Diagnosis and treatment information integrated analysis management system for outpatient and emergency treatment and processing method thereof

Abstract

The invention provides a diagnosis and treatment information integrated analysis management system for outpatient and emergency treatment and a processing method thereof, which are used for providing a set of construction scheme of the diagnosis and treatment information integrated analysis management system and can realize automatic acquisition, intelligent processing and analysis application. In detail, a series of optimization settings are further provided for the system architecture and the working mode thereof, applicability, processing efficiency, processing precision, stability, safety and application cost are considered, and the problems that an existing information platform is scattered in data collection, insufficient in quality control and the like are well solved. Therefore, reliable data support is provided for hospital management decision making, high-quality outpatient and emergency treatment management work can be carried out, and high-quality medical services can be provided.

Description

Technical Field

[0001] The present application relates to the field of medical technology, and in particular to an outpatient and emergency department-oriented diagnosis and treatment information integrated analysis and management system and a processing method thereof. Background Art

[0002] For outpatient and emergency departments (abbreviated as outpatient and emergency departments), in actual hospital application scenarios, many different business systems are involved, which correspond to different medical business needs. Therefore, under the development direction of high-quality development and refined management, based on digital means, creating an information platform that can integrate different data sources can provide a good foundation for outpatient and emergency department management, and thus effectively improve service quality and efficiency.

[0003] The inventors of this application have discovered that the existing information platform currently constructed for outpatient and emergency departments has poor processing performance in actual performance, which means that the underlying platform construction plan or its platform working mode has limitations. Summary of the Invention

[0004] This application provides an integrated analysis and management system for outpatient and emergency medical information and a processing method thereof, which is used to provide a solution for building an integrated analysis and management system for outpatient and emergency medical information, which can realize automatic collection, intelligent processing and analysis applications. In terms of details, a series of optimization settings are further provided for the system architecture and its working mode, taking into account applicability, processing efficiency, processing accuracy, stability, security and application cost, and effectively solving the problems of scattered data collection and insufficient quality control in existing information platforms, thereby providing reliable data support for hospital management decisions, helping to carry out high-quality outpatient and emergency medical management and provide high-quality medical services.

[0005] In the first aspect, the present application provides a diagnosis and treatment information integrated analysis and management system for outpatient and emergency departments, which includes a front-end display layer, an application service layer, and a data source access layer; The front-end display layer is configured based on the Vue+Quasar framework, involving the data collection management interface, data analysis display interface and system configuration management interface; The application service layer is configured based on the Node.js+Express.js framework, involving data collection services, data processing services, and a business rule engine. The data collection service involves data capture and data integration sub-services, the data processing service involves data validation and data conversion sub-services, and the business rule engine involves quality control rules and business logic. The data source access layer involves data source adapters and data security mechanisms, and specifically accesses various business systems including electronic medical record systems, hospital information systems, surgical information systems, anesthesia information systems, emergency information systems and cost management systems.

[0006] In the second aspect, the present application provides a processing method for an outpatient and emergency department-oriented medical information integrated analysis and management system. The processing method for the outpatient and emergency department-oriented medical information integrated analysis and management system is applied to the outpatient and emergency department-oriented medical information integrated analysis and management system. The medical information integrated analysis and management system includes a front-end display layer, an application service layer, and a data source access layer; the front-end display layer is configured on the basis of the Vue+Quasar framework, involving a data collection management interface, a data analysis display interface, and a system configuration management interface; the application service layer is configured on the basis of the Node.js+Express.js framework, involving data collection services, data processing services, and a business rule engine. The data collection service involves a data capture sub-service and a data integration sub-service, the data processing service involves a data verification sub-service and a data conversion sub-service, and the business rule engine involves quality control rules and business logic; the data source access layer involves a data source adapter and a data security mechanism, and specifically accesses various business systems including an electronic medical record system, a hospital information system, a surgical information system, an anesthesia information system, an emergency information system, and a cost management system; the processing method for the outpatient and emergency department-oriented medical information integrated analysis and management system includes: Obtain patient information of different patients during the monitoring period from each business system, including basic information, medical information, diagnosis and treatment information, and cost information; After the patient information is verified, the basic characteristics, medical distribution, diagnosis and treatment conditions, and costs of different patients are analyzed; Based on the basic characteristics, medical distribution, treatment conditions and costs of different patients, statistical analysis and processing are carried out from four dimensions: service quantity, service quality, service efficiency and cost analysis.

[0007] From the above content, it can be concluded that this application has the following beneficial effects: In response to the information integration, analysis and management needs of outpatient and emergency clinics, this application provides a solution for building a diagnosis and treatment information integration and analysis management system, which can realize automatic collection, intelligent processing and analysis applications. In terms of details, it also provides a series of optimization settings for the system architecture and its working mode, taking into account applicability, processing efficiency, processing accuracy, stability, security and application cost, and effectively solves the problems of scattered data collection and insufficient quality control in existing information platforms, thereby providing reliable data support for hospital management decisions, helping to carry out high-quality outpatient and emergency management and provide high-quality medical services. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 This is a system architecture diagram of the outpatient and emergency medical information integrated analysis and management system for this application. DETAILED DESCRIPTION

[0010] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0011] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules clearly listed, but may include other steps or modules that are not clearly listed or that are inherent to these processes, methods, products or devices. The naming or numbering of steps in this application does not mean that the steps in the method flow must be executed in the time / logical sequence indicated by the naming or numbering. The process steps that have been named or numbered can be changed in the execution order according to the technical purpose to be achieved, as long as the same or similar technical effects can be achieved.

[0012] The division of modules in this application is a logical division. In actual application, there may be other division methods. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection between modules can be electrical or other similar forms, which are not limited in this application. Moreover, the modules or submodules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed into multiple circuit modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this application.

[0013] First, see Figure 1 The system architecture diagram of the application for the integrated analysis and management system of outpatient and emergency medical information is shown in FIG. Figure 1 As shown, the outpatient and emergency medical information integrated analysis and management system provided by this application can specifically include three major parts: the front-end display layer, the application service layer and the data source access layer.

[0014] Among them, it can be understood that the diagnosis and treatment information integration analysis and management system for outpatient and emergency departments provided by this application adopts a system design of B / S architecture, that is, a browser / server architecture. The user work interface is implemented through a browser, and less transaction logic is implemented on the front end, but the main transaction logic is implemented on the server side. In this way, the core part of the system function implementation is concentrated on the server, which can effectively simplify the system development, maintenance and use costs.

[0015] Correspondingly, the front-end display layer targets the front-end part and is used to configure the corresponding display interface. At the same time, it should also be understood that the front-end display layer does not rule out the possibility of partial deployment on the back-end.

[0016] The application service layer and data source access layer are obviously deployed on the back end, that is, the server.

[0017] On this basis, the main configuration contents involved in the three major parts of the front-end presentation layer, application service layer, and data source access layer are as follows: (1) The front-end display layer is configured based on the Vue+Quasar framework, involving specific interfaces such as data collection management interface, data analysis display interface, and system configuration management interface; Among them, Vue is a JavaScript framework for building user interfaces. It is based on standard HTML, CSS and JavaScript and can efficiently develop user interfaces. Quasar is a framework based on Vue.js, which is suitable for building high-performance, responsive web applications. It provides a rich component library, tools and plug-ins, and allows the same code base to build cross-platform applications. Therefore, the combination of the two, the Vue+Quasar framework, will help to easily create a high-performance front-end display layer for this application system.

[0018] As for the specific interfaces involved in the front-end display layer, it can be seen that in the specific settings, this application has configured three major interfaces: data collection management interface, data analysis and display interface, and system configuration management interface, which correspond to the three major front-end work contents of data collection management, data analysis and display, and system configuration management.

[0019] These three types of interfaces are organized and integrated for the front-end services of this application from the numerous work services involved, and are highly concise and efficient.

[0020] Of course, it is not ruled out that in actual applications, as the system performance needs to be further expanded, new specific interfaces can be further subdivided and added.

[0021] In specific applications, for the front-end display layer, the three specific interfaces mentioned above can be: 1. The data collection management interface is specifically used to display and manage the data collection status (of data involved in various business systems), and perform manual data entry, data editing, and data query (involving the form components of the Quasar framework). It adopts a component-based design and performs real-time data verification through a data binding mechanism.

[0022] 2. The data analysis display interface is based on the Chart.js chart library, which is used for visual display of various statistical indicators. It can dynamically switch between multiple chart types and select the most suitable display method based on data characteristics.

[0023] 3. The system configuration management interface is specifically used to configure system parameters including various rules (such as quality control rules and data collection rules), and is defined in JSON format to dynamically adjust system rules without modifying the code.

[0024] Among them, the use of JSON format to define quality control rules and other rules can support logical operators and conditional expressions, so that non-technical personnel can also easily configure and adjust the rules. Compared with the hard-coding method, it can effectively reduce the technical threshold and maintenance costs.

[0025] (2) The application service layer is configured based on the Node.js+Express.js framework, involving specific services such as data collection service, data processing service and business rule engine. The data collection service involves data capture sub-service and data integration sub-service, the data processing service involves data verification sub-service and data conversion sub-service, and the business rule engine involves quality control rules and business logic; Among them, Node.js is a JavaScript runtime environment and a development platform that allows JavaScript to run on the server. It can easily build network applications that are fast in response and easy to expand. Express.js is a minimalist and flexible Node.js Web application framework with a series of powerful functions to create web applications. The Node.js+Express.js framework formed by the two helps to conveniently build the application service layer involved in this application.

[0026] As for the services involved in the application service layer, it can be seen that they can specifically involve three types: data collection service, data processing service and business rule engine. Furthermore, this application has made further configurations for the sub-services / sub-contents in the detailed operations of the three.

[0027] In addition, in actual applications, as the system performance needs to be further expanded, new specific services can be further subdivided and added.

