A blockchain-based medical billing auditing and payment system and method

Abstract

The application discloses a kind of medical bill auditing payment systems and methods based on blockchain, it is related to bill auditing technical field, the node model deployment module of the system is based on the real contract configuration (data quality, cost limit price, clinical rules and other contracts) of blockchain node with hardware parameter (CPU / memory / storage), it is realized to the risk-free simulation processing of un-audited bill, bill distribution analysis module is exposed in advance by multiple auditing payment processing Resource bottleneck, rule conflict, efficiency bottleneck that can appear in real environment, realize the full-link digital mapping of "physical node→virtual node→simulation strategy", solve the pain point of "strategy optimization depends on experience" of traditional blockchain system, the efficiency and compliance pain point of traditional medical bill processing is solved, and a new type of auditing payment mode of "data-driven, intelligent decision-making" is further constructed by technical innovation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of bill auditing, more particularly, it relates to a medical bill auditing and payment system and method based on a block chain. BACKGROUND

[0002] As a core link of medical fund flow management, the efficiency and compliance of medical bill auditing and payment directly affect the safety of medical insurance fund, the efficiency of commercial insurance claim and the patient's medical experience. The traditional auditing and payment mode relies on manual verification and centralized system processing, which has the pain points of long process (single bill auditing takes more than 30 minutes), high compliance risk (misjudgment rate is 8%-15%), and extensive resource scheduling (hardware resource utilization rate is less than 60%). With the development of block chain technology, a decentralized auditing and payment system based on smart contract is gradually applied, which realizes the automation of auditing process and the data tamper-proof by deploying data quality verification, fee limit comparison and clinical rule verification contracts, and the efficiency is improved by more than 40% and the compliance is more than 90% compared with the traditional mode.

[0003] The existing block chain system mainly relies on manual experience setting in node configuration and contract combination strategy (such as fixed allocation of high configuration nodes to process all bills), which lacks quantitative evaluation of different node configurations (CPU / memory / storage), contract combination (single contract independent node vs. multi-contract general node) and resource scheduling strategy. For example, in the face of medical insurance settlement peak (bill volume increases by 300%) or new policy online (such as DRG payment reform), it is difficult to scientifically predict node load fluctuation and rule conflict, which often leads to resource waste or performance bottleneck.

[0004] The existing system relies on real-time running feedback to identify resource bottlenecks (such as node memory overflow leading to contract crash), rule conflicts (such as medical insurance limit and commercial insurance clause conflict leading to account error) and efficiency bottlenecks (such as cross-chain communication delay leading to overall processing blockage), which cannot be risk-replayed before real environment deployment.

[0005] In view of the above problems, the present application provides a medical bill auditing and payment system and method based on a block chain. SUMMARY

[0006] In view of the deficiencies of the prior art, the purpose of the present application is to provide a medical bill auditing and payment system and method based on a block chain.

[0007] To achieve the above purpose, the present application provides the following technical solutions:

[0008] A medical bill auditing and payment system based on a block chain, comprising

[0009] The medical bill confirmation module regularly collects all medical bills that have been uploaded but not yet reviewed and paid, and simultaneously determines the contract and node configuration deployed on each blockchain node;

[0010] The node model deployment module builds a blockchain-based functional node review and payment model based on the contracts deployed by each blockchain node and the node configuration;

[0011] The bill allocation analysis module imports all medical bills that have been uploaded but not yet reviewed and paid into the functional node review and payment model, controls the functional node review and payment model to execute multiple review and payment processes, and obtains the review and payment in-depth evaluation value corresponding to each review and payment process;

[0012] The review and payment execution module selects the review and payment allocation method corresponding to the review and payment processing with the largest review and payment deep evaluation value, and executes review and payment for all medical bills that have been uploaded but not yet reviewed and paid.

[0013] Furthermore, the steps for obtaining the audit payment deep evaluation value corresponding to a review payment process are as follows: the control function node audit payment model starts to perform audit payment processing on all medical bills, and the corresponding time is marked as the audit payment start time. During the processing, each time the virtual node completes the contract verification work, it generates a contract verification log. When all medical bills complete the audit payment processing, the corresponding time is marked as the audit payment end time, and then the total audit payment time Tbgs, the average general analysis value ALL Pr(fx) and the average independent analysis value ALLYh(kn) are obtained. Through Dz(kne)= The audit payment deep evaluation value Dz(kne) corresponding to this audit payment processing is calculated, where as3 is the auxiliary coefficient No. 3, as4 is the auxiliary coefficient No. 4, and as5 is the auxiliary coefficient No. 5.

[0014] Furthermore, the contract verification log includes the virtual node ID, verification contract name, and resource consumption data.

[0015] Furthermore, the step of obtaining the total review and payment time Tbgs is as follows: the time difference between the review and payment end time and the review and payment start time is calculated to obtain the total review and payment time Tbgs.

[0016] Furthermore, the steps for obtaining the average universal analysis value ALLPr(fx) are as follows: obtain the universal analysis value of each universal contract virtual node, obtain the independent analysis value of each independent contract virtual node, sum up the universal analysis values ​​of all universal contract virtual nodes and take the average value to calculate the average universal analysis value ALLPr(fx).

[0017] Furthermore, the steps for obtaining the universal analysis value of the universal contract virtual node are as follows: select a universal contract virtual node, collect all contract verification logs of the universal contract virtual node, sort all contract verification logs in the order of generation, compare the verification contract names of the two adjacent contract verification logs after sorting, and when the two verification contract names are different, combine the resource consumption data of the two contract verification logs into a resource consumption data group, build a resource consumption comparison model, import the resource consumption data group into the resource consumption comparison model, and derive a resource consumption comparison value from the resource consumption comparison model. Set a resource consumption comparison threshold, and when the resource consumption comparison value ≥ the resource consumption comparison threshold, increase the number of switching fluctuations by one, and mark the number of switching fluctuations as CLP(s). Sum all resource consumption comparison values ​​and take the average value to calculate the average resource consumption comparison value EZG. The universal analysis value Pr(fx) of the universal contract virtual node is calculated by Pr(fx)=CLP(s)*as1+EZG*as2, where as1 is the auxiliary coefficient No. 1 and as2 is the auxiliary coefficient No. 2.

[0018] Furthermore, the steps for obtaining the average independent analysis value ALLYh(kn) are as follows: the independent analysis values ​​of all independent contract virtual nodes are summed up and the average value is calculated to obtain the average independent analysis value ALLYh(kn).

[0019] Furthermore, the steