Hospital clinical staff management system supporting multi-application cross-cloud deployment

Abstract

The application discloses a hospital clinical function department personnel management system supporting multi-application cross-cloud deployment, which comprises a cross-cloud deployment module, a personnel main index construction module, a multi-mode adaptation module and a tenant management module. The cross-cloud deployment module supports the system deployment in a public cloud, a private cloud and a private cloud. The personnel main index construction module uniformly designs a personnel architecture at a top layer, constructs a staff main index, realizes the unified matching of staff among different systems and deployment modes, and unifies the organization architecture and personnel identity. The multi-mode adaptation module is used for the business system to access in three modes, i.e. completely using a personnel base system, reserving a self-owned system for work number matching, and only making application login portals. The tenant management module realizes the multi-tenant mode for the institution registration and work number matching under the public cloud and the private cloud, and realizes the internal staff information interaction of the institution under the private cloud. The application belongs to the technical field of clinical management systems of medical systems, and the structure can realize the process intercommunication and information alignment between the upper business subsystem and different modules, and guarantee the business continuity.

Description

Technical Field

[0001] This invention relates to the field of clinical management system technology in the medical system. Background Technology

[0002] Currently, most clinical functional department management systems in medical institutions are independent systems for individual departments. Different management systems have their own independent user management systems, and there is no unified overall solution.

[0003] The existing technology has the following technical problems: First, when it comes to collaboration between different management departments, customized data interfaces need to be developed between systems. However, since there is no unified standard for personnel organizational structure among the systems, problems such as misaligned organizational structures and the need for each system to maintain personnel information often occur, resulting in a large workload and inaccurate data. Second, different hospitals may choose public cloud SaaS mode or private deployment mode at different stages. When existing independent systems are deployed, switched or coexisted across clouds, data synchronization is delayed, and concurrent modifications on multiple terminals are prone to data conflicts that cannot be self-healed. Third, relying entirely on employee IDs for matching personnel between systems has an extremely low fault tolerance rate. Once employee IDs are missing or incorrect, it is impossible to achieve unified personnel identities and interoperability of processes.

[0004] Therefore, there is an urgent need to develop a hospital clinical functional department personnel management system that supports multi-application cross-cloud deployment to solve the problems in existing technologies. Summary of the Invention

[0005] The purpose of this invention is to provide a hospital clinical functional department personnel management system that supports multi-application cross-cloud deployment. It can realize process interoperability and information alignment between upper-level business subsystems and different modules, ensuring business continuity. Moreover, it has a simple structure and is easy to use, thus solving the problem mentioned in the background art that the existing hospital clinical department personnel management system cannot achieve unified matching of personnel across systems in a multi-cloud environment, resulting in process inconsistencies and information silos.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A hospital clinical functional department personnel management system that supports multi-application, cross-cloud deployment, including: A cross-cloud deployment module is used to support the deployment of the system on public clouds, dedicated clouds, and private clouds; The personnel master index construction module is used for top-level unified design of the personnel system architecture of different departments in medical institutions, constructing a master index of employees in the hospital's clinical functional departments, and realizing unified matching of employees between different systems and different deployment methods. The personnel master index construction module performs employee master index matching based on multi-dimensional attribute weighting, including: Obtain personnel information from heterogeneous systems and extract multi-dimensional attribute features including employee ID, name, ID card number, mobile phone number, and department; By combining the input attribute data with the existing main index attribute data of the base and the weight coefficients corresponding to each attribute, a comprehensive similarity score is obtained based on the similarity weighted calculation principle. The weight coefficient of the ID number is 0.4 and the weight coefficient of the name is 0.2. When the comprehensive similarity score is between a preset high threshold and a preset low threshold, the AI ​​identity resolution model is triggered to make a judgment. The AI ​​identity resolution model converts the attributes of the people to be compared into feature vectors, inputs them into a machine learning binary classification model, and outputs the probability value that each pair of people records belongs to the same person. If the probability value is greater than the preset probability threshold, it is determined to be the same person and the main index is merged; otherwise, it is determined to be a new person and a new main index is generated. The multi-mode adaptation module allows business systems on the platform to access the platform in three modes: the first mode is to fully utilize the organizational structure and personnel management system of the platform; the second mode is to retain the platform's own personnel management system, match employee IDs, unify personnel identities, and maintain the platform's own organizational structure; the third mode is to use the platform only as an application login portal, fully retaining the platform's own organizational structure and user system. The tenant management module is used to implement a multi-tenant mode in public cloud and private cloud deployments. Different medical institutions can use the departmental organizational relationship and personnel master index of the personnel base through registration, and match the relationship between the personnel ID and the existing system of the medical institution. In the private cloud deployment, it is used by the medical institution itself and realizes the interaction of employee information with other systems within the institution.

