A hospital price supervision system

Abstract

This invention relates to the field of medical management technology, specifically disclosing a hospital pricing supervision system, including modules for multi-source data fusion and acquisition, policy-item intelligent matching, dynamic verification and early warning, policy response and automatic updating, interactive and statistical analysis, and data security assurance. The multi-source data module collects and standardizes in-hospital treatment information and external policy data; the intelligent matching module uses NLP technology to match and score items with charges; the dynamic verification module uses triple verification to issue graded early warnings for abnormal charges; the policy update module automatically identifies policies and updates parameters in advance; the interactive analysis module provides visual operation and multi-dimensional reports; and the data security module ensures data encryption and access control. This invention significantly improves policy response speed and matching accuracy, reduces the risk of medical insurance refusal to pay, ensures charging compliance, and provides data support for optimizing hospital pricing management.

Description

Technical Field

[0001] This invention relates to the field of medical management technology, specifically to a hospital price monitoring system. Background Technology

[0002] Price management is a crucial aspect of current hospital operations. However, the existing hospital price management model, which relies heavily on manual processes, has numerous drawbacks. Price policies are characterized by rapid updates and wide-ranging impacts, such as adjustments to medical insurance payment standards and pricing for new medical services. Manually updating fee standards often leads to omissions or delays, potentially causing discrepancies between hospital charges and relevant policies, and consequently triggering a series of problems.

[0003] Meanwhile, the matching of medical services and their corresponding charge codes relies on manual judgment. Because some medical service names are similar and the charge code rules are complex, mismatches are easily made. Such mismatches can not only lead to billing disputes but may also result in medical insurance refusal to reimburse, causing economic losses and reputational damage to hospitals.

[0004] In addition, traditional price management methods cannot monitor charges in real time, and abnormal charging behaviors such as overcharging and double charging cannot be detected and warned in a timely manner, which undoubtedly increases the operational risks of hospitals.

[0005] Therefore, a hospital price supervision system has become an urgent problem to be solved. Summary of the Invention

[0006] The purpose of this invention is to provide a hospital price monitoring system that overcomes the problems of low efficiency, large matching errors, delayed policy response, and difficulty in monitoring abnormal charges caused by the reliance on manual operation in hospital price management in the prior art.

[0007] To solve the above-mentioned technical problems, the technical solution provided by the present invention is: a hospital price supervision system, including a multi-source data fusion and acquisition module, a policy-project intelligent matching module, a dynamic verification and early warning module, a policy response and automatic update module, and an interaction and statistical analysis module; The multi-source data fusion acquisition module is used to collect information on diagnosis and treatment items, price policy documents, and supplementary pricing regulations made by the hospital, and stores the collected data after standardization processing; The policy-project intelligent matching module constructs a semantic analysis model based on natural language processing technology, intelligently matches medical treatment items with the charging items in the pricing policy and generates a matching score, and performs corresponding processing based on the score; The dynamic verification and early warning module is used to monitor the billing process in real time, control the billing situation through price range verification, frequency verification and medical insurance compliance verification, and provide graded early warning for abnormal situations. The policy response and automatic update module is used to receive new price policy documents and extract key information, automatically update relevant charging parameters, and support the retrospective of historical policies. The interactive and statistical analysis module provides a visual user interface, supports manual operation, and automatically generates reports and data dashboards.

[0008] Furthermore, the multi-source data fusion acquisition module establishes data interfaces with the hospital's HIS system, LIS system, PACS system, national and local price control department databases, and medical insurance bureau policy platform, and supports manual data upload; When collecting information on diagnosis and treatment items, the multi-source data fusion acquisition module obtains detailed information such as examination name, operating physician, and implementing department; when collecting price policy documents, it can capture fee standards, coding rules, and medical insurance payment scope; the manually uploaded data is used for uploading self-made supplementary regulations on pricing of special services within the hospital, and the collected data is uniformly stored in the system database after being processed in a standardized format.

[0009] Furthermore, the semantic analysis model of the policy-project intelligent matching module, after receiving the treatment project information, first analyzes the name and description of the treatment project to extract key information, and then performs a semantic comparison between the extracted key information and the charging items in the price policy. During the comparison process, historical matching records are combined to finally generate a matching score of 0-100. For projects in different matching score ranges, automatic association, manual review and push, and new prompts are performed according to the score, and the differences are marked and pushed to the manual review interface.

[0010] Furthermore, the matching score generated by the policy-project intelligent matching module ranges from 0 to 100. Projects with a matching score of ≥90 are automatically associated with a fee code and standard; projects with a matching score of 60-89 are pushed to the manual review interface; and projects with a matching score <60 trigger a prompt for adding new fee items.

[0011] Furthermore, the specific method by which the dynamic verification and early warning module manages the charging situation is as follows: Price range verification: The system compares the actual charge amount with the upper and lower limits stipulated by the policy in real time. If the actual charge amount exceeds the stipulated range, the system will immediately issue a warning pop-up. Frequency verification: For the same treatment item for the same patient, the system judges whether the charging frequency is reasonable according to the disease category standards. If the charging frequency is abnormal, the system will mark it. Medical insurance compliance verification: It connects with the medical insurance catalog in real time, automatically identifies chargeable items that are outside the scope of medical insurance payment, and prompts patients with a self-pay confirmation mark.

[0012] Furthermore, the dynamic verification and early warning module's graded early warning is divided into three levels: red, yellow, and blue, based on the severity of the warning. The warnings are sent via system messages and mobile app push notifications, which include project details and handling suggestions.

[0013] Furthermore, the policy response and automatic update module has a built-in policy recognition engine. When a new price policy document is received, the policy recognition engine extracts the effective date, adjusted items, and price change information from the document. For newly added medical services, it automatically creates a temporary charging code and associates it with the pricing rules of similar items, while prompting price control personnel to supplement and improve the code information. The policy response and automatic update module automatically updates the charging parameters of the corresponding items 24 hours before the new price policy takes effect, and generates a list of updates to be executed for manual confirmation. The historical policy retrospective allows administrators to query the fee schedule at any point in time.

[0014] Furthermore, the interactive and statistical analysis module's visual interface allows for the input of special fee descriptions; the interactive and statistical analysis module generates daily, weekly, and monthly reports on price implementation, with the daily reports including indicators such as fee matching accuracy rate, abnormal warning handling rate, and policy update completion rate; the data dashboard displays the fee compliance rate of each department, data on high-frequency abnormal fee items, and comparative data on price policy implementation over different time periods.

[0015] Furthermore, it also includes a data security module, which uses data encryption technology to encrypt the diagnosis and treatment information, price policy documents, and fee records stored in the system. At the same time, it sets up a user permission management mechanism to assign different operating permissions to staff in different positions. The data security module also backs up the system data regularly.

[0016] Furthermore, the data encryption technology adopts a combination of symmetric and asymmetric encryption. The symmetric encryption is used to encrypt the data, and the asymmetric encryption is used to encrypt the key of the symmetric encryption during transmission. The user permission management mechanism is divided into data viewing permissions, data editing permissions, and system management permissions according to the staff's positions and responsibilities.

[0017] The advantages of this invention compared to the prior art are: This invention can quickly respond to changes in price policies, reduce repetitive manual operations, and greatly alleviate the workload of price management personnel.

[0018] This invention utilizes the semantic analysis and matching functions of the policy-project intelligent matching module, as well as the real-time verification of the dynamic verification and early warning module, to reduce the rate of billing mismatch. This effectively reduces the number of medical insurance refusal cases caused by mismatch and lowers the risk of medical insurance refusal.

[0019] The policy response and automatic update module of this invention can respond promptly to policy changes, achieving "immediate identification and immediate implementation" of pricing policies. The dynamic verification and early warning module can monitor charging behavior in real time, shortening the response time for abnormal charging warnings, effectively preventing illegal charging, and ensuring the compliance of hospital charges.

[0020] The interactive and statistical analysis module of this invention generates various reports and data dashboards that intuitively present weaknesses in price management. This information provides data support for hospital-wide fee standardization training and departmental assessments, helping hospitals continuously optimize price management and improve overall operational management. Attached Figure Description

[0021] Figure 1 This is a system block diagram of a hospital price monitoring system according to the present invention.

[0022] Figure 2 This is a flowchart of a hospital price monitoring system according to the present invention. Detailed Implementation

[0023] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present invention.

[0024] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0025] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0026] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0027] The following is a detailed description of a hospital price monitoring system according to the present invention, with reference to the accompanying drawings.

[0028] Combined with appendix Figure 1-2 This invention will be described in detail below.

[0029] A hospital price supervision system includes a multi-source data fusion and acquisition module, a policy-project intelligent matching module, a dynamic verification and early warning module, a policy response and automatic update module, and an interaction and statistical analysis module. Each module is independent in function but works together to form a complete price supervision closed loop.

[0030] The multi-source data fusion and acquisition module is the data foundation of the system. It is responsible for comprehensively collecting various types of data required for price management and ensuring data consistency through standardized processing. Its specific functions are as follows: Integration with hospital internal business systems: Through preset data interfaces, it connects in real time to the hospital's HIS (Hospital Information System), LIS (Laboratory Information System), and PACS (Medical Image Archiving and Communication System) to automatically obtain detailed information on diagnostic and treatment items, including examination name (such as "knee joint MRI plain scan"), operating physician, and performing department. Connect with external policy platforms: Establish data links with national and local price authorities' databases and medical insurance bureau's policy platforms to automatically capture the latest price policy documents and extract key information such as fee standards, coding rules, and medical insurance coverage. Support for manual uploading: Provides a manual uploading portal, allowing price management personnel to upload supplementary pricing regulations made within the hospital, such as pricing for special services and temporary fee standards for emergency rescue projects.

[0031] Data processing and storage: The collected multi-source data (such as medical service information, policy documents, and hospital supplementary regulations) are first processed through format standardization (unifying data format, field naming and data type) and then stored in the system database to avoid subsequent processing errors caused by inconsistent data formats and to provide reliable data support for each module.

[0032] The policy-project intelligent matching module, based on natural language processing (NLP) technology, automatically matches medical services with pricing policy charges, solving the problems of low efficiency and large errors in manual matching. The specific process and rules are as follows: Semantic analysis model construction: A semantic analysis model is built based on NLP technology. This model has the ability to extract keywords, compare semantic similarity, and learn from historical data, and can accurately identify the relationship between medical treatment items and policy-based fee items.

[0033] Matching process: Receive diagnostic and treatment information (such as project name and project description) transmitted by the multi-source data fusion acquisition module; The model performs semantic analysis on the names and descriptions of diagnostic and treatment items to extract key information (e.g., extracting "knee joint" and "MRI plain scan" from "knee joint MRI plain scan"). The extracted key information is semantically compared with the charges in the price policy (such as "magnetic resonance imaging (specific area)"). At the same time, the comparison accuracy is optimized by combining historical matching records (such as the past charging codes and matching results of the same items). Generate a matching score from 0 to 100, with a higher score indicating higher matching accuracy.

[0034] Matching result processing rules: Matching score ≥ 90: The system automatically associates the corresponding charging code and charging standard, without manual intervention, and directly synchronizes it to the charging execution process; Matching score 60-89: The system will push the project to the manual review interface and automatically mark the differences (such as "inconsistent description of project parts" or "ambiguous coding rules") to help reviewers quickly locate and confirm the problem; Matching score < 60 points: The system triggers a "Pending addition of fee items" prompt, reminding price management personnel to verify whether the item is a new item not included in the existing policy, and to supplement and improve the fee code and standard before including it in the management.

[0035] The dynamic verification and early warning module is responsible for real-time monitoring of the charging process. It identifies abnormal charging behavior through three verification rules and promptly pushes reminders in a tiered early warning manner. Specific functions are as follows: Three verification rules: Price range verification: The system obtains the actual amount charged in real time during the charging process and compares it with the upper and lower limits of the charges stipulated by the price policy. If the actual amount exceeds the stipulated range (e.g., the policy stipulates that the charge for "blood routine examination" is 25-28 yuan, but the actual charge is 30 yuan), the system will immediately issue a pop-up warning to prevent illegal charging operations. Frequency verification: For the same treatment item for the same patient, the system judges whether the charging frequency is reasonable based on the disease-specific guidelines (e.g., postoperative dressing change once a day, no more than 7 times a week); if the charging frequency exceeds the limit (e.g., charging 3 times a day for postoperative dressing change), the system will automatically mark it as "to be verified", suspend the charging process and prompt for verification; Medical insurance compliance verification: It connects with the medical insurance catalog in real time and automatically identifies whether the chargeable items are within the scope of medical insurance payment; if the item exceeds the scope of medical insurance payment (such as non-essential special services), the system generates a "patient self-payment confirmation required" mark, requiring medical staff to explain to the patient and obtain confirmation before continuing to charge.

