Objective:To design an assisted management system for medical consumables that integrated management logic of diagnosis related groups(DRG)for disease,so as to standardize the use for medical consumables and to strengthen regulatory efficiency.Methods:The system was designed by a microservices architecture,and the data fusion of business data,data of diagnosis and treatment,and DRG data was realized through constructed data lake.A knowledge graph of associated rule for medical consumables was established,and the intelligent analysis function included prediction for demand,usage optimization,and anomaly detection was provided to assist management decision-making on the basis of inference for historical data and knowledge,and multi-dimensional data queries.A rule engine was deployed at key clinical nodes for real-time compliance review and intelligent alerts.A DRG-based business management process was constructed to cover full lifecycle of consumables,including admission,procurement,warehousing,storage,requisition,usage billing,and traceability,so as to realize real-time monitoring and early warning for consumable costs at the DRG level.Six clinical doctors with 2-3 years of experience in using medical consumable were selected as test users from Tangdu Hospital of the Air Force Medical University,and they were randomly assigned into a system group and a control group,with 3 subjects in each group.The system group utilized the auxiliary management system for medical consumable to perform prediction for the demand of monthly procurement,and rationality verification of consumable.The control group relied on individual experience of doctors.The predicted monthly procurement demand for medical consumables,the accuracy of verifying rationality of using medical consumables between two groups were compared,and the efficiencies of two kinds of management modes also were compared.Results:The accuracy rate of system group was 89.17%in predicting the monthly procurement demand for medical consumables,and the rate of checking accuracy and the rate of checking comprehensiveness of system group were respectively 87.50%and 91.67%in verifying rationality of using medical consumables,which were significantly higher than those of control group,and the differences were significant(x2=6.62,1.96,16.73,P<0.05).The durations of predicting the demand for procurement,and verifying and testing the rationality of consumables in system group were significantly shorter than these in control group[(3.54±0.45)s,(2.23±0.15)s],and the differences were statistically significant(t=1.97,1.65,P<0.05).Conclusion:The medical consumables auxiliary management system integrated with DRG management logic can significantly enhance the accuracy of monthly demand prediction for consumables and the recall rate and precision rate of rationality verification for consumables usage,while greatly improving work efficiency.It is conducive to enhancing the standardized and refined supervision level of consumables usage.

Objective:To design an assisted management system for medical consumables that integrated management logic of diagnosis related groups(DRG)for disease,so as to standardize the use for medical consumables and to strengthen regulatory efficiency.Methods:The system was designed by a microservices architecture,and the data fusion of business data,data of diagnosis and treatment,and DRG data was realized through constructed data lake.A knowledge graph of associated rule for medical consumables was established,and the intelligent analysis function included prediction for demand,usage optimization,and anomaly detection was provided to assist management decision-making on the basis of inference for historical data and knowledge,and multi-dimensional data queries.A rule engine was deployed at key clinical nodes for real-time compliance review and intelligent alerts.A DRG-based business management process was constructed to cover full lifecycle of consumables,including admission,procurement,warehousing,storage,requisition,usage billing,and traceability,so as to realize real-time monitoring and early warning for consumable costs at the DRG level.Six clinical doctors with 2-3 years of experience in using medical consumable were selected as test users from Tangdu Hospital of the Air Force Medical University,and they were randomly assigned into a system group and a control group,with 3 subjects in each group.The system group utilized the auxiliary management system for medical consumable to perform prediction for the demand of monthly procurement,and rationality verification of consumable.The control group relied on individual experience of doctors.The predicted monthly procurement demand for medical consumables,the accuracy of verifying rationality of using medical consumables between two groups were compared,and the efficiencies of two kinds of management modes also were compared.Results:The accuracy rate of system group was 89.17%in predicting the monthly procurement demand for medical consumables,and the rate of checking accuracy and the rate of checking comprehensiveness of system group were respectively 87.50%and 91.67%in verifying rationality of using medical consumables,which were significantly higher than those of control group,and the differences were significant(x2=6.62,1.96,16.73,P<0.05).The durations of predicting the demand for procurement,and verifying and testing the rationality of consumables in system group were significantly shorter than these in control group[(3.54±0.45)s,(2.23±0.15)s],and the differences were statistically significant(t=1.97,1.65,P<0.05).Conclusion:The medical consumables auxiliary management system integrated with DRG management logic can significantly enhance the accuracy of monthly demand prediction for consumables and the recall rate and precision rate of rationality verification for consumables usage,while greatly improving work efficiency.It is conducive to enhancing the standardized and refined supervision level of consumables usage.

Objective:To explore the association of microsatellite polymorphism of MICA gene with susceptibility to esophageal cancer.Methods: PCR-STR microsatellite genotyped technique was used to detect the polymorphism of MICA in Exon 5 in 103 cases of esophageal cancer and 84 cases of normal controls.Constructed of eukaryotic expression vector in esophageal carcinoma with high frequency of occurrence of the MICA allele.NK cells killing effect to 293T cells after alleles MICA transfected were assayed by LDH and the effect on target was 20∶1.ELISA was used to test supernatants sMICA of 293T cell after transfected.Results: Identified five allelic genes in MICA Exon 5 with esophageal cancer.Each allele and its frequency respectively were:MICA-A4(9.71%),MICA-A5(22.3%),MICA-A5.1(40.8%),MICA-A6(15.5%),MICA-A9(11.7%).MICA-A5.1 showed significant difference comparison with the control group.After 293T cell line was transfected MICA allele,MICA-A5.1 group was less sensitive to NK cytotoxicity compared to other groups[(30.4±6.3)%,P<0.05].The secretion of soluble MICA increased(135.7±6.2)pg/ml.Conclusion: Esophageal cancer was relevent with the MICA-A5.1 polymorphism of MICA Exon 5 alleles.Its risk is higher than other alleles.

Objective To design a support system based on HIS for enhancing hospital managers' ability in making decision. Methods Through modeling and programming for the system,we integrate,classify and analyze the date from outside and inside. Results Managers can analyze the outcome using multi-dimensions online tools. This system brings the convenience to managers,and enhances scientific and timely decision. Conclusion We put forward the basic method for hospital support system,which is the foundation for future research.

Objective To discuss the ideas and specific implementation steps of Oracle database upgrading.Methods By using the EXP and IMP which are provided by the Oracle database,import and export of entire database are implemented and complete database upgrading.Results The database is upgraded form Oracle 8i to Oracle 10g,which is the foundation of our hospital follow-up implementation of PACS and RAC technology.Conclusion Because the environment of practical application is different and complex,the Oracle database must test before the upgrading;the appropriate parameters are set according to different front-end application environment,and then enhance server performance significantly.