[0028] In specific applications, for the application service layer, the three major services mentioned above can be: 1. The data collection service specifically uses the node-oracledb module to establish connections with the databases of various business systems, conduct unified access and management of data sources, perform dynamic task scheduling, and use a connection pool mechanism to optimize database access performance.

[0029] Among them, the database connection pool technology is implemented through the node-oracledb module, which can support the establishment of multiple database connections at the same time, effectively avoiding the performance overhead caused by frequent establishment and disconnection of connections, allowing the system to collect data from multiple data sources in parallel at the same time. Compared with the traditional serial collection method, the data acquisition efficiency is improved by about 300%.

[0030] At the same time, the dynamic scheduling mechanism of data collection tasks can automatically adjust the collection frequency and concurrency according to the response time of the data source. This can also effectively avoid excessive pressure on the source system while ensuring the timeliness of the data.

[0031] 2. Data processing services are specifically used for pre-processing such as data cleaning, conversion, and standardization. They use preset mapping rules to achieve field matching of data from different systems, perform multi-level data verification and exception handling, and use streaming processing, sharding processing, and parallel processing to improve data processing efficiency.

[0032] Among them, streaming processing technology adopts pipeline processing in data collection, conversion, verification and other links, which can effectively avoid repeated storage and loading of intermediate data. Compared with traditional batch processing methods, the processing efficiency is improved by about 200%. Through data sharding and parallel processing technology, it can effectively support the rapid processing of large-scale data. A single machine can process more than 100,000 outpatient records per hour.

[0033] At the same time, preliminary verification is carried out in the data collection stage, and real-time verification of data is achieved through streaming processing technology. Compared with the traditional batch verification method, problem discovery and processing will be more timely, and the multi-level data verification mechanism (including verification of multiple dimensions such as field format, value range, logical relationship, etc.) has also significantly improved the accuracy of the data. For data that does not comply with quality control rules, the system will automatically generate a problem list during the exception handling process, and push it to relevant personnel in real time through the message queue mechanism, which also effectively improves the efficiency of problem handling.

[0034] 3. The business rule engine implements dynamic management of quality control rules based on JSON configuration, configures and executes complex logic rules, processes rule execution logs and results tracking, and performs rule version management and rapid switching.

[0035] Among them, using JSON configuration files to define the connection parameters and mapping rules of different data sources can effectively enable the system to quickly adapt to different types of database systems on the data source side. New data sources can be expanded without modifying the code, significantly improving the scalability of the system.

[0036] In addition, for quality control rules, dynamic loading mechanism and hot update mechanism can also be configured. In this way, after adding or modifying rules, they can take effect without restarting the system, effectively improving the flexibility of the system. In addition, rule priority management and dependency checking can be used to ensure the correct execution order of complex rules and effectively avoid rule conflicts.

[0037] (3) The data source access layer involves specific data docking configurations such as data source adapters and data security mechanisms, and specifically connects to various business systems including electronic medical record systems, hospital information systems (HIS), surgical information systems, anesthesia information systems, emergency information systems, and cost management systems.

[0038] It can be understood that in the data docking work that the data source access layer is responsible for, the data source adapter is aimed at being compatible with different types of business systems or data sources, and the data security mechanism provides corresponding security guarantees for the data collection link.

[0039] Among them, specific content is also provided here for the business systems that may be involved in this application in outpatient and emergency aspects. These six major systems usually have existing business systems. Of course, it is not ruled out that they are systems that are redeployed when applying the present application solution. In addition, in specific applications, other types of business systems may continue to be involved, which is also possible.

[0040] In specific applications, for the data source access layer, for the above two major data connection configurations, there can be: 1. The data source adapter provides unified access to multiple database types, dynamically configures and manages data sources, configures data source health monitoring mechanisms, and performs data source failover. Among them, the data source health monitoring and fault switching mechanism realizes real-time monitoring of the system operation status (involving key indicators such as data collection progress, processing performance, resource usage, etc.), supports timely detection and processing of system anomalies, and automatically switches to the backup data source when a data source anomaly is detected, thereby effectively ensuring the continuous availability of the system.

[0041] 2. The data security mechanism specifically uses JWT+Bcrypt for user authentication and authorization, data transmission encryption, data access control and audit log recording, as well as data backup and recovery.

[0042] Among them, JWT (Java Web Token) is a standard for transmission based on JSON, and Bcrypt is a cross-platform text encryption tool. It uses a combination of JWT and Bcrypt to implement user authentication and authorization. Compared with traditional session authentication methods, it provides better cross-domain support and scalability. At the same time, fine-grained data access control and support for role-based and data range-based permission management effectively ensure secure data access. It also provides complete security audit capabilities through data transmission encryption and access logging.

[0043] Furthermore, based on the system architecture and its specific configuration content involved above, this application can also provide a more vivid explanation of the outpatient and emergency medical information integration analysis and management system provided by this application from the perspective of system operation.

[0044] Specifically, in terms of the overall aspect, the diagnosis and treatment information integrated analysis and management system of this application can include the following processing contents based on the front-end display layer, application service layer and data source access layer: 1) During the data collection phase, various business systems are connected through configured data source adapters, raw data is extracted according to preset collection rules, a data collection task queue is established to enable concurrent collection, the collection process is monitored, and abnormal situations are recorded; It can be understood that in response to the data usage needs of outpatient and emergency management work, data collection work can be carried out and promoted based on the data source adapter.

[0045] 2) During the data processing phase, the collected data is cleaned and standardized, and data verification is performed using a quality control rule engine to generate diagnosis and treatment information. During the processing process, data sharding and parallel processing are used to perform real-time data batch processing; It can be understood that after the corresponding data is collected through the data source adapter, a series of data processing can be performed to initially obtain the required simplified data, and further data processing can be performed subsequently based on user needs and business needs.

[0046] 3) During the data storage phase, a distributed storage architecture is used to improve data access efficiency, configure data version management and historical traceability, perform incremental data updates and full data synchronization, and configure data backup and disaster recovery mechanisms. Among them, the distributed storage architecture can improve the access efficiency and reliability of data through data sharding and replication mechanisms, record the history of each data change through the data version management mechanism, thereby supporting data backtracking and auditing, and effectively improving data traceability. The data incremental update mechanism can record the last updated timestamp of the data and only process the changed data each time, thereby significantly reducing system resource consumption. Full synchronization synchronizes all data at time intervals such as every day.

[0047] In the data backup and disaster recovery mechanism, incremental data backup and scheduled full data backup can be performed to support rapid data recovery. At the same time, data disaster recovery capabilities can be provided through data copies and distributed storage to avoid data loss caused by single point failures. An automatic verification mechanism for backup data can also be introduced to ensure the integrity and availability of backup data.

[0048] 4) In the data analysis phase, multi-dimensional data statistical analysis is performed, automatic calculation and update of configuration indicators are configured, data export functions are provided in multiple formats, report generation modules are integrated, and report templates are customized.

[0049] In terms of data analysis, a series of preset indicators can be used to reflect the work status of outpatient and emergency departments, and data can be exported in different selected formats such as pictures, texts, and videos. Among them, the same type of file format can be further subdivided into different specific formats. In addition, the integrated report generation module can be used to generate more relevant reports that meet the requirements based on the customized report template for output.

[0050] It can be understood that the above content is developed on the basis of the system architecture and its specific configuration content given above, so no repetition is made.

[0051] In addition, this application also provides further configuration solutions to meet the management needs of outpatient and emergency departments.

[0052] Specifically, the medical information integrated analysis and management system of this application may also include the following processing contents based on the front-end display layer, application service layer and data source access layer: 1) Obtain patient information of different patients during the monitoring period from each business system, including basic information, medical information, diagnosis and treatment information, and cost information; It can be seen that the information that this application can obtain from the data source side, that is, the business system side, may specifically involve basic information, medical information, diagnosis and treatment information, and cost information, and these data can be referred to as patient information.

[0053] In terms of details, the acquisition can be triggered manually or performed automatically, such as real-time acquisition.

[0054] 2) After patient information is verified, analyze the basic characteristics, medical distribution, diagnosis and treatment status, and cost of each patient; After obtaining the patient information, it can be verified. If an abnormality is determined during the verification process, a prompt can be given, thereby further improving the accuracy of data capture.

[0055] After passing the verification, feature analysis can be carried out to analyze the basic characteristics, medical distribution, diagnosis and treatment conditions and cost conditions. The four correspond to the basic information, medical information, diagnosis and treatment information and cost information mentioned above.

[0056] Among them, basic characteristics may specifically involve gender, age, region, etc., medical distribution may specifically involve medical departments, appointment registration methods, patient outcomes, etc., medical treatment conditions may specifically involve outpatient diagnosis, emergency diagnosis, emergency classification, surgical operations, etc., and cost conditions may specifically involve total costs, various cost structures, medical insurance payment information, etc.

[0057] In specific operations, specific feature situations can be analyzed based on specific content objects and their corresponding feature analysis strategies.

[0058] 3) Based on the basic characteristics, medical distribution, diagnosis and treatment conditions and cost of different patients, statistical analysis and processing are carried out from four dimensions: service quantity, service quality, service efficiency and cost analysis.

[0059] It can be understood that the indicator system constructed in this application can be deployed specifically from the four dimensions of service quantity, service quality, service efficiency and cost analysis, and further specific indicators can be configured under these four dimensions. In this way, the basic characteristics, medical distribution, diagnosis and treatment conditions and cost conditions determined earlier can be mapped to these four dimensions, and the specific statistical analysis indicators can be quantified to deeply and accurately reflect the working conditions of outpatient and emergency departments.

[0060] For example, specific indicators may include the proportion of patient structure (corresponding to the number of services), the proportion of follow-up patients (corresponding to service quality), the consistency rate between outpatient diagnosis and discharge diagnosis (corresponding to service quality), the outpatient on-time attendance rate (corresponding to service efficiency) and the average increase in outpatient cost per visit (corresponding to cost analysis).