[0036] Tiered early warning mechanism: Warning Level Classification: Warning information is divided into three levels according to the severity of the anomaly: Red Warning (representing illegal charges, such as charging above the standard), Yellow Warning (representing suspected anomalies, such as abnormal frequency requiring verification), and Blue Warning (representing a reminder to update, such as preparing for a policy that is about to take effect). Warning push method: Warning information is pushed simultaneously through system messages (such as pop-ups on the management terminal) and mobile APP (such as push notifications from a dedicated APP for price management personnel), along with project details (such as patient information, billing items, reasons for abnormalities) and handling suggestions (such as "please check the surgical record to confirm the frequency of dressing changes"), ensuring that management personnel can respond quickly, and the average warning response time is shortened to within 5 minutes.

[0037] The policy response and automatic update module enables the automatic identification, parsing, and execution of price policies, solving the problem of lag caused by manual updates and ensuring that policies are "identified as soon as they are available and executed as soon as they expire." Specific functions are as follows: Policy Recognition and Analysis: The built-in policy recognition engine automatically extracts key information from new price policy documents (such as the fee adjustment notice issued by the National Healthcare Security Administration) when it receives them. This information includes the policy's effective date, adjusted items (such as "blood routine examination"), price change range (such as from 25 yuan to 28 yuan), and added / cancelled items. Automatic update execution: For price adjustment items: 24 hours before the policy takes effect, the system will automatically update the corresponding item's charging parameters (such as adjusting the charging standards in the database) and generate a "list of updates to be executed", which will be pushed to price management personnel for confirmation to avoid accidental updates; For newly added medical services: the system automatically creates a temporary charging code and associates it with the pricing rules of similar services, while prompting pricing personnel to supplement and improve the code information; Historical Policy Retrospective: Supports managers to query price policies and fee standards at any point in time and generate historical policy ledgers to meet the needs of scenarios such as audit verification and fee dispute resolution.

[0038] The interactive and statistical analysis module provides price management personnel with an operational interface and decision support. Through a visual interface and multi-dimensional reports, it enhances management convenience and the scientific nature of decision-making. Specific functions are as follows: Visual user interface: Manual intervention function: Allows price management personnel to manually adjust the matching results (such as correcting the coding association of low matching degree items), enter special charge explanations (such as the temporary pricing reasons for emergency rescue projects), and confirm the policy update list, etc.; Interface design: It adopts a simple and intuitive layout, distinguishing functional areas such as "Pending", "Processed", and "Exception Records", and supports fuzzy search (such as searching by department or project name) to improve operational efficiency.

[0039] Report and data dashboard generation: Multi-dimensional reports: Automatically generates "Daily Report on Price Implementation", "Weekly Report" and "Monthly Report". The daily report includes core indicators such as the accuracy rate of fee matching (e.g., 98% of items are automatically matched successfully on the same day), the handling rate of abnormal warnings (e.g., 100% completion rate of handling yellow warnings on the same day), and the policy update completion rate (e.g., 95% completion rate of new policy updates this week). Data dashboard: Displays key data in chart format (such as bar charts, line charts, and heat maps), including the compliance rate of charges for each department (e.g., 99% compliance rate for internal medicine and 97% compliance rate for surgery), high-frequency abnormal charges (e.g., the "dressing change" item has the highest abnormal rate), and comparisons of price policy implementation over different time periods (e.g., the difference in compliance rate between this month and last month), providing data support for hospital charge standardization training, departmental assessments, and management optimization.

[0040] To ensure the security and integrity of system data (including patient treatment information, billing records, and policy documents), a data security module has been added to the system, with the following specific functions: Data encryption processing: A combination of symmetric and asymmetric encryption is used. Symmetric encryption (such as the AES algorithm) is used to quickly encrypt large amounts of stored data in the system (such as medical information and billing records), while asymmetric encryption (such as the RSA algorithm) is used to encrypt the transmission of the symmetric encryption key to prevent data cracking caused by key leakage. User access control: Based on staff positions and responsibilities, operation permission levels are subdivided, including data viewing permissions (e.g., medical staff in a department can only view the department's billing data), data editing permissions (e.g., pricing specialists can edit billing standards), and system management permissions (e.g., administrators can configure module parameters); dynamic permission adjustment is supported, and when a staff member's position changes, their permissions can be updated in real time to prevent unauthorized operations; Data backup and recovery: The system database is backed up regularly (e.g., every morning at midnight), and the backup data is stored on an off-site server. When system data is lost or damaged (e.g., due to hardware failure or virus attack), the data can be quickly recovered from the backup file, with a recovery time of no more than 1 hour, ensuring the continuous and stable operation of the system.

[0041] The specific implementation process of the hospital price monitoring system of the present invention is as follows: Example 1: Price Management Process for the "Knee Joint MRI Plain Scan" Project Data acquisition phase: The multi-source data fusion acquisition module obtains the diagnosis and treatment information of "knee MRI plain scan" in real time through the hospital PACS system interface (examination name: knee MRI plain scan; operating physician: Zhang XX; performing department: radiology department); at the same time, it retrieves the latest "Medical Service Price Item Specification" from the local medical insurance bureau policy platform and extracts the charging standard (350 yuan / time) and coding rules (such as "xxxxx") for "MRI plain scan (specific site)". Intelligent matching phase: After receiving the above data, the policy-project intelligent matching module extracts the key information of "knee joint" and "MRI plain scan" from the semantic analysis model, performs semantic comparison with "MRI plain scan (specific area)" in the policy, and combines it with historical matching records (past "hip joint MRI plain scan" matching code "xxxxx") to generate a matching score of 95 points; because the score is ≥90 points, the system automatically associates the code "xxxxx" with the fee standard of 350 yuan / time; Dynamic verification phase: When the radiology department performs a "knee MRI plain scan" on a patient and initiates billing, the dynamic verification and early warning module activates three major verifications: Price range verification: The actual charge was 350 yuan, which is consistent with the policy-stipulated range of 350-380 yuan, and no warning was issued; Frequency verification: The patient is undergoing this examination for the first time, which meets the "single charge for the same item" standard, and there is no warning. Medical insurance compliance verification: This project is covered by medical insurance and does not require confirmation from the patient out-of-pocket. Policy update phase: If the local medical insurance bureau issues a policy one month later, adjusting the fee standard for "magnetic resonance imaging (specific area)" to 360 yuan / time, the policy response and automatic update module will automatically extract key policy information (effective date: the 1st of the following month; adjustment range: +10 yuan), update the fee parameters 24 hours before the effective date, and generate a "list of updates to be implemented" to be pushed to the price specialist for confirmation. Statistical Analysis Phase: The interactive and statistical analysis module generates a daily "Price Implementation Status Report," showing that the "Knee Joint MRI Plain Scan" item has a 100% matching accuracy rate and no abnormal warnings on the day; the data dashboard shows that the radiology department's monthly fee compliance rate for this item is 100%, providing a basis for departmental assessment.

[0042] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. A hospital price monitoring system, characterized in that: It includes a multi-source data fusion and acquisition module, a policy-project intelligent matching module, a dynamic verification and early warning module, a policy response and automatic update module, and an interaction and statistical analysis module; The multi-source data fusion acquisition module is used to collect information on diagnosis and treatment items, price policy documents, and supplementary pricing regulations made by the hospital, and stores the collected data after standardization processing; The policy-project intelligent matching module constructs a semantic analysis model based on natural language processing technology, intelligently matches medical treatment items with the charging items in the pricing policy and generates a matching score, and performs corresponding processing based on the score; The dynamic verification and early warning module is used to monitor the billing process in real time, control the billing situation through price range verification, frequency verification and medical insurance compliance verification, and provide graded early warning for abnormal situations. The policy response and automatic update module is used to receive new price policy documents and extract key information, automatically update relevant charging parameters, and support the retrospective of historical policies. The interactive and statistical analysis module provides a visual user interface, supports manual operation, and automatically generates reports and data dashboards.

2. The hospital price monitoring system according to claim 1, characterized in that: The multi-source data fusion acquisition module establishes data interfaces with the hospital's HIS system, LIS system, PACS system, national and local price control department databases, and medical insurance bureau policy platform, and supports manual data upload; When collecting information on diagnosis and treatment items, the multi-source data fusion acquisition module obtains detailed information such as examination name, operating physician, and implementing department; when collecting price policy documents, it can capture fee standards, coding rules, and medical insurance payment scope; the manually uploaded data is used for uploading self-made supplementary regulations on pricing of special services within the hospital, and the collected data is uniformly stored in the system database after being processed in a standardized format.

3. A hospital price monitoring system according to claim 2, characterized in that: The semantic analysis model of the policy-project intelligent matching module, after receiving the treatment project information, first analyzes the name and description of the treatment project to extract key information, and then performs a semantic comparison between the extracted key information and the charging items in the price policy. During the comparison process, historical matching records are combined to finally generate a matching score of 0-100. For projects in different matching score ranges, automatic association, manual review and push, and new addition prompts are performed according to the score, and the differences are marked and pushed to the manual review interface.

4. A hospital price monitoring system according to claim 3, characterized in that: The matching score generated by the policy-project intelligent matching module ranges from 0 to 100. Projects with a matching score of ≥90 are automatically associated with a fee code and standard; projects with a matching score of 60-89 are pushed to the manual review interface; and projects with a matching score <60 trigger a prompt for adding a new fee item.

5. A hospital price monitoring system according to claim 4, characterized in that: The specific methods by which the dynamic verification and early warning module manages and controls charging are as follows: Price range verification: The system compares the actual charge amount with the upper and lower limits stipulated by the policy in real time. If the actual charge amount exceeds the stipulated range, the system will immediately issue a warning pop-up. Frequency verification: For the same treatment item for the same patient, the system judges whether the charging frequency is reasonable according to the disease category standards. If the charging frequency is abnormal, the system will mark it. Medical insurance compliance verification: It connects with the medical insurance catalog in real time, automatically identifies chargeable items that are outside the scope of medical insurance payment, and prompts patients with a self-pay confirmation mark.

6. A hospital price monitoring system according to claim 5, characterized in that: The dynamic verification and early warning module classifies early warnings into three levels: red, yellow, and blue, based on severity. These warnings are sent via system messages and mobile app push notifications, which include project details and handling suggestions.

7. A hospital price monitoring system according to claim 6, characterized in that: The policy response and automatic update module has a built-in policy recognition engine. When a new price policy document is received, the policy recognition engine extracts the effective date, adjusted items, and price change information from the document. For newly added medical services, it automatically creates a temporary charging code and associates it with the pricing rules of similar items, while prompting price control personnel to supplement and improve the code information. The policy response and automatic update module automatically updates the charging parameters of the corresponding items 24 hours before the new price policy takes effect, and generates a list of updates to be executed for manual confirmation. The historical policy retrospective allows administrators to query the fee schedule at any point in time.

8. A hospital price monitoring system according to claim 7, characterized in that: The interactive and statistical analysis module's visual interface allows for the input of special fee descriptions; the interactive and statistical analysis module generates daily, weekly, and monthly reports on price implementation, with the daily reports including indicators such as fee matching accuracy rate, abnormal warning handling rate, and policy update completion rate; the data dashboard displays the fee compliance rate of each department, data on high-frequency abnormal fee items, and comparative data on price policy implementation over different time periods.

9. A hospital price monitoring system according to claim 8, characterized in that: It also includes a data security module, which uses data encryption technology to encrypt the diagnosis and treatment information, price policy documents, and fee records stored in the system. At the same time, it sets up a user permission management mechanism to assign different operation permissions to staff in different positions. The data security module backs up system data regularly.

10. A hospital price monitoring system according to claim 9, characterized in that: The data encryption technology employs a combination of symmetric and asymmetric encryption. Symmetric encryption is used to encrypt the data, while asymmetric encryption is used to encrypt the key used for symmetric encryption during transmission. The user access control mechanism is divided into data viewing permissions, data editing permissions, and system management permissions based on the staff's positions and responsibilities.

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