[0007] By adopting the above technical solutions, unified management of hospital clinical functional departments personnel can be achieved in a cross-cloud environment. The cross-cloud deployment module supports deployment in multiple cloud environments, the personnel master index construction module enables unified matching of employees between different systems, the multi-mode adaptation module provides three access modes, the tenant management module achieves multi-tenant isolation, and the cross-cloud synchronization engine ensures real-time data synchronization.

[0008] As a further aspect of the present invention: the personnel master index construction module performs employee master index matching based on dynamic weight adjustment, specifically including: dynamically adjusting the weight coefficients according to the importance of attributes in the medical scenario, wherein the weight of professional title is higher than that of department, the weight of professional qualification is higher than that of mobile phone number, and the weight allocation is adjusted in real time based on business scenarios such as emergency and regular outpatient clinics.

[0009] By adopting the above technical solutions, the accuracy of identity matching in medical scenarios can be improved. The attribute weights can be dynamically adjusted according to business scenarios such as emergency and professional titles, thus solving the problem that conventional fixed weights cannot adapt to complex medical data.

[0010] As a further aspect of the present invention: the cross-cloud deployment module stores sensitive medical data, such as patient information and diagnostic records, in a private cloud, while non-sensitive data, such as organizational structure and basic personnel information, are processed in a public cloud. Combined with encryption technology and audit logs, this ensures the compliance of medical data.

[0011] By adopting the above technical solutions, the security and compliance of medical data are ensured. Through hybrid cloud architecture and encryption technology, the requirements of the medical industry for data not leaving the domain and privacy protection are met, and the leakage of sensitive data is avoided.

[0012] As a further aspect of the present invention: the tenant management module supports multi-tenant business collaboration, specifically including: on the basis of logical isolation of tenant data, temporary collaboration between different medical institutions is achieved through access control and data anonymization, such as cross-hospital consultations, expert support, and sharing of limited data, such as patient medical record summaries and expert qualifications.

[0013] By adopting the above technical solutions, business collaboration between medical institutions can be supported, limited data sharing can be achieved on the basis of multi-tenant isolation, cross-hospital collaboration can be promoted, such as expert support and consultation, and the utilization rate of medical resources can be improved.

[0014] As a further aspect of the present invention: the system also includes a cross-cloud synchronization engine, used to perform cross-cloud bidirectional real-time synchronization based on event-driven and message queues; when the personnel information of the base and subsystems changes, the changed content is encapsulated as a standard event message and pushed into the message queue; according to the event subscription relationship, the standard event message is pushed to the target system across the cloud to achieve incremental real-time synchronization.

[0015] By adopting the above technical solutions, real-time perception and data flow of personnel organizational structure changes in a cross-cloud environment can be achieved, breaking down data silos between systems and ensuring the timeliness of information synchronization.

[0016] As a further aspect of the present invention: the cross-cloud synchronization engine executes a conflict resolution strategy driven by business logic, specifically including: adjusting the conflict determination rules in conjunction with the priority of medical business, such as prioritizing emergency care over regular outpatient care, prioritizing the processing of data changes related to high-priority business, and ensuring the consistency of critical medical data.

[0017] By adopting the above technical solutions, we can optimize the conflict resolution of cross-cloud synchronization, and combine it with medical business priorities, such as emergency priority, to ensure the consistency of critical business data, such as patient diagnosis and emergency information, and avoid medical errors caused by conflicts.

[0018] As a further aspect of the present invention, the cross-cloud synchronization engine also executes a data conflict resolution strategy: if the same employee's master index is modified simultaneously on different deployment terminals, the timestamp of the modification operation and the priority of the source system are obtained; based on the timestamp and the source system priority determination rules, the source system priority is first determined, and when the priorities are the same, the timestamp is determined, and the changed data of the high-priority source system is overwritten with the changed data of the low-priority source system, and the conflict log is recorded.

[0019] By adopting the above technical solutions, the problem of data inconsistency caused by concurrent modifications across multiple cloud platforms can be solved, conflicts can be automatically resolved and traces can be left, and the authority and consistency of master data can be guaranteed.

[0020] As a further aspect of this invention: the multi-mode adaptation module executes different technical logic for the three modes: in the first mode, the subsystem business operation request directly calls the base interface to read the organizational structure and personnel data, and the subsystem does not store the personnel table locally; in the second mode, the mapping dictionary between the local employee ID and the employee master index is generated through the personnel master index building module, and bidirectional synchronization is performed through the cross-cloud synchronization engine when the data changes; in the third mode, an open authorization protocol is used for authentication, the base issues a token, and the subsystem uses a local independent user system after verifying the token, without triggering data synchronization.

[0021] By adopting the above technical solutions, differentiated access for business systems with different levels of informatization can be achieved, balancing the unified foundation with system autonomy, and reducing the cost of subsystem transformation and access.

[0022] As a further aspect of the present invention: the process by which the cross-cloud synchronization engine pushes the standard event message to the target system across clouds includes: pushing between public clouds and private clouds through a public network gateway, and pushing between private clouds and public clouds / private clouds through a security proxy.

[0023] By adopting the above technical solutions, a secure cross-cloud transmission channel is established to ensure the connectivity and security of personnel data synchronization in different network environments such as public cloud, private cloud, and private cloud.

[0024] As a further aspect of the present invention: in the multi-tenant mode, the tenant management module ensures that the data of different medical institutions are logically isolated from each other, and the employee ID relationship matching mapping table within each medical institution is stored and managed independently.

[0025] By adopting the above technical solutions, logical isolation and independent operation of data from multiple medical institutions can be achieved, ensuring the privacy, security, and independent matching of data for each tenant in the cloud model.

[0026] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention achieves accurate unification of personnel identities across multiple cloud systems through a multi-dimensional attribute weighting algorithm and AI model, solving the problem of low matching fault tolerance caused by inconsistent or missing employee IDs in heterogeneous systems, and constructing a unified employee master index.

[0027] 2. This invention achieves incremental synchronization through an event-driven mechanism, ensuring real-time data synchronization and conflict self-healing across clouds, and automatically resolves conflicts caused by concurrent modifications from multiple devices through a priority strategy, ensuring strong consistency of personnel base data.

[0028] 3. This invention is compatible with different business systems through three technical adaptation modes, supports multi-mode adaptive access and multi-tenant isolation, and realizes data logic isolation of multiple organizations, reducing transformation costs and ensuring data security.

[0029] Other features and advantages of the present invention will be disclosed in detail in the following detailed description and accompanying drawings. Attached Figure Description

[0030] Figure 1 This is a schematic diagram of the overall structure of a hospital clinical functional department personnel management system that supports multi-application cross-cloud deployment in an embodiment of the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] In this embodiment of the invention, a hospital clinical functional department personnel management system that supports multi-application cross-cloud deployment is described. (See also...) Figure 1 As shown, it includes five core modules: cross-cloud deployment module, personnel master index building module, cross-cloud synchronization engine, multi-mode adaptation module, and tenant management module.

[0033] 1. Personnel Master Index Construction Module This module is used to achieve unified matching of employees across different systems. Its core lies in a matching algorithm based on multi-dimensional attribute weighting and an AI identity resolution model.