[0061] At the same time, based on the above-mentioned use of a series of indicator systems to quantify the work status of outpatient and emergency departments, this application can also involve the promotion of the corresponding outpatient and emergency management work.

[0062] Specifically, the integrated analysis and management system for diagnosis and treatment information of this application may also include the following processing contents: Based on the statistical analysis and processing results, corresponding outpatient and emergency management strategies are generated.

[0063] It can be understood that the outpatient and emergency department management strategy automatically generated here can be understood as the specific work content of the management work of the outpatient and emergency department or corresponding improvement suggestions.

[0064] For example, after systematically monitoring and evaluating the work of outpatient and emergency departments through a series of indicator systems to objectively reflect the basic quality, link quality and final quality of outpatient and emergency medical care, the evaluation results can be linked to department performance, and timely feedback and rectification can be provided to form a closed management loop.

[0065] For example, physician visit management measures can be adjusted based on the outpatient on-time attendance rate, and the average outpatient cost analysis results can be used as one of the indicators for evaluating reasonable diagnosis and treatment.

[0066] In addition, this application also takes into account the need for retrospective review of past medical behaviors that may be involved in actual medical work, and can perform targeted processing based on the data recorded in the system to better meet this need from an archiving perspective.

[0067] Specifically, the integrated analysis and management system for diagnosis and treatment information of this application may also include the following processing contents: For each individual patient, the ID number is used as the unique identifier to archive the corresponding patient information, basic characteristics, medical distribution, medical treatment status, cost status and statistical analysis results to form a core medical record suitable for outpatient and emergency medical treatment information page processing business.

[0068] Among them, it is understandable that by adopting the retrospective archiving mode, the system will automatically monitor the patient's data update status in different systems, ensuring that subsequent completed data such as tests and examinations can be automatically associated and archived, avoiding the data omission problem that exists in traditional methods.

[0069] For current patients, while archiving the series of data involved above, this application also specifically and uniformly uses the patient's ID number as a unique identifier to achieve cross-system data correlation and integration, solving the data fragmentation problem caused by inconsistent patient identification under traditional methods.

[0070] In this way, if there is a need to review or trace a certain medical treatment behavior or medical treatment behavior for a certain disease in the future, the patient's ID number can be used as the query keyword to initiate a query request to the system, and the target archived data that you want to know can be viewed in the series of archived data returned / feedback.

[0071] It can also be seen that for archiving processing, this application can be further combined with the relevant outpatient and emergency treatment information page processing business to provide stable, adaptive and accurate data support for the relevant outpatient and emergency treatment information page processing business, and meet the hospital itself or relevant institutions outside the hospital based on the outpatient and emergency treatment information page (which can be understood as a page specifically used to highly centrally display the patient's outpatient and emergency treatment status) for archiving data recording, viewing and supervision needs, for example, it can involve third-party regulatory agencies, and for example, it can involve higher-level regulatory departments, so as to further strengthen the outpatient and emergency treatment information integration analysis and management functions.

[0072] Correspondingly, in the subsequent stages of this application, the medical information integrated analysis and management system may also include the following processing contents: Upload all core medical records to the data interface of the relevant outpatient and emergency treatment information page for processing business.

[0073] It can be understood that uploading archived data, that is, the processing of all core medical records, to the data interface of the relevant outpatient and emergency medical information page processing business can further promote the development of the relevant outpatient and emergency medical information page processing business.

[0074] Furthermore, for the applications involved in the outpatient and emergency medical treatment information page processing business here, in addition to considering the commonly thought data content adaptability settings (that is, the data content must adapt to the data usage requirements of the outpatient and emergency medical treatment information page processing business) during the data archiving process, this application can also consider how to better manage and transmit archived data for the outpatient and emergency medical treatment information page processing business.

[0075] Specifically, in order to facilitate data management and transmission and improve processing performance, some general technical means can usually be used to achieve this goal. In terms of details, this application can introduce machine learning technology or artificial intelligence (AI) technology in combination with the specific application scenario. Through the corresponding neural network model (mainly deep learning neural network), the archived data, that is, the core medical records of all previous visits, can be adjusted to the corresponding format that is more suitable for the subsequent data processing business corresponding to the outpatient and emergency treatment information page, so as to facilitate data management and transmission work to be carried out more conveniently and efficiently.

[0076] In this regard, this application can be considered that there is an unequal degree of adaptability between the data storage format of local core medical records and the specific application requirements of outpatient and emergency medical information page processing services in different situations, and this will reflect differences in data management (storage, query and call, etc.) and transmission at a subtle level. In this way, this application can output a data storage format that is compatible with the current application requirements of outpatient and emergency medical information page processing services through a configured data storage format configuration model.

[0077] Specifically, the present application can determine the target application requirements of the current outpatient and emergency treatment information page processing business, and input the description data of the target application requirements into the data storage format configuration model (obtained by training the initial model with different application requirements marked with the adapted data storage format) to carry out the corresponding data storage format configuration processing and obtain the target data format adapted to the target application requirements. In this way, the stored core medical records and / or the core medical records to be stored in the future can be configured according to the target data format.

