Design and development of hospital financial management and decision system based on large data
Tang, Medical University of the four
This thesis mainly completes the following work: 1. Analysis of the system requirements of hospital financial management and decision making based on large data the data from the existing hospital financial management information system and related subsystems, through the export of financial and related data collection and analysis, And according to China's financial software data Interim standard interface standardization, standardization and customization. By setting up a modern hospital financial management framework to meet the needs of digital construction of the current hospital financial management, the paper provides a digital working platform for the hospital management to provide quantitative data for the decision-making data of macroscopic financial data report, financial trend analysis and hospital financial supervision system. It not only solves the problems existing in the traditional hospital financial management system, but also breaks through the traditional limitation, regulates the working flow of the hospital financial management system from the normal operation angle, provides the management with the financial data trend analysis, the comparative analysis, the profit and loss, etc. 2, the design of service-oriented system architecture we use advanced and flexible computer technology, network technology and workflow technology to design and develop a hospital financial decision and management information system based on the large data idea. In the system design concept that does not affect the normal operation of the existing hospital financial system, through the data (structured, semi-structured and unstructured) collection, cleaning and centralization, using the standard data Model (standard) to integrate and optimize the financial data, integrating into the large data platform, Change the traditional business intelligence layout. Using Autosys dispatching job to automate batch data export, import and backup, use RTD to update financial data in real time, bulk and real-time data concentration in data Warehouse; Realize data resource unification and normalization through metadata management To improve data storage optimization by means of database counter normalization and data partitioning, the abstract model of business process is used to drive data interoperability, the introduction of NoSQL non-document database-mongodb as data aggregation layer to improve system access speed and data analysis and mining support platform. 3, the development of High-performance Financial management system development Server based on the Java EE system, the client based on the DOT Net framework development, select High-performance, modeless document database MongoDB as a background aggregation database, MS SQL Server as a background data warehouse, Java and C # are the main programming languages, using the spring framework and the classic MVC design pattern for high-end C/S mode application development. Of these, the Dot Net FRAMEWORK–WPF provides rich client implementation data VISUALIZATION,SPRING+J2EE as a business logic layer based on the MVVM design pattern as the presentation layer, hibernate as ORM and provides data persistence , MongoDB as the data aggregation layer, Autosys as the core system of the operation of the system, which ensures the systemDynamic operation Management. The spring framework separates business objects from business logic, and completes the creation, invocation, and recycling of business logic objects through both container (Container) and non container (Non-container) management, guaranteeing the platform independence and scalability of the system. In the design and use of MongoDB in close conjunction with the actual work, according to business rules on the data landscape (basic data) and longitudinal (analytical data) processing and independent storage and effective isolation, and MongoDB as near cache (class caching technology), the data stored in memory and disk, Provide fast access and instantaneous positioning capabilities to achieve high-performance financial management system. 4, realizes the big data thought in the hospital financial system function application This system is to the current hospital financial Information management system function enhancement and the expansion, through introduces the big data thought, realizes the large data set storage, the management unstructured and the semi-structured data and the large data analysis and the excavation. In addition to basic financial accounting and the basic functions of financial statements, it also uses the functions of r language Statistic analysis, classification regression, clustering and association rules to realize the function of real-time financial statement, financial index and cash flow forecasting model to meet the needs of hospital modern financial management, The design goal of hospital financial management and decision system is achieved. Through the complete system test and the performance test, has obtained the good application effect. This study aims at the common problems and deficiencies of hospital informatization, draws on the mature management thought and realization method of banking financial system, designs and develops the hospital financial management and decision system based on the large data idea. In the traditional data warehouse and business intelligence based on the integration of large data ideas, to achieve large data concentration. Based on flexible, easy to expand and robust software architecture design and development, enhance data synergy, provide efficient data aggregation, analysis and mining and dynamic display. The realization of real-time change of financial data, information mining and process supervision, to improve the overall operating efficiency of the hospital, budget management, cost management, performance management, pay attention to the time value of capital and operational risk has very strong practical significance and application value.
Design and development of hospital financial management and decision system based on large data