[0034] (1) Multidimensional attribute weighted matching algorithm Obtain personnel information from heterogeneous systems and extract attribute features including employee ID, name, ID card number, mobile phone number, and department.

[0035] By inputting attribute data (data A), the existing main index attribute data of the base (data B), and the weight coefficients (coefficient C) corresponding to each attribute, the comprehensive similarity score F is obtained based on the similarity weighted calculation principle.

[0036] The calculation formula is: Where S is the overall similarity score. Let be the weight coefficient of the i-th attribute. The matching score for the i-th attribute.

[0037] The specific weight allocation is as follows: ID number weight. Name weight Mobile number weight Departmental weight Employee ID weight .

[0038] Attribute matching degree The value logic is as follows: if the attribute matches exactly, it is 1; if it does not match, it is 0. For text attributes, if there are typos, the edit distance algorithm is used to calculate the similarity and the value is between 0 and 1.

[0039] (2) Threshold grading determination logic The calculated S value is compared with the preset high threshold of 0.85 and the preset low threshold of 0.4: like If they are determined to be the same person, bind them to the existing primary index; like If it is determined to be a new user, a new primary index is generated; like If it falls into a gray area, it triggers the AI ​​identity resolution model to make a judgment.

[0040] (3) Training and inference of AI identity resolution model Training process: Collect historical personnel information mapping pairs to construct a dataset, which includes positive samples of information pairs of the same person in different systems and negative samples of information pairs of different people, and label them; Personnel attributes are transformed into feature vectors: text-type attributes use pinyin sequence and edit distance features, document-type attributes use regular expression extraction and comparison features, and category-type attributes use one-hot encoding. The extracted pinyin sequence features are flattened and concatenated with edit distance values, regular contrast Boolean values, and one-hot encoded sparse vectors at a fixed length to form a unified dimension fused feature vector, which serves as the input matrix for the extreme gradient boosting binary classification model. An extreme gradient boosting binary classification model is adopted, with feature vectors as input and the probability of whether they are the same person as output. Cross-entropy is used as the loss function to optimize the model parameters during training. The formula for the cross-entropy loss function is: .

[0041] Where N is the number of samples. For the true label, 0 or 1, This represents the probability value predicted by the model as belonging to the same person.

[0042] Reasoning process: The attributes of the people to be compared are converted into feature vectors and input into the trained model, and the probability value of each pair of people records belonging to the same person is output.

[0043] If the probability value is greater than the preset probability threshold, such as 0.5, it is determined to be the same person and the primary index is merged; otherwise, it is determined to be a new person and a new primary index is generated.

[0044] 2. Cross-cloud synchronization engine This module is used to achieve real-time data synchronization and conflict resolution in cross-cloud environments.

[0045] (1) Event-driven and message queue mechanisms When personnel information in the base or subsystem changes, the changes are encapsulated as a standard event message and pushed into the message queue.

[0046] The standard event message format includes: event type, employee master index ID, changed fields and values, timestamp, and source system identifier. Based on event subscription relationships, messages are pushed across the cloud to the target system, achieving incremental real-time synchronization.

[0047] (2) Data conflict resolution strategy If the same employee's master index is modified simultaneously on different deployment sites, the system obtains the timestamp of the modification operation and the priority of the source system. For example, the human resources system has the highest priority and is set to 1, while the nursing system has the second highest priority and is set to 2.

[0048] Comparison rules: Prioritize the source system's priority; change data from a system with a lower priority value will overwrite data from a system with a higher priority. If the priorities are the same, the newer timestamp will overwrite the older timestamp, and a conflict log will be recorded.

[0049] (3) Cross-cloud network push method Public clouds and private clouds push data through a public network gateway; private clouds and public or private clouds push data through a secure proxy to ensure data connectivity under the isolation of internal and external networks.

[0050] 3. Multi-mode adaptation module The application system on the base can be accessed in the following three modes: The first mode fully utilizes the foundational system: Subsystem business operation requests directly call the foundational API to read organizational structure and personnel data, and the subsystem does not store personnel tables locally.

[0051] The second mode retains its own system for employee ID matching: a mapping dictionary between local employee IDs and employee master indexes is generated through the personnel master index building module; when data changes, changes to the base system are pushed to the subsystem to update the local table, and changes to the subsystem are pushed to the base system to achieve bidirectional synchronization after being unified by the enterprise master index EMPI.

[0052] The third mode, login portal only: uses the OAuth2.0 protocol for authentication. The base acts as the authentication center to issue tokens. After the subsystem verifies the token, it uses a completely independent local user system without triggering any data synchronization.

[0053] 4. Tenant Management Module A multi-tenant model is implemented in both public and private cloud deployments, allowing different medical institutions to use the personnel database through registration. Data for each tenant is logically isolated, with mapping tables stored independently. In a private cloud deployment, the database is used only by the specific medical institution, enabling internal interaction within the institution.

[0054] 5. Cross-cloud deployment module This module provides basic operational support for the system in a multi-cloud environment, ensuring that the base system can flexibly choose the deployment architecture according to the size, compliance requirements, and current information technology status of the medical institution.

[0055] (1) Adaptation and operation in multi-cloud environments The system supports deployment and operation in three environments: public cloud, dedicated cloud, and private cloud. In the public cloud environment, the system provides services in a SaaS model, with multiple tenants sharing computing and storage resources to achieve quick out-of-the-box use. In the dedicated cloud environment, the system is deployed in an industry-specific cloud environment to meet the medical industry's requirements for data not leaving the domain and compliance. In the private cloud environment, the system is deployed in the local data center of the medical institution to achieve complete local control of core data and high-speed access to the intranet.

[0056] (2) Unified architecture and hybrid coexistence Regardless of the deployment method, the underlying system maintains a unified core architecture and API interface standard, ensuring that upper-layer business subsystems can be migrated between different cloud environments without code modification. Simultaneously, it supports the use of hybrid cloud architectures by the same medical institution at different stages of development; for example, the core human resources system may be deployed on a private cloud, while the SaaS nursing system may be deployed on a public cloud. The underlying system ensures the alignment of personnel information and the interoperability of processes between the two through a cross-cloud synchronization engine.

[0057] (3) Cross-cloud network infrastructure support Provides underlying network connectivity guarantees for cross-cloud synchronization engines. Configures corresponding network policies for the security boundaries of different cloud environments: public cloud and private cloud communicate through open public network gateway interfaces; and deploys security proxies, such as VPNs or dedicated line proxies, to establish encrypted tunnels between private cloud and public / dedicated cloud environments, ensuring secure data transmission channels in isolated internal and external network environments.

[0058] Example 1 A provincial health commission built a personnel management platform deployed on a private cloud. Hospital A under its jurisdiction uses a privately deployed nursing system, while Hospital B directly uses a public cloud SaaS nursing system.

[0059] Step 1: Multi-tenant registration and system access Hospital A and Hospital B are registered tenants on a dedicated cloud platform, with data logically isolated. Hospital B directly adopts the first mode to access the SaaS nursing system, fully utilizing the platform's organizational structure. Hospital A's private cloud nursing system adopts the second mode, retaining its own personnel system and generating a mapping dictionary by matching local employee IDs with the platform's main index via API.

[0060] Step 2: Building the Master Index for Personnel The nursing system of Hospital A transmitted information about Nurse Li Si: Employee ID: A-N001, Name: Li Si, ID Card Number: 3301...1234, Mobile Phone Number: 138...5678, Department: Internal Medicine.

[0061] After the base receives the data, it extracts multidimensional features and calculates the score according to the weighting formula. Assuming the system already has a record of Li Si in the medical system, with ID number 3301...1234 and name Li Si, then the ID matching... Name matching Overall score .

[0062] because This triggers the AI ​​identity resolution model; the model extracts feature vectors such as pinyin and regular expressions, inputs them into the XGBoost model, and outputs a probability value of 0.89, which is greater than 0.5, indicating that it is the same person. The base binds A-N001 of the nursing system of Hospital A with the existing EMPI to achieve identity unification.

[0063] Step 3: Cross-cloud real-time synchronization and conflict resolution Hospital A's personnel system, high priority, value 1; Hospital A's nursing system, low priority, value 2; and Li Si's department information was also modified.

[0064] The HR system was changed to Surgery, and the Nursing system was changed to Emergency. The two change events were encapsulated as messages and pushed into the private cloud message queue through a security broker. The base's cross-cloud synchronization engine detected the conflict, extracted the timestamp and priority, determined that the HR system's priority 1 was higher than the Nursing system's priority 2, and finally updated the base's main index to Surgery. This result was synchronized to the Nursing system to overwrite its Emergency records, and was also written to the conflict log.

[0065] Example 2 Hospital C previously used a third-party, outdated infection control system in Mode 3, serving only as a login portal. This outdated system did not synchronize data with the platform. With the hospital's evolving needs, Hospital C purchased a new infection control system and required unified management through the platform. During implementation, the access mode of the new infection control system was switched from Mode 3 to Mode 2. The platform enabled bidirectional synchronization logic through a multi-mode adaptation module. Login to the outdated system remained unaffected, while the new system synchronized personnel data bidirectionally with the platform via a mapping dictionary. This achieved a smooth transition during the information system upgrade process and ensured business continuity.

[0066] Example 3 The difference between this embodiment and Embodiment 1 is that during the construction of the main index of personnel, when the comprehensive similarity score is between 0.4 and 0.85, the AI ​​identity resolution model is triggered to make a judgment. Specifically, the attributes of the personnel to be compared are converted into feature vectors: text attributes such as the pinyin sequence features of the names "Li Si" and "Li Si" are flattened and compared with the edit distance value of 0.8, the regular Boolean value (1) of the document attributes such as the ID card number, and the one-hot code ([0,1,0]) of the category attributes such as the department, and a fixed-length concatenation is performed to form a unified dimension fusion feature vector [0.8,1,0,0.8,1,0], which is input into the extreme gradient boosting binary classification model. The output probability value is 0.89, which is greater than 0.5, and it is determined to be the same person and the main index is merged.

[0067] Meanwhile, during cross-cloud synchronization, when both the HR system (priority 1) and the nursing system (priority 2) modify Li Si's department information, the cross-cloud synchronization engine obtains the timestamp of the modification operation, such as HR system: 2023-05-20 10:00:00, nursing system: 2023-05-20 10:00:05, and the priority of the source system. It prioritizes HR system (priority 1) over nursing system (priority 2), and finally updates the base main index to surgery. This result is synchronized to the nursing system to overwrite its emergency records, and a conflict log is recorded: "2023-05-20 10:00:05, nursing system modification overwritten, source system: HR system (priority 1)".

[0068] In addition, regarding multi-mode adaptation, the third mode adopts the OAuth2.0 protocol: the new version of the hospital infection control system requests a token from the base station, the base station verifies the token and issues the token, and the hospital infection control system verifies the token and uses a local independent user system without triggering any data synchronization.

[0069] In terms of tenant management, the data of Hospital A and Hospital B are logically isolated from each other, and the employee ID mapping tables of Hospital A and Hospital B are stored independently to ensure the data privacy and security of each medical institution.

[0070] In one feasible embodiment, the employee number mapping table for Hospital A is: A-N001→EMPI-001; and the employee number mapping table for Hospital B is: B-N001→EMPI-002.

[0071] This embodiment further improves the accuracy, consistency and security of the system through feature engineering optimization, conflict resolution strategies and OAuth2.0 integration, and solves the problems of identity management and data synchronization in complex medical scenarios.

[0072] Example 4 The difference between this embodiment and Embodiment 1 is that a dynamic weight adjustment mechanism is used during the construction of the personnel master index.