[0078] Among them, it is necessary to understand that for the data storage format configuration model, the different application requirements involved are reflected in the different application condition indicators that may be involved in actual applications, such as display time period, display device type, display screen specifications, data management cost constraints, data management accuracy constraints, data management efficiency constraints, data transmission cost constraints, data transmission accuracy constraints, data transmission efficiency constraints, data transmission intervals, data transmission time periods, processing only for specific data content, information integration scope, etc., involving fine granularity in different aspects, rather than simply distinguishing by several application scenarios.

[0079] Similarly, the data storage formats involved cannot be limited to conventional or universal data storage formats (or data storage forms / schemes). Based on the introduction of machine learning models with powerful processing performance, the models can be configured to independently search and construct specific data storage formats, forming a personalized / customized data storage format that can be more highly adapted to the specific application needs of outpatient and emergency treatment information page processing business based on the specific application scenario of the hospital application scenario in which it is located.

[0080] Under this setting, it is obvious that under the condition that the original data content is already suitable for outpatient and emergency medical treatment information page processing business, the specific application needs of the outpatient and emergency medical treatment information page can be considered, taking into account the management performance and transmission performance at the data processing level (performance mainly involves processing efficiency, processing accuracy and processing cost), especially to meet the complex or dynamically changing specific application needs, achieve better solution application effects in details, and be more conducive to the development of related outpatient and emergency medical treatment information page processing business.

[0081] In addition, in terms of details, this application also considers further improving the convenience and user experience of medical staff or patients in querying specific archived data. In the above-mentioned archiving mechanism, the subdivision setting of archiving units or archiving granularity is also introduced.

[0082] Specifically, in the above archiving mechanism, for the same patient, it is usually considered that all the data related to the patient are archived together in the database. In this regard, the present application can also be further divided based on the identified single medical visit behavior.

[0083] For example, corresponding data generated within the same time range (usually one day) can be considered to belong to the same single medical visit and can be archived together; For another example, for the same confirmed disease within a preset number of days, the corresponding data for one or more days involved can be identified as belonging to the same single medical visit and can be archived together.

[0084] It can be seen that the specific definition of a single medical visit behavior can also be adjusted in specific operations. In this way, based on a single medical visit behavior, a more flexible data archiving architecture that better meets the needs of real users can be constructed, laying a good foundation for the efficient and accurate retrospective processing of the entire medical process of subsequent patients.

[0085] Finally, regarding the above solution content, in general, this application provides a solution for building a diagnosis and treatment information integrated analysis and management system, which can realize automatic collection, intelligent processing and analysis applications. In terms of details, it also provides a series of optimization settings for the system architecture and its working mode, taking into account applicability, processing efficiency, processing accuracy, stability, security and application cost, and effectively solves the problems of scattered data collection and insufficient quality control in existing information platforms, thereby providing reliable data support for hospital management decisions, helping to carry out high-quality outpatient and emergency management work and provide high-quality medical services.

[0086] In addition, corresponding to the previously provided outpatient and emergency medical information integrated analysis and management system, this application also provides a processing method for the outpatient and emergency medical information integrated analysis and management system from the perspective of the system's workflow.

[0087] Specifically, the processing method of the diagnosis and treatment information integrated analysis and management system for outpatient and emergency departments is applied to the diagnosis and treatment information integrated analysis and management system for outpatient and emergency departments. The diagnosis and treatment information integrated analysis and management system includes a front-end display layer, an application service layer and a data source access layer; the front-end display layer is configured based on the Vue+Quasar framework, involving a data collection management interface, a data analysis display interface and a system configuration management interface; the application service layer is configured based on the Node.js+Express.js framework, involving data collection services, data processing services and a business rule engine, the data collection service involves a data capture sub-service and a data integration sub-service, the data processing service involves a data verification sub-service and a data conversion sub-service, and the business rule engine involves quality control rules and business logic; the data source access layer involves a data source adapter and a data security mechanism, and specifically accesses various business systems including an electronic medical record system, a hospital information system, a surgical information system, an anesthesia information system, an emergency information system and a cost management system; the processing method of the diagnosis and treatment information integrated analysis and management system for outpatient and emergency departments includes: 1) Obtain patient information of different patients during the monitoring period from each business system, including basic information, medical information, diagnosis and treatment information, and cost information; 2) After patient information is verified, analyze the basic characteristics, medical distribution, diagnosis and treatment status, and cost of each patient; 3) Based on the basic characteristics, medical distribution, diagnosis and treatment conditions and cost of different patients, statistical analysis and processing are carried out from four dimensions: service quantity, service quality, service efficiency and cost analysis.

