cost categories had different impacts on the total costs. Conclusions:The weight assignment and value orientation of DRG and DIP disease types are consistent, and the multi-dimensional fusion evaluation mode for DRG-DIP-clinical pathway is feasible. The correlation analysis of DRG, DIP, and clinical pathways can serve as the basis for disease classification and cost structure evaluation, which could help to carry out hospital′s refined management and optimize disease structure.
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Informatization plays an important role in the management of clinical diagnosis and treatment. However, due to the specialty of the discipline, the informatization construction of critical care medicine(CCM)is faced with such problems as the inefficient application of data, the low compliance of diagnosis and treatment operation, and the lack of intelligent quality control tools. The authors discussed the new mode of CCM information management based on data driven. By upgrading clinical information system, establishing single disease control system, introducing comprehensive intelligent analysis platform and building open remote platform, the bottleneck of CCM informatization was broken. The information collection and interaction in ICU was realized, the automatic monitoring and early warning of diagnosis and treatment process was realized, the operation of medical staff according to the guidelines was effectively improved, and the ability of diagnosis and treatment and management efficiency was improved.Furthermore, the homogenization of regional critical medical information could be promoted.
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Objective To assess the efficacy and safety of febuxostat in the treatment of hypemricemia in renal transplant recipients.Methods A total of 124 renal transplant patients with hyperuricemia receiving febuxostat between June 2016 and July 2018 were retrospectively analyzed.Uric acid (UA),liver function and renal function parameters before and 3 months after treatment were compared.Adverse events,recipient and renal allograft survival were recorded throughout the follow-up period.Results Serum level of uric acid significantly decreased after 3-month treatment (P＜0.001).And 66.1％ of them achieved target UA level at Month 3 after dosing.Estimated glomerular filtration rate (eGFR) was maintained.No severe adverse event was observed.All recipient and renal grafts survived during the follow-up period.Conclusions Febuxostat is both effective and safe in the treatment of hyperuricemia in renal transplant.