[0073] For example, in emergency scenarios, the weight of professional qualifications, such as the doctor's license number, will be increased from 0.3 to 0.5, the weight of professional titles, such as chief physician, will be increased from 0.2 to 0.4, while the weight of department will be decreased from 0.15 to 0.1.

[0074] When nurse Li Si, employee number A-N001, enters information, if her professional qualifications match the existing records in the database, the weight is 0.5. Even if the department information is slightly different, the weight is 0.1. If the overall score is still higher than the threshold, it is determined to be the same person.

[0075] Meanwhile, in the cross-cloud deployment, Li Si's patient diagnosis records (sensitive data) are stored in Hospital A's private cloud, while organizational structure information (non-sensitive data) is synchronized to the public cloud. Sensitive data is protected using AES-256 encryption technology, and audit logs are generated, such as "2023-05-20 10:00:00, private cloud storage of patient diagnosis records, access permissions: only Hospital A's personnel system".

[0076] In multi-tenant collaboration, Hospital B's public cloud SaaS nursing system needs expert support from Hospital A. It applies to share Li Si's expert qualification information through the tenant management module, and anonymizes it to only display "Chief Physician".

[0077] After approval by Hospital A, the shared data is pushed to Hospital B through a secure proxy to ensure privacy and security.

[0078] In resolving cross-cloud synchronization conflicts, if the HR system (regular outpatient, priority 2) and the emergency system (priority 1) modify Li Si's department information at the same time, the cross-cloud synchronization engine will prioritize the emergency system over the regular outpatient system based on business logic priority, and will prioritize the changed data from the emergency system, such as the emergency department, overwriting the internal medicine records in the HR system to ensure the consistency of emergency business data.

[0079] This embodiment addresses issues related to identity matching, data security, cross-hospital collaboration, and consistency of critical business processes in the medical setting through dynamic weight adjustment, medical data compliance processing, multi-tenant business collaboration, and business logic-driven conflict resolution.

[0080] This invention provides a hospital clinical functional department personnel management system that supports multi-application cross-cloud deployment, enabling process interoperability and information alignment between upper-level business subsystems and different modules, ensuring business continuity.

[0081] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0082] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A hospital clinical functional department personnel management system that supports multi-application cross-cloud deployment, characterized in that: include: A cross-cloud deployment module is used to support the deployment of the system on public clouds, dedicated clouds, and private clouds; The personnel master index construction module is used for top-level unified design of the personnel system architecture of different departments in medical institutions, constructing a master index of employees in the hospital's clinical functional departments, and realizing unified matching of employees between different systems and different deployment methods. The personnel master index construction module performs employee master index matching based on multi-dimensional attribute weighting, including: Obtain personnel information from heterogeneous systems and extract multi-dimensional attribute features including employee ID, name, ID card number, mobile phone number, and department; By combining the input attribute data with the existing main index attribute data of the base and the weight coefficients corresponding to each attribute, a comprehensive similarity score is obtained based on the similarity weighted calculation principle. The weight coefficient of the ID number is 0.4 and the weight coefficient of the name is 0.

2. When the comprehensive similarity score is between a preset high threshold and a preset low threshold, the AI ​​identity resolution model is triggered to make a judgment. The AI ​​identity resolution model converts the attributes of the people to be compared into feature vectors, inputs them into a machine learning binary classification model, and outputs the probability value that each pair of people records belongs to the same person. If the probability value is greater than the preset probability threshold, it is determined to be the same person and the main index is merged; otherwise, it is determined to be a new person and a new main index is generated. The multi-mode adaptation module allows business systems on the platform to access the platform in three modes: the first mode is to fully utilize the organizational structure and personnel management system of the platform; the second mode is to retain the platform's own personnel management system, match employee IDs, unify personnel identities, and maintain the platform's own organizational structure; the third mode is to use the platform only as an application login portal, fully retaining the platform's own organizational structure and user system. The tenant management module is used to implement a multi-tenant mode in public cloud and private cloud deployments. Different medical institutions can use the departmental organizational relationship and personnel master index of the personnel base through registration, and match the relationship between the personnel ID and the existing system of the medical institution. In the private cloud deployment, it is used by the medical institution itself and realizes the interaction of employee information with other systems within the institution.

