Early warning management method for suspected tuberculosis cases

Abstract

The invention relates to tuberculosis early warning, in particular to an early warning management method for suspected tuberculosis cases, which comprises the following steps of: carrying out standardized coding system design on a pulmonary tuberculosis examination institution, a jurisdiction fixed-point institution, a jurisdiction fixed-point institution department, a jurisdiction fixed-point institution doctor and an early warning management system workstation, and carrying out warehousing management on related information; setting a database table and a corresponding index; determining a contrast relationship between the pulmonary tuberculosis examination institution and the jurisdiction fixed-point institution, and a logic relationship between a jurisdiction fixed-point institution department to which a jurisdiction fixed-point institution doctor belongs and an early warning management system workstation to which the jurisdiction fixed-point institution department belongs; when the pulmonary tuberculosis examination institution judges that a suspected tuberculosis case appears, early warning bubbles are pushed through an early warning management system work station to remind a designated jurisdiction fixed-point institution department and a designated jurisdiction fixed-point institution doctor, and whole-process state management is carried out; according to the technical scheme provided by the invention, the defect that efficient early warning management is difficult to carry out on suspected tuberculosis cases in the prior art can be effectively overcome.

Description

Technical Field

[0001] The present invention relates to tuberculosis early warning, and in particular to an early warning management method for suspected tuberculosis cases. Background Art

[0002] Tuberculosis (TB) is a major infectious disease that severely endangers public health and poses a significant challenge to global public health. In 2023, there were 10.8 million new TB cases worldwide, with an incidence rate of approximately 134 cases per 100,000 people. Among all new cases, 662,000, or approximately 6.1%, were coinfected with HIV; and 400,000, or approximately 3.7%, were diagnosed with multidrug-resistant / rifampicin-resistant TB.

[0003] Early warning management of suspected tuberculosis cases is an effective means to prevent the spread of tuberculosis, but existing technical solutions have the following main problems:

[0004] 1) Inefficient diagnosis: Primary healthcare institutions lack intelligent analysis tools and rely on manual analysis of medical images, resulting in delayed responses.

[0005] 2) Disconnected patient management: There is a lack of automated connection between screening results and review notifications, which can easily lead to missed diagnoses and missed management;

[0006] 3) Difficulty in data collaboration: There is a serious phenomenon of information silos between medical institutions, making it impossible to achieve real-time sharing and tracking of screening data;

[0007] 4) Lack of early warning mechanism: Existing technical solutions are unable to actively identify suspected tuberculosis cases and provide graded early warning, resulting in a low detection rate. Summary of the Invention

[0008] (1) Technical problems solved

[0009] In view of the above-mentioned shortcomings of the prior art, the present invention provides a method for early warning management of suspected tuberculosis cases, which can effectively overcome the defect of the prior art that it is difficult to carry out efficient early warning management of suspected tuberculosis cases.

[0010] (2) Technical solution

[0011] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0012] A method for early warning management of suspected tuberculosis cases, comprising the following steps:

[0013] S1. Design a standardized coding system for tuberculosis examination institutions, designated institutions in the jurisdiction, departments of designated institutions in the jurisdiction, doctors of designated institutions in the jurisdiction, and early warning management system workstations to achieve effective correspondence between different data;

[0014] S2. Manage the information of tuberculosis examination institutions, designated institutions in the jurisdiction, departments of designated institutions in the jurisdiction, doctors of designated institutions in the jurisdiction, and workstations of the early warning management system, and set up database tables and corresponding indexes to improve data query efficiency;

[0015] S3. Determine the mapping relationship between pulmonary tuberculosis examination institutions and designated institutions within the jurisdiction, as well as the logical relationship between the departments of designated institutions to which doctors of designated institutions within the jurisdiction belong and the early warning management system workstations to which departments of designated institutions within the jurisdiction belong;

[0016] S4. When a tuberculosis examination agency determines that a suspected tuberculosis case has occurred, it will push a warning bubble reminder to the designated departments and doctors of the designated institutions in the jurisdiction through the early warning management system workstation, and conduct full-process status management.

[0017] Preferably, in S1, a standardized coding system is designed for tuberculosis examination institutions, designated institutions in the jurisdiction, departments of designated institutions in the jurisdiction, doctors of designated institutions in the jurisdiction, and early warning management system workstations to achieve effective correspondence between different data, including:

[0018] Reminder rule management supports the setting of a one-to-many mapping relationship between tuberculosis inspection institutions and designated institutions in the jurisdiction, and supports the addition, deletion, modification and query of the mapping relationship between tuberculosis inspection institutions and designated institutions in the jurisdiction;

[0019] Dictionary management supports dictionary management for designated departments in the jurisdiction, supports addition, deletion, modification and query of dictionaries and dictionary details, and supports batch import;

[0020] Role management supports role management of doctors in designated institutions within the jurisdiction, supports adding, deleting, modifying and checking roles, and supports setting menu permissions and menu homepage;

[0021] User management: supports user management of doctors in designated institutions within the jurisdiction, and supports enabling / disabling users;

[0022] Workstation management supports the management of early warning management system workstations, binds MAC addresses and IP segments to ensure the uniqueness of physical terminals, and supports enabling / disabling operations on early warning management system workstations.

[0023] Preferably, S2 stores and manages information on tuberculosis examination institutions, designated institutions in the jurisdiction, departments of designated institutions in the jurisdiction, doctors of designated institutions in the jurisdiction, and workstations of the early warning management system, including:

[0024] Select a suitable database management system according to needs, and store and manage the information of tuberculosis examination institutions, designated institutions in the jurisdiction, department dictionaries of designated institutions in the jurisdiction, doctor roles of designated institutions in the jurisdiction, doctor users of designated institutions in the jurisdiction and early warning management system workstations, as well as the comparison relationship between tuberculosis examination institutions and designated institutions in the jurisdiction.

[0025] Preferably, a database table and corresponding index are set in S2 to improve data query efficiency, including:

[0026] Design the database table structure and determine the relationship between database tables;

[0027] Create databases and tables in the database management system and set corresponding indexes to improve data query efficiency. Build B+ tree indexes for frequently queried fields to control query latency to less than 10ms.

[0028] Import the encoded data into the database and perform integrity and consistency checks;

[0029] Among them, AES-256 encryption is used to store sensitive data including patient personal information, and change data capture CDC is used to achieve real-time synchronization of cross-institutional data, and network delays are tolerated within 1 minute.

[0030] Preferably, when the tuberculosis examination institution in S4 determines that a suspected tuberculosis case occurs, a warning bubble reminder is pushed to the designated department and doctor of the designated institution in the jurisdiction through the early warning management system workstation, and full-process status management is carried out, including:

[0031] When the tuberculosis examination agency determines that the patient's medical imaging is within the threshold range for suspected tuberculosis cases, the early warning management system conducts AI screening and automatically selects a matching designated institution in the jurisdiction using a weighted-priority institution matching strategy;

[0032] The early warning management system pushes warning bubble reminders to designated departments and doctors of designated institutions in the jurisdiction through the early warning management system workstation, and conducts full-process status management.

[0033] Preferably, the early warning management system pushes early warning bubble reminders to designated departments and doctors of designated institutions in the jurisdiction through the early warning management system workstation, and performs full-process status management, including:

[0034] Define the status flow rules of "suspected - notification - re-examination - confirmed / excluded", record a complete operation log for each status change, support rollback based on time windows, and trigger a secondary confirmation mechanism for abnormal operations to prevent the spread of erroneous operations;

[0035] Doctors at designated institutions in the jurisdiction can directly open the warning bubble to view the AI ​​screening suspected list, exclude suspected tuberculosis cases from the AI ​​screening suspected list, notify patients for re-examination via SMS, and view AI screening details.

[0036] Preferably, patients who have been sent SMS notifications will be added to the SMS notification list, where doctors at designated institutions in the jurisdiction will exclude suspected tuberculosis cases, confirm tuberculosis cases, send SMS notifications to patients for reexamination, and view AI screening details.

[0037] The content of the SMS is a unified template configured by the early warning management system, which can automatically configure variables including the patient's name, the name of the tuberculosis examination institution, the name of the designated institution in the jurisdiction, and the telephone number of the designated institution in the jurisdiction;

[0038] Doctors at designated institutions in the jurisdiction can click the SMS notification button with one click, and after a second confirmation, quickly send it to the patient.

[0039] Preferably, suspected tuberculosis cases excluded by the operation of excluding suspected tuberculosis cases will be included in the excluded suspected list, and tuberculosis cases confirmed by the operation of confirming tuberculosis cases will be included in the confirmed tuberculosis list;

[0040] Among them, list query implements a multi-level caching strategy to support high concurrent access.

[0041] (3) Beneficial effects

[0042] Compared with the existing technology, the early warning management method for suspected tuberculosis cases provided by the present invention has the following beneficial effects:

[0043] 1) Build a coding system and matching mechanism for a collaborative network of medical institutions. Through a unique six-level coding architecture consisting of "TB examination institution - designated institution in the jurisdiction - department dictionary of designated institution in the jurisdiction - doctor role of designated institution in the jurisdiction - doctor user of designated institution in the jurisdiction - early warning management system workstation," this system enables precise routing of cross-institutional data, thereby achieving accurate matching of suspected TB cases with responsible doctors, effectively solving the inefficiency caused by traditional manual allocation.

[0044] 2) Create a two-way interactive mechanism for intelligent early warning, breaking new ground by converting AI analysis and screening results into actionable clinical workflows in real time. This includes a three-in-one interactive design featuring early warning bubble reminders, SMS notifications, and full-process status management, achieving closed-loop interaction.

[0045] 3) Form a state machine model for closed-loop management, ensuring full process traceability through a four-state transition mechanism of "suspected - notified - retested - confirmed / excluded";

[0046] 4) Achieve digital tracking of the entire process of "screening-warning-disposition-feedback", especially through workstation-level precise push and automatic status rollback mechanism, effectively solving the dual problems of "excessive warning" and "disconnected disposition" common in existing technical solutions;

[0047] 5) Realize intelligent management of the entire process from initial screening and warning to confirmed treatment, and effectively improve the early detection rate and standardized management rate of tuberculosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0049] Figure 1 It is a schematic diagram of the process of the present invention;

[0050] Figure 2 This is a schematic diagram of the present invention in which warning bubble reminders are pushed to designated departments and doctors of designated institutions in the jurisdiction through the early warning management system workstation, and full-process status management is carried out. DETAILED DESCRIPTION

[0051] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0052] An early warning management method for suspected tuberculosis cases, such as Figure 1 As shown in S1, a standardized coding system is designed for tuberculosis examination institutions, designated institutions in the jurisdiction, departments of designated institutions in the jurisdiction, doctors of designated institutions in the jurisdiction, and early warning management system workstations to achieve effective correspondence between different data, including:

[0053] Reminder rule management supports the setting of a one-to-many mapping relationship between tuberculosis inspection institutions and designated institutions in the jurisdiction, and supports the addition, deletion, modification and query of the mapping relationship between tuberculosis inspection institutions and designated institutions in the jurisdiction;

[0054] Dictionary management supports dictionary management for designated departments in the jurisdiction, supports addition, deletion, modification and query of dictionaries and dictionary details, and supports batch import;

[0055] Role management supports role management of doctors in designated institutions within the jurisdiction, supports adding, deleting, modifying and checking roles, and supports setting menu permissions and menu homepage;

[0056] User management: supports user management of doctors in designated institutions within the jurisdiction, and supports enabling / disabling users;

[0057] Workstation management supports the management of early warning management system workstations, binds MAC addresses and IP segments to ensure the uniqueness of physical terminals, and supports enabling / disabling operations on early warning management system workstations.

[0058] S2. Manage the information of tuberculosis examination institutions, designated institutions in the jurisdiction, departments of designated institutions in the jurisdiction, doctors of designated institutions in the jurisdiction and workstations of early warning management system in the database, and set up database tables and corresponding indexes to improve data query efficiency.

[0059] Specifically, information on tuberculosis examination institutions, designated institutions within the jurisdiction, departments within the jurisdiction, doctors within the jurisdiction, and early warning management system workstations is stored and managed, including:

[0060] Select a suitable database management system (such as MySQL, PostgreSQL, etc.) according to needs, and store and manage the information of tuberculosis examination institutions, designated institutions in the jurisdiction, department dictionaries of designated institutions in the jurisdiction, doctor roles of designated institutions in the jurisdiction, doctor users of designated institutions in the jurisdiction and early warning management system workstations, as well as the comparison relationship between tuberculosis examination institutions and designated institutions in the jurisdiction.

[0061] Specifically, set up database tables and corresponding indexes to improve data query efficiency, including:

[0062] Design the database table structure and determine the relationship between database tables;

[0063] Create databases and tables in the database management system and set corresponding indexes to improve data query efficiency. Build B+ tree indexes for frequently queried fields (such as org_id and ws_id) to control query latency to less than 10ms.

[0064] Import the encoded data into the database and perform integrity and consistency checks;

[0065] Among them, AES-256 encryption is used to store sensitive data including patient personal information, and change data capture CDC is used to achieve real-time synchronization of cross-institutional data, and network delays are tolerated within 1 minute.

[0066] S3. Determine the correspondence between the tuberculosis examination institutions and the designated institutions in the jurisdiction, as well as the logical relationship between the departments of the designated institutions to which the doctors of the designated institutions in the jurisdiction belong and the early warning management system workstations to which the departments of the designated institutions in the jurisdiction belong.

[0067] S4. When a suspected tuberculosis case is identified by the pulmonary tuberculosis examination agency, a warning bubble reminder will be pushed to the designated department and doctor of the designated institution in the jurisdiction through the early warning management system workstation, and the whole process status management will be carried out, such as Figure 2 As shown, specifically including:

[0068] When the tuberculosis examination agency determines that the patient's medical imaging is within the threshold range for suspected tuberculosis cases, the early warning management system conducts AI screening and automatically selects a matching designated institution in the jurisdiction using a weighted-priority institution matching strategy;

[0069] The early warning management system pushes early warning bubble reminders (using real-time push technology to ensure delivery within seconds) to designated departments and doctors of designated institutions in the jurisdiction through the early warning management system workstation, and conducts full-process status management.

[0070] Specifically, the early warning management system pushes early warning bubble reminders to the designated departments and doctors of designated institutions in the jurisdiction through the early warning management system workstation, and conducts full-process status management, such as Figure 2 Shown, including:

[0071] Define the status flow rules of "suspected - notification - re-examination - confirmed / excluded", record a complete operation log for each status change, support rollback based on time windows, and trigger a secondary confirmation mechanism for abnormal operations to prevent the spread of erroneous operations;

[0072] Doctors at designated institutions in the jurisdiction can directly open the warning bubble to view the AI ​​screening suspected list, exclude suspected tuberculosis cases from the AI ​​screening suspected list, notify patients for re-examination via SMS, and view AI screening details.

[0073] In the technical solution of this application, patients who have already received SMS notifications will be added to the SMS notification list. Doctors at designated institutions in the jurisdiction will exclude suspected tuberculosis cases, confirm tuberculosis cases, send SMS notifications to patients for reexamination, and view AI screening details in the SMS notification list.

[0074] The content of the SMS is a unified template configured by the early warning management system, which can automatically configure variables including the patient's name, the name of the tuberculosis examination institution, the name of the designated institution in the jurisdiction, and the telephone number of the designated institution in the jurisdiction;

[0075] Doctors at designated institutions in the jurisdiction can click the SMS notification button with one click, and quickly send it to patients after secondary confirmation, making the review SMS notification intelligent and efficient.

[0076] In the technical solution of this application, suspected tuberculosis cases that have been excluded through the operation of excluding suspected tuberculosis cases will be included in the excluded suspected list, and tuberculosis cases that have been confirmed through the operation of confirming tuberculosis cases will be included in the confirmed tuberculosis list;

[0077] Among them, list query implements a multi-level caching strategy to support high concurrent access.

[0078] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for early warning management of suspected tuberculosis cases, characterized by: The following steps are involved: S1. Design a standardized coding system for tuberculosis examination institutions, designated institutions in the jurisdiction, departments of designated institutions in the jurisdiction, doctors of designated institutions in the jurisdiction, and early warning management system workstations to achieve effective correspondence between different data; S2. Manage the information of tuberculosis examination institutions, designated institutions in the jurisdiction, departments of designated institutions in the jurisdiction, doctors of designated institutions in the jurisdiction, and workstations of the early warning management system, and set up database tables and corresponding indexes to improve data query efficiency; S3. Determine the mapping relationship between pulmonary tuberculosis examination institutions and designated institutions within the jurisdiction, as well as the logical relationship between the departments of designated institutions to which doctors of designated institutions within the jurisdiction belong and the early warning management system workstations to which departments of designated institutions within the jurisdiction belong; S4. When a tuberculosis examination agency determines that a suspected tuberculosis case has occurred, it will push a warning bubble reminder to the designated departments and doctors of the designated institutions in the jurisdiction through the early warning management system workstation, and conduct full-process status management.

2. The early warning management method for suspected tuberculosis cases according to claim 1, characterized in that: In S1, a standardized coding system is designed for tuberculosis examination institutions, designated institutions in the jurisdiction, departments of designated institutions in the jurisdiction, doctors of designated institutions in the jurisdiction, and early warning management system workstations to achieve effective correspondence between different data, including: Reminder rule management supports the setting of a one-to-many mapping relationship between tuberculosis inspection institutions and designated institutions in the jurisdiction, and supports the addition, deletion, modification and query of the mapping relationship between tuberculosis inspection institutions and designated institutions in the jurisdiction; Dictionary management supports dictionary management for designated departments in the jurisdiction, supports addition, deletion, modification and query of dictionaries and dictionary details, and supports batch import; Role management supports role management of doctors in designated institutions within the jurisdiction, supports adding, deleting, modifying and checking roles, and supports setting menu permissions and menu homepage; User management: supports user management of doctors in designated institutions within the jurisdiction, and supports enabling / disabling users; Workstation management supports the management of early warning management system workstations, binds MAC addresses and IP segments to ensure the uniqueness of physical terminals, and supports enabling / disabling operations on early warning management system workstations.

3. The early warning management method for suspected tuberculosis cases according to claim 2, characterized in that: S2 stores and manages information on tuberculosis examination institutions, designated institutions within the jurisdiction, departments within the jurisdiction, doctors within the jurisdiction, and early warning management system workstations, including: Select a suitable database management system according to needs, and store and manage the information of tuberculosis examination institutions, designated institutions in the jurisdiction, department dictionaries of designated institutions in the jurisdiction, doctor roles of designated institutions in the jurisdiction, doctor users of designated institutions in the jurisdiction and early warning management system workstations, as well as the comparison relationship between tuberculosis examination institutions and designated institutions in the jurisdiction.

4. The early warning management method for suspected tuberculosis cases according to claim 3, characterized in that: Set up database tables and corresponding indexes in S2 to improve data query efficiency, including: Design the database table structure and determine the relationship between database tables; Create databases and tables in the database management system and set corresponding indexes to improve data query efficiency. Build B+ tree indexes for frequently queried fields to control query latency to less than 10ms. Import the encoded data into the database and perform integrity and consistency checks; Among them, AES-256 encryption is used to store sensitive data including patient personal information, and change data capture CDC is used to achieve real-time synchronization of cross-institutional data, and network delays are tolerated within 1 minute.

5. The early warning management method for suspected tuberculosis cases according to claim 1, characterized in that: When a suspected tuberculosis case is identified by the pulmonary tuberculosis examination agency in S4, a warning bubble reminder is pushed to the designated departments and doctors of designated institutions in the jurisdiction through the early warning management system workstation, and full-process status management is carried out, including: When the tuberculosis examination agency determines that the patient's medical imaging is within the threshold range for suspected tuberculosis cases, the early warning management system conducts AI screening and automatically selects a matching designated institution in the jurisdiction using a weighted-priority institution matching strategy; The early warning management system pushes warning bubble reminders to designated departments and doctors of designated institutions in the jurisdiction through the early warning management system workstation, and conducts full-process status management.

6. The early warning management method for suspected tuberculosis cases according to claim 5, characterized in that: The early warning management system pushes early warning bubble reminders to designated departments and doctors of designated institutions in the jurisdiction through the early warning management system workstation, and conducts full-process status management, including: Define the status flow rules for "suspected - notification - re-examination - confirmed / excluded". Record a complete operation log for each status change, support time window-based rollback, and trigger a secondary confirmation mechanism for abnormal operations to prevent the spread of erroneous operations. Doctors at designated institutions in the jurisdiction can directly open the warning bubble to view the AI ​​screening suspected list, exclude suspected tuberculosis cases from the AI ​​screening suspected list, notify patients for re-examination via SMS, and view AI screening details.

7. The early warning management method for suspected tuberculosis cases according to claim 6, characterized in that: For patients who have been sent SMS notifications, they will be added to the SMS notification list. Doctors at designated institutions in the jurisdiction will exclude suspected tuberculosis cases, confirm tuberculosis cases, send SMS notifications to patients for re-examination, and view AI screening details in the SMS notification list. The content of the SMS is a unified template configured by the early warning management system, which can automatically configure variables including the patient's name, the name of the tuberculosis examination institution, the name of the designated institution in the jurisdiction, and the telephone number of the designated institution in the jurisdiction; Doctors at designated institutions in the jurisdiction can click the SMS notification button with one click, and after a second confirmation, quickly send it to the patient.

8. The early warning management method for suspected tuberculosis cases according to claim 7, characterized in that: Suspected TB cases that have been excluded through the procedure for excluding suspected TB cases will be placed in the excluded suspected list; confirmed TB cases that have been confirmed through the procedure for confirming TB cases will be placed in the confirmed TB list. Among them, list query implements a multi-level caching strategy to support high concurrent access.

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