[0088] In an exemplary embodiment, for the front-end presentation layer, there are: The data collection management interface is specifically used to display and manage the data collection status, and perform manual data entry, data editing and data query. It adopts a component-based design and performs real-time data verification through a data binding mechanism; The data analysis display interface is based on the Chart.js chart library, which is used for visual display of various statistical indicators. It can also dynamically switch between multiple chart types and select the most suitable display method based on data characteristics. The system configuration management interface is specifically used to configure system parameters including various rules, and is defined in JSON format to dynamically adjust system rules without modifying the code.

[0089] In another exemplary embodiment, for the application service layer, there are: The data collection service specifically uses the node-oracledb module to build connections with various business system databases, conduct unified access and management of data sources, perform dynamic task scheduling, and use a connection pool mechanism to optimize database access performance; Data processing services are specifically used to clean, convert, and standardize data. They use preset mapping rules to match fields of data from different systems, perform multi-level data verification and exception handling, and use streaming, sharding, and parallel processing to improve data processing efficiency. The business rule engine implements dynamic management of quality control rules based on JSON configuration, configures and executes complex logic rules, processes rule execution logs and results tracking, and performs rule version management and quick switching.

[0090] In another exemplary embodiment, for the data source access layer, there are: The data source adapter specifically provides unified access to multiple database types, performs dynamic configuration and management of data sources, configures data source health monitoring mechanisms, and performs data source fault switching; The data security mechanism specifically uses JWT+Bcrypt for user authentication and authorization, data transmission encryption, data access control and audit log recording, as well as data backup and recovery.

[0091] In another exemplary embodiment, the medical information integrated analysis and management system includes the following processing contents based on the front-end display layer, application service layer and data source access layer: During the data collection phase, various business systems are connected through configured data source adapters, raw data is extracted according to preset collection rules, a data collection task queue is established to achieve concurrent collection, the collection process is monitored, and abnormal situations are recorded; During the data processing phase, the collected data is cleaned and standardized, and data verification is performed using a quality control rule engine to generate diagnosis and treatment information. During the processing, data sharding and parallel processing are used to perform real-time data batch processing. During the data storage phase, a distributed storage architecture is used to improve data access efficiency, configure data version management and historical traceability, perform incremental data updates and full synchronization, and configure data backup and disaster recovery mechanisms. During the data analysis phase, multi-dimensional data statistical analysis is performed, automatic calculation and update of configuration indicators are performed, data export functions are provided and involve multiple formats, report generation modules are integrated, and report templates are customized.

[0092] In yet another exemplary embodiment, the method further includes: Based on the statistical analysis and processing results, corresponding outpatient and emergency management strategies are generated.

[0093] In yet another exemplary embodiment, the method further includes: For each individual patient, the ID number is used as the unique identifier to archive the corresponding patient information, basic characteristics, medical distribution, diagnosis and treatment conditions, cost conditions and statistical analysis results to form the core medical records of all previous visits.

[0094] In yet another exemplary embodiment, the method further includes: Upload all core medical records to the data interface of the relevant outpatient and emergency treatment information page for processing business.

[0095] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process of the processing method of the outpatient and emergency medical information integrated analysis and management system described above can refer to the following. Figure 1 The description of the integrated analysis and management system for outpatient and emergency medical information in the corresponding embodiment will not be repeated here.

[0096] The above is a detailed introduction to the outpatient and emergency medical information integrated analysis and management system and the processing method of the outpatient and emergency medical information integrated analysis and management system provided by this application. This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the core idea of ​​this application; at the same time, for technical personnel in this field, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on this application.

Claims

1. A diagnosis and treatment information integrated analysis and management system for outpatient and emergency departments, characterized by: The diagnosis and treatment information integrated analysis and management system includes a front-end display layer, an application service layer and a data source access layer; The front-end display layer is configured based on the Vue+Quasar framework, involving data collection management interface, data analysis display interface and system configuration management interface; The application service layer is configured on the basis of Node.js+Express.js framework, involving data collection services, data processing services and business rule engines. The data collection services involve data capture sub-services and data integration sub-services, the data processing services involve data verification sub-services and data conversion sub-services, and the business rule engine involves quality control rules and business logic. The data source access layer involves data source adapters and data security mechanisms, and specifically accesses various business systems including electronic medical record systems, hospital information systems, surgical information systems, anesthesia information systems, emergency information systems and expense management systems.

2. The integrated analysis and management system for outpatient and emergency medical information according to claim 1 is characterized in that: For the front-end presentation layer, there are: The data collection management interface is specifically used to display and manage the data collection status, and perform manual data entry, data editing and data query. It adopts a componentized design and performs real-time data verification through a data binding mechanism; The data analysis and display interface is specifically based on the Chart.js chart library, which is used for the visual display of various statistical indicators and dynamic switching of multiple chart types, selecting the most suitable display method according to data characteristics; The system configuration management interface is specifically used to configure system parameters including various rules, and is defined in JSON format to dynamically adjust system rules without modifying the code.

3. The integrated analysis and management system for outpatient and emergency medical information according to claim 1 is characterized in that: For the application service layer, there are: The data collection service specifically uses the node-oracledb module to establish connections with the databases of the various business systems, performs unified access and management of data sources, performs dynamic task scheduling, and uses a connection pool mechanism to optimize database access performance; The data processing service is specifically used to perform data cleaning, conversion and standardization, achieve field matching of data from different systems through preset mapping rules, perform multi-level data verification and exception handling, and adopt streaming processing, sharding processing and parallel processing to improve data processing efficiency; The business rule engine specifically implements dynamic management of quality control rules based on JSON configuration, configures and executes complex logic rules, processes rule execution logs and results tracking, and performs rule version management and fast switching.

4. The integrated analysis and management system for outpatient and emergency medical information according to claim 1 is characterized in that: For the data source access layer, there are: The data source adapter specifically provides unified access to multiple database types, performs dynamic configuration and management of data sources, configures data source health monitoring mechanisms, and performs data source fault switching; The data security mechanism specifically uses JWT+Bcrypt for user authentication and authorization, data transmission encryption, data access control and audit log recording, and data backup and recovery.

5. The integrated analysis and management system for outpatient and emergency medical information according to claim 1 is characterized in that: The medical information integrated analysis and management system includes the following processing contents based on the front-end display layer, the application service layer and the data source access layer: During the data collection phase, the business systems are connected via the configured data source adapters, raw data is extracted according to preset collection rules, a data collection task queue is established to achieve concurrent collection, the collection process is monitored, and abnormal situations are recorded; During the data processing phase, the collected data is cleaned and standardized, and data verification is performed using a quality control rule engine to generate diagnosis and treatment information. During the processing, data sharding and parallel processing are used to perform real-time data batch processing. During the data storage phase, a distributed storage architecture is used to improve data access efficiency, configure data version management and historical traceability, perform incremental data updates and full synchronization, and configure data backup and disaster recovery mechanisms. During the data analysis phase, multi-dimensional data statistical analysis is performed, automatic calculation and update of configuration indicators are performed, data export functions are provided and involve multiple formats, report generation modules are integrated, and report templates are customized.

6. The integrated analysis and management system for outpatient and emergency medical information according to claim 1, characterized in that: The medical information integrated analysis and management system includes the following processing contents based on the front-end display layer, the application service layer and the data source access layer: Obtaining patient information including basic information, medical information, diagnosis and treatment information, and expense information of different patients during the monitoring period from each business system; After the patient information is verified, the basic characteristics, medical distribution, diagnosis and treatment conditions and expenses of the different patients are analyzed; Based on the basic characteristics of the different patients, the distribution of medical treatment, the diagnosis and treatment conditions and the cost conditions, statistical analysis and processing are carried out from four dimensions: service quantity, service quality, service efficiency and cost analysis.

7. The integrated analysis and management system for outpatient and emergency medical information according to claim 6, characterized in that: The integrated analysis and management system for diagnosis and treatment information also includes the following processing contents: Based on the statistical analysis and processing results, corresponding outpatient and emergency management strategies are generated.

8. The integrated analysis and management system for outpatient and emergency medical information according to claim 6 is characterized in that: The integrated analysis and management system for diagnosis and treatment information also includes the following processing contents: For each individual patient, the ID number is used as the unique identifier, and the corresponding patient information, basic characteristics, medical distribution, medical treatment conditions, cost conditions and statistical analysis results are archived to form the core medical records of all times.

9. The integrated analysis and management system for outpatient and emergency medical information according to claim 8, characterized in that: The integrated analysis and management system for diagnosis and treatment information also includes the following processing contents: Upload the core medical records to the data interface of the relevant outpatient and emergency treatment information page processing business.

10. A processing method for an integrated analysis and management system of outpatient and emergency medical information, characterized in that: The processing method of the integrated analysis and management system for outpatient and emergency departments is applied to the integrated analysis and management system for outpatient and emergency departments. The integrated analysis and management system for outpatient and emergency departments includes a front-end display layer, an application service layer, and a data source access layer. The front-end display layer is configured on the basis of the Vue+Quasar framework, involving a data acquisition management interface, a data analysis display interface, and a system configuration management interface. The application service layer is configured on the basis of the Node.js+Express.js framework, involving data acquisition services, data processing services, and a business rule engine. The data acquisition service involves a data capture sub-service and a data integration sub-service. The data processing service involves a data verification sub-service and a data conversion sub-service. The business rule engine involves quality control rules and business logic. The data source access layer involves a data source adapter and a data security mechanism, and specifically accesses various business systems including an electronic medical record system, a hospital information system, a surgical information system, an anesthesia information system, an emergency information system, and a cost management system. The processing method of the integrated analysis and management system for outpatient and emergency departments includes: Obtaining patient information including basic information, medical information, diagnosis and treatment information, and expense information of different patients during the monitoring period from each business system; After the patient information is verified, the basic characteristics, medical distribution, diagnosis and treatment conditions and expenses of the different patients are analyzed; Based on the basic characteristics of the different patients, the distribution of medical treatment, the diagnosis and treatment conditions and the cost conditions, statistical analysis and processing are carried out from four dimensions: service quantity, service quality, service efficiency and cost analysis.

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