2. The hospital clinical functional department personnel management system supporting multi-application cross-cloud deployment according to claim 1, characterized in that, The personnel master index construction module performs employee master index matching based on dynamic weight adjustment, specifically including: dynamically adjusting the weight coefficients according to the importance of attributes in the medical scenario, where the weight of professional title is higher than that of department, the weight of professional qualification is higher than that of mobile phone number, and the weight allocation is adjusted in real time based on business scenarios such as emergency and regular outpatient clinics.

3. The hospital clinical functional department personnel management system supporting multi-application cross-cloud deployment as described in claim 1, characterized in that, The cross-cloud deployment module stores sensitive medical data, such as patient information and diagnostic records, in a private cloud, while processing non-sensitive data, such as organizational structure and basic personnel information, in a public cloud. It combines encryption technology and audit logs to ensure the compliance of medical data.

4. The hospital clinical functional department personnel management system supporting multi-application cross-cloud deployment according to claim 1, characterized in that, The tenant management module supports multi-tenant business collaboration, specifically including: on the basis of logical isolation of tenant data, temporary collaboration between different medical institutions can be achieved through access control and data anonymization, sharing limited data.

5. The hospital clinical functional department personnel management system supporting multi-application cross-cloud deployment according to claim 1, characterized in that, The system also includes a cross-cloud synchronization engine for performing bidirectional real-time cross-cloud synchronization based on event-driven and message queues. When personnel information in the base and subsystems changes, the changes are encapsulated into standard event messages and pushed into the message queue. Based on the event subscription relationship, the standard event messages are pushed across clouds to the target system to achieve incremental real-time synchronization.

6. The hospital clinical functional department personnel management system supporting multi-application cross-cloud deployment according to claim 5, characterized in that, The cross-cloud synchronization engine executes a conflict resolution strategy driven by business logic, specifically including: adjusting conflict judgment rules based on medical business priorities, prioritizing the handling of data changes related to high-priority businesses, and ensuring the consistency of critical medical data.

7. The hospital clinical functional department personnel management system supporting multi-application cross-cloud deployment according to claim 5, characterized in that, The cross-cloud synchronization engine also executes a data conflict resolution strategy: if the same employee's master index is modified simultaneously on different deployment terminals, the timestamp of the modification operation and the priority of the source system are obtained; Based on the timestamp and source system priority determination rules, the source system priority is first determined. When the priorities are the same, the timestamp is then determined. The change data of the high-priority source system is used to overwrite the change data of the low-priority source system, and the conflict log is recorded.

8. The hospital clinical functional department personnel management system supporting multi-application cross-cloud deployment according to claim 5, characterized in that, The process by which the cross-cloud synchronization engine pushes the standard event messages to the target system across clouds includes: pushing between public clouds and private clouds through a public network gateway, and pushing between private clouds and public clouds / private clouds through a security proxy.

9. The hospital clinical functional department personnel management system supporting multi-application cross-cloud deployment according to claim 1, characterized in that, The multi-mode adaptation module executes different technical logic for the three modes: In the first mode, the subsystem business operation request directly calls the base interface to read the organizational structure and personnel data, and the subsystem does not store the personnel table locally; In the second mode, the local employee ID and employee master index mapping dictionary is generated through the personnel master index building module, and bidirectional synchronization is performed through the cross-cloud synchronization engine when data changes; In the third mode, an open authorization protocol is used for authentication, the base issues a token, and the subsystem uses a local independent user system after verifying the token, without triggering data synchronization.

10. The hospital clinical functional department personnel management system supporting multi-application cross-cloud deployment according to claim 1, characterized in that, In the multi-tenant mode, the tenant management module logically isolates the data of different medical institutions, and the employee ID relationship matching mapping table within each medical institution is stored and managed independently.

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