Settlement optimization method for hospital scientific research consumable purchase and financial system linkage

Abstract

The invention discloses a hospital scientific research consumable purchase and financial system linkage settlement optimization method, and relates to the technical field of purchase management, and the method comprises the steps: collecting scientific research purchase data, building a scientific research purchase data incidence matrix model, and carrying out the automatic verification based on the submission of a consumable application, and calling the scientific research purchase data incidence matrix model, and completing the purchase. After purchasing is completed, a scientific research fund dynamic balance model is constructed to output fund change information; an account structure is monitored and adjusted by outputting fund change information, and scientific research purchase efficiency and risk assessment model output quantitative indexes are constructed. According to the method, the scientific research purchase data incidence matrix model, the scientific research fund dynamic balance model and the purchase efficiency and risk assessment model are constructed, so that real-time linkage of hospital scientific research consumable purchase and a financial system is innovatively realized. The intelligent verification, fund dynamic monitoring and risk quantitative analysis capabilities of the purchasing process are effectively improved, the reasonable fund structure is ensured, and the intelligent level of scientific research management is promoted to be comprehensively improved.

Description

Technical Field

[0001] This invention relates to the field of procurement management technology, specifically to a settlement optimization method that links hospital research consumables procurement with the financial system. Background Technology

[0002] In recent years, with the continuous expansion of hospital research work, the complexity of research material procurement and funding management has been increasing. Especially in medium and large-sized medical institutions, the procurement of research consumables is gradually shifting from traditional manual approval and decentralized management towards informatization, standardization, and systematization. Some hospitals have initially established research procurement platforms, realizing procurement information registration, supplier directory management, and online approval for some processes. Simultaneously, research funding management is gradually being integrated into the financial information system, forming a funding category classification and budget control mechanism. These technological means have, to some extent, improved procurement efficiency and the transparency of fund usage, promoting the overall improvement of hospital research management.

[0003] While existing technologies have made some progress in the informatization of scientific research procurement and funding management, they generally suffer from technical bottlenecks such as system isolation, data fragmentation, and process disconnect. First, research procurement platforms and financial systems mostly operate independently, lacking effective data linkage mechanisms. This leads to a real-time disconnect between the procurement process and the funding structure, hindering dynamic settlement and budget optimization. Second, existing research procurement systems largely rely on static rule validation, failing to build dynamic relationships based on multi-dimensional data such as projects, consumables, and supply chains. Their level of intelligence is insufficient, easily resulting in mismatches between procurement requests and research projects, budget structures, and supplier qualifications. Furthermore, existing technologies lack real-time monitoring and risk warning capabilities for the use of research funds, and cannot dynamically reflect changes in the funding structure through mathematical models. This makes it difficult to promptly detect and intervene in issues such as budget overruns and imbalanced funding structures. More importantly, the current lack of integrated procurement efficiency and risk quantification assessment mechanisms makes it difficult for managers to make scientific decisions based on real-time data. The research management process remains limited by information silos, process lags, and uncontrollable risks. Therefore, there is an urgent need for an innovative technical solution that integrates data correlation modeling, automatic verification, dynamic funding balancing, intelligent monitoring, and comprehensive efficiency and risk assessment in scientific research procurement, in order to break through the above-mentioned technical bottlenecks and improve the overall intelligence and collaboration level of scientific research procurement and financial management. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by this invention is that existing hospital research consumables procurement and financial system management methods suffer from data fragmentation between the procurement system and the financial system, lack of real-time dynamic balancing mechanism, and difficulty in quantifying and assessing procurement risk levels. The invention also addresses how to achieve integrated linkage and intelligent optimization of research procurement, funding management, and risk assessment.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a settlement optimization method for linking hospital research consumables procurement with the financial system, comprising collecting research procurement data to construct a research procurement data correlation matrix model; based on the submission of consumables applications, calling the research procurement data correlation matrix model for automatic verification to complete the procurement; after the procurement is completed, constructing a research funding dynamic balance model to output funding change information; monitoring and adjusting the account structure by outputting funding change information, and constructing a research procurement efficiency and risk assessment model to output quantitative indicators.

[0007] As a preferred embodiment of the settlement optimization method for linking hospital research consumables procurement with the financial system as described in this invention, the construction of the research procurement data association matrix model includes dimensions of the research procurement data association matrix model for research projects, consumable categories, supplier information, and researcher authorization information.

[0008] As a preferred embodiment of the settlement optimization method for linking hospital research consumables procurement with the financial system as described in this invention, the automatic verification includes verification of the procurement applicant's authority, verification of the compatibility between consumables and the project, verification of the supplier's qualifications, and verification of the budget account balance.

[0009] As a preferred embodiment of the settlement optimization method for linking hospital research consumables procurement with the financial system described in this invention, the construction of the dynamic balance model for research funding includes integrating historical fund inflow information, procurement execution rate, fund structure parameters and budget utilization rate to output dynamic indicators reflecting the balance of research funding structure, and guiding account structure adjustments accordingly.

[0010] As a preferred embodiment of the settlement optimization method for linking hospital research consumables procurement with the financial system described in this invention, the information on changes in funding includes dynamically restricting procurement authority based on dynamic monitoring of the use of research project funding, adjusting the budget structure, and automatically triggering an early warning mechanism and linkage control measures when the budget is overrun.

[0011] As a preferred embodiment of the settlement optimization method for linking hospital research consumables procurement with the financial system as described in this invention, the construction of the research procurement efficiency and risk assessment model includes dynamically reflecting procurement behavior and risk status by outputting procurement efficiency, budget execution deviation, and procurement risk level.

[0012] As a preferred embodiment of the settlement optimization method for linking hospital research consumables procurement with the financial system described in this invention, the output quantitative indicators include procurement efficiency trends, budget structure changes, and dynamic distribution of risk levels, thereby assisting the research management department in optimizing procurement strategies, adjusting budget structures, and controlling procurement risks.

[0013] Another objective of this invention is to provide a settlement optimization system that links hospital research consumables procurement with the financial system. This system can output funding change information by constructing a dynamic balance model for research funding, thus solving the problems of current hospital research consumables procurement and financial system management methods, which lack a real-time dynamic balance mechanism and have difficulty in quantifying and assessing procurement risk levels.

[0014] As a preferred embodiment of the settlement optimization system linking hospital research consumables procurement and financial systems as described in this invention, it includes: a research procurement data modeling and automatic verification module, a research funding dynamic balancing and account structure optimization module, and a procurement efficiency and risk intelligent assessment and decision support module. The research procurement data modeling and automatic verification module collects research procurement data, constructs a research procurement data correlation matrix model, verifies procurement requests, and generates procurement orders. The research funding dynamic balancing and account structure optimization module constructs a research funding dynamic balancing model, outputs funding change information, and adjusts the account structure in real time. The procurement efficiency and risk intelligent assessment and decision support module assesses procurement efficiency and risk levels, outputs quantitative indicators, and assists in management decision-making and risk control.

[0015] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement a settlement optimization method that links the procurement of hospital research consumables with the financial system.

[0016] A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of a settlement optimization method for linking the procurement of hospital research consumables with the financial system are disclosed.

[0017] The beneficial effects of this invention are as follows: The settlement optimization method for linking hospital research consumables procurement and financial systems provided by this invention innovatively achieves intelligent linkage and settlement optimization between hospital research consumables procurement and financial systems by constructing a research procurement data correlation matrix model, a research funding dynamic balance model, and a research procurement efficiency and risk assessment model. By collecting relevant research procurement data and establishing a multi-dimensional, structured data matrix, the isolated state between research projects, consumable categories, supplier information, and personnel authorization is broken, significantly improving data fusion and information matching efficiency. Based on the matrix model, when researchers submit procurement requests, intelligent verification of identity permissions, consumable compatibility, supplier compliance, and budget balance can be automatically completed, ensuring the procurement process is legal, standardized, and efficient, and reducing the risks of illegal procurement and budget irregularities. Simultaneously, after procurement is completed, the dynamic balance model outputs real-time funding change information, dynamically monitors changes in the research funding structure, intelligently adjusts the internal budget configuration of the account, enhances the transparency and flexibility of fund flow, and prevents imbalances in the funding structure. Furthermore, through the efficiency and risk assessment model, the system comprehensively analyzes efficiency indicators, budget deviation, and risk levels in the procurement process, outputting quantitative results to assist research management departments in achieving process monitoring, risk warning, and scientific decision-making. Overall, this invention breaks through the technical bottlenecks of traditional scientific research procurement and financial systems being separated, data being isolated, and management being lagging behind. It constructs a new scientific research procurement management model that integrates data fusion, intelligent verification, dynamic balancing, and risk assessment, comprehensively improving the informatization, intelligence, and compliance level of hospital scientific research management. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 The first embodiment of the present invention provides an overall flowchart of a settlement optimization method for linking hospital scientific research consumables procurement with the financial system.

[0020] Figure 2 The first embodiment of the present invention provides a method logic diagram for optimizing the settlement of hospital scientific research consumables procurement and financial system linkage.

[0021] Figure 3 The third embodiment of the present invention provides an overall flowchart of a settlement optimization system that links hospital research consumables procurement with the financial system. Detailed Implementation

[0022] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0023] Example 1, referring to Figures 1-2 As an embodiment of the present invention, a settlement optimization method for linking hospital research consumables procurement with the financial system is provided, comprising: S1: Collect scientific research procurement data to construct a scientific research procurement data association matrix model. Based on the submission of consumables applications, call the scientific research procurement data association matrix model to automatically verify and complete the procurement.

[0024] Furthermore, based on the hospital's internal scientific research management information platform, the following scientific research procurement data are collected and integrated: Scientific research project information database: including project number, project name, project leader, project category, start and end dates, budget structure, budget item classification, and remaining funds; Scientific research personnel information database: including personnel identity information, job responsibilities, procurement authorization scope, and research team affiliation; Supplier information database: including supplier qualification level, product category catalog, historical cooperation records, and reputation evaluation; Consumables category database: including consumable name, specifications, applicable research fields, price information, and restrictive requirements.

[0025] It should be noted that the collection of research projects includes:

[0026] Let the set of consumable categories be:

[0027] Let the supplier set be:

[0028] The research personnel are grouped as follows:

[0029] The data association matrix model for scientific research procurement is represented as follows: ; in, Indicates the first One research project This represents the total number of research projects. For the first One category of consumables, This represents the total quantity of consumable items. For the first One supplier, The total number of suppliers, For the first One researcher, This refers to the total number of researchers.

[0030] Researchers log in to the hospital's research procurement platform and submit consumable procurement requests based on their existing authorization scope. Request information includes: research project number. Applicant's identity information Consumables categories and specifications Expected supplier information (optional) Purchase quantity and amount; source of funds (budget item classification).

[0031] The procurement request information is written into the scientific research procurement data management system in real time, awaiting system verification.

[0032] The system calls the scientific research procurement data association matrix model. And related output metrics, and perform the following verification actions in sequence: Identity and authorization verification is performed based on the authorized purchase list output by the matrix. ; Determine the applicant Does it have the ability to participate in scientific research projects? Grant the authority to purchase this category of consumables.

[0033] like Includes the categories of consumables applied for. If the verification passes, the system will reject the application and display the message "No procurement authority".

[0034] Consumable compatibility verification is performed based on the consumable list output by the matrix. Determine the consumables requested. Does it meet the requirements of scientific research projects? The scope of technology, clinical applicability, and research direction.

[0035] like If the verification passes, the message "Consumables do not meet the project's applicable scope" will be displayed.

[0036] Supplier compliance verification, if the applicant designates a supplier List of compliant consumable suppliers output by the matrix Verify whether the supplier's qualifications comply with the hospital's procurement catalog, cooperation standards, and regulatory requirements.

[0037] like If the verification passes, the message "Supplier qualifications do not meet requirements, it is recommended to replace" will be displayed.

[0038] If no supplier is specified, the system will automatically recommend a list of compliant suppliers for the applicant to choose from.

[0039] Budget remaining balance and account compliance verification are based on the budget remaining balance information output by the matrix. ; Verify that the procurement amount is within the balance of the project funding account and that the use of funds complies with the budget structure.

[0040] If the purchase amount If the verification passes, the message "Insufficient budget balance, unable to submit application" will be displayed.

[0041] Comprehensive compliance verification, based on matrix elements The system outputs a binary value and makes an overall determination of the compliance of this procurement request. like The system determines that the application is compliant and proceeds to the next step. like The system rejected the application and sent the corresponding reason for the violation.

[0042] Purchase order generation and data push: After verification, the system automatically generates a standardized electronic purchase order, which includes: research project number and funding information; applicant information and authorization record; detailed parameters of consumables; compliant supplier information; budget deduction details; verification log and compliance conclusion.

[0043] Purchase orders are simultaneously pushed to the hospital's financial system, forming a linked front-end data for financial accounting; purchase information is written into the scientific research management platform in real time, facilitating process monitoring, data traceability, and performance statistics.

[0044] S2: After procurement is completed, construct a dynamic balance model for research funding and output funding change information.

[0045] Furthermore, after a purchase order is generated, the system automatically records the following information: purchaser information, authorization verification record; consumable category, quantity, unit price, and supplier information; the research project number and budget item; verification log and compliance judgment result.

[0046] Procurement data is pushed to the financial system in real time to ensure a high degree of synchronization between procurement activities, budget information, supply chain information, and fund account information.

[0047] It should be noted that, while receiving procurement data, the financial system constructs a dynamic balance model for research funding, represented as follows;

[0048] in, For time The dynamic balance output value of research funding at any given time. To calculate the time step for the system, This is the budget sensitivity adjustment coefficient. For the first One factor influencing capital inflows Based on historical capital inflows With procurement execution rate The composite function, To count the number of valid fund inflow records within the statistical period, For the first Weights of each capital expenditure structure Based on historical time Importance indicators of procurement categories Remaining percentage of budget The structural adjustment function, For the first Supplier credit scoring in this procurement Risk level of consumables The composite function, This represents the cumulative number of purchases within the statistical period.

[0049] This indicates that the research funding structure remains dynamically balanced and that the flow of funds is healthy. This indicates that cash inflows exceed expenditures, there is a budget surplus, and it is recommended to optimize investment efficiency. This indicates excessive spending and a tight budget, requiring a warning to control the intensity or structure of procurement. If the risk of running out of funds is detected, immediate intervention and management strategies are necessary.

[0050] like This indicates that the research project's funding structure is in a healthy state; the system automatically generates fund deduction instructions and deducts funds directly from the corresponding research project funding account according to the purchase order amount; real-time settlement of supplier payments is completed; researchers do not need to submit additional reimbursement applications, and the procurement and financial systems are linked in a closed loop, making the process efficient and transparent.

[0051] like This indicates that the project's funding structure is tight, with risks of budget overdraft or structural imbalance; the system automatically blocks the procurement and settlement process; triggers an early warning message to be pushed to the research management department and project leader; and suspends fund transfers to prevent financial risks and ensure the compliance of fund flows.

[0052] The financial system calculates the results of each procurement based on a real-time balancing model: dynamically adjusts the allocation ratio of funds for each budget item within the research project; reassesses the structure of fund items and remaining funds to optimize account utilization efficiency; and forms a dynamic self-balancing mechanism to enhance the flexibility and scientific nature of research fund management.

[0053] S3: By monitoring and adjusting the account structure through the output of funding change information, a research procurement efficiency and risk assessment model is constructed to output quantitative indicators.

[0054] Furthermore, the financial system shares data in real time with the procurement platform and the scientific research management platform, dynamically synchronizing the following information: the balance of funding accounts for each scientific research project; the budget item structure and execution progress; the latest purchase orders and fund expenditure records; supplier transaction behavior and credit changes; and consumable categories, risk levels, and actual usage.

[0055] It should be noted that, based on the model output The system automatically determines the funding status of research projects and triggers corresponding early warning responses, as shown in Table 1: Table 1 Early Warning Response Table

[0056] Furthermore, the system automatically implements the following control strategies for different warning levels: dynamically adjust procurement permissions to control high-risk or unnecessary procurement activities; restrict the allocation of funds for certain budget items to ensure priority for core research needs; push real-time warning information to research management departments, finance departments, and project leaders; automatically recommend budget structure optimization suggestions based on historical data and model trends; and, when necessary, trigger a special financial audit to ensure compliance of fund usage.

[0057] It should be noted that the system collects and stores the following information in real time and in a structured manner: procurement application records, intelligent verification results, compliance judgment logs; procurement order details, supplier information, consumable categories, budget item information; financial settlement instructions, fund deduction records, and expenditure structure change data; output results of the dynamic balance model for each period; calculation results of the procurement efficiency and risk assessment model for each period; and early warning information, linkage control measures, and execution feedback triggered by the system.

[0058] Furthermore, the research procurement efficiency and risk assessment model is expressed as follows:

[0059] in, For time The results of a comprehensive assessment of the efficiency and risk of scientific research procurement at all times. This is a dynamic adjustment coefficient for procurement efficiency. For the first The contribution weight of procurement efficiency. For the first This procurement was based on supplier credit scoring. Procurement time Matching with budget Constructed efficiency composite function, This represents the cumulative number of purchases during the statistical period. Adjust parameters based on procurement risk. For the first Risk level weighting for each procurement For the first This procurement was based on the risk level of consumables. Budget overrun deviation Number of supplier anomaly records Constructed risk composite function, This represents the cumulative number of purchases during the statistical period.

[0060] It should be noted that, This indicates high procurement efficiency, low risk level, and good system operation. This indicates that procurement efficiency and risk are within the normal range; This indicates low procurement efficiency or increased risk level, triggering a risk warning in the system.

[0061] The system integrates the following decision-making support measures: recommending supplier structure optimization and low-risk supply chain replacement solutions; proposing budget structure adjustment suggestions to prioritize core scientific research needs; outputting procurement strategy improvement plans to enhance procurement process efficiency and compliance; and supporting joint analysis and collaborative decision-making among project leaders, financial managers, and scientific research management departments.

[0062] Based on the output results and historical data, the system automatically generates multi-dimensional data reports for scientific research management: procurement efficiency trend analysis; budget execution deviation visualization; dynamic distribution chart of risk level; historical procurement compliance statistics; and comparative analysis of project, department, and supplier dimensions.

[0063] The report results are used for: performance evaluation of scientific research management; special audits of budget execution; assessment of the rationality of the use of scientific research funds; and quantitative feedback on the stability of the supply chain and the effectiveness of risk control.

[0064] Example 2, one embodiment of the present invention, provides a settlement optimization method for linking hospital scientific research consumables procurement with the financial system. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiment.

[0065] First, this embodiment conducts a systematic linkage test based on a large hospital's research management platform to verify the collaborative working effect of the research procurement data association matrix model, the dynamic funding balance model, and the procurement efficiency and risk assessment model. Before the test, the system completed data entry and structural configuration for the research project database, researcher information database, supplier directory, and consumable category database. A total of six research projects were included, covering basic research and clinical translation projects, involving various research consumables and different suppliers. During the test, researchers initiated consumable requests through the procurement platform. The system called the research procurement data association matrix model in real time, automatically completing identity, permission, consumable compatibility, supplier qualifications, and budget compliance verification. Compliant requests automatically generated purchase orders and pushed them to the financial system. After procurement, the system constructed a research funding dynamic balance model based on real-time procurement data, outputting funding change indicators to dynamically reflect the funding structure of each project, and automatically adjusting the internal budget structure or triggering early warnings based on the balance results. Furthermore, the system continuously monitors various real-time data, calls the research procurement efficiency and risk assessment model, and outputs comprehensive evaluation indicators to quantitatively reflect the procurement efficiency level and risk status, assisting management departments in optimizing strategies. To ensure the objectivity of the test, all data throughout the experiment was automatically generated and archived by the system. The test scenario simulated the real procurement process to ensure that the system's innovative advantages were reflected.

[0066] Table 2 Experimental Data

[0067] As shown in Table 2, the system of this invention effectively ensures intelligent verification of the scientific research procurement process, dynamic balance of the funding structure, and comprehensive analysis of efficiency and risk. Firstly, observing the dynamic balance value of funding, projects P001, P003, and P005 reached 1.15, 1.25, and 1.30 respectively, indicating healthy cash flow, optimized budget structure, and significant effect of the system's real-time adjustment of the account structure. Meanwhile, project P004 had a dynamic balance value of 0.75, indicating that the system successfully identified a tight funding situation, triggered an early warning, and restricted unnecessary procurement, effectively preventing imbalances in the funding structure. Secondly, regarding the procurement efficiency and risk assessment results, projects P001, P003, and P005 had values ​​of 1.60, 1.70, and 1.50 respectively, indicating high procurement efficiency, low risk level, and good overall operation. However, projects P004 and P006 had values ​​below 0.9, indicating that the system accurately identified low procurement efficiency or high risk level, automatically recommended optimization solutions, and assisted management in decision-making. Compared to the shortcomings of traditional scientific research procurement, such as information silos, fragmented processes, and uncontrollable risks, this invention innovatively achieves real-time linkage and intelligent optimization of scientific research procurement, budget management, and risk control through multi-source data fusion, dynamic balancing, and intelligent evaluation. This significantly improves the scientific nature, transparency, and efficiency of scientific research funding management, demonstrating the technological progress and innovative advantages of this invention in terms of system structure, management processes, and level of intelligence.

[0068] Example 3, referring to Figure 3 As an embodiment of the present invention, a settlement optimization system linking hospital research consumables procurement and financial system is provided, including a research procurement data modeling and automatic verification module, a research funding dynamic balancing and account structure optimization module, and a procurement efficiency and risk intelligent assessment and auxiliary decision-making module.

[0069] The research procurement data modeling and automatic verification module is used to collect research procurement data, build a research procurement data correlation matrix model, verify procurement applications and generate procurement orders. The research funding dynamic balance and account structure optimization module is used to build a research funding dynamic balance model, output funding change information, and adjust the account structure in real time. The procurement efficiency and risk intelligent assessment and auxiliary decision-making module is used to assess procurement efficiency and risk level, output quantitative indicators, and assist management decision-making and risk prevention and control.

[0070] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0071] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0072] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0073] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc. It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

[0074] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A settlement optimization method for linking hospital research consumables procurement with the financial system, characterized in that, include: Collect scientific research procurement data to construct a scientific research procurement data association matrix model. Based on the submission of consumables application, call the scientific research procurement data association matrix model to automatically verify and complete the procurement. After procurement is completed, a dynamic balance model for research funding is constructed to output information on changes in funding. By monitoring and adjusting the account structure through the output of funding change information, a research procurement efficiency and risk assessment model is constructed to output quantitative indicators.

2. The settlement optimization method for linking hospital research consumables procurement with the financial system as described in claim 1, characterized in that: The constructed scientific research procurement data association matrix model includes dimensions of scientific research projects, consumable categories, supplier information, and scientific research personnel authorization information.

3. The settlement optimization method for linking hospital research consumables procurement with the financial system as described in claim 2, characterized in that: The automatic verification includes verification of the applicant's authority, verification of the compatibility of consumables with the project, verification of the supplier's qualifications, and verification of the budget account balance.

4. The settlement optimization method for linking hospital research consumables procurement with the financial system as described in claim 3, characterized in that: The construction of the dynamic balance model for research funding involves integrating historical funding inflow information, procurement execution rate, funding structure parameters, and budget utilization rate to output dynamic indicators reflecting the balance of the research funding structure, and using these indicators to guide adjustments to the account structure.

5. The settlement optimization method for linking hospital research consumables procurement with the financial system as described in claim 4, characterized in that: The information on changes in funding includes dynamically restricting procurement authority and adjusting the budget structure based on dynamic monitoring of the use of research project funds, and automatically triggering early warning mechanisms and linkage control measures when the budget is overrun.

6. The settlement optimization method for linking hospital research consumables procurement with the financial system as described in claim 5, characterized in that: The proposed research procurement efficiency and risk assessment model dynamically reflects procurement behavior and risk status by outputting procurement efficiency, budget execution deviation, and procurement risk level.

7. The settlement optimization method for linking hospital research consumables procurement with the financial system as described in claim 6, characterized in that: The output quantitative indicators include procurement efficiency trends, budget structure changes, and dynamic distribution of risk levels, which help scientific research management departments optimize procurement strategies, adjust budget structures, and control procurement risks.

8. A system employing a settlement optimization method linking hospital research consumables procurement and financial systems as described in any one of claims 1 to 7, characterized in that: It includes modules for scientific research procurement data modeling and automatic verification, dynamic balancing and account structure optimization of scientific research funding, and intelligent assessment and decision support for procurement efficiency and risk. The scientific research procurement data modeling and automatic verification module is used to collect scientific research procurement data, construct a scientific research procurement data association matrix model, verify procurement requests and generate procurement orders. The research funding dynamic balancing and account structure optimization module is used to build a research funding dynamic balancing model, output funding change information, and adjust the account structure in real time. The intelligent assessment and decision support module for procurement efficiency and risk is used to assess procurement efficiency and risk levels, output quantitative indicators, and assist in management decision-making and risk prevention and control.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the settlement optimization method for linking the hospital research consumables procurement and financial system as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the settlement optimization method for linking the hospital research consumables procurement and financial system as described in any one of claims 1 to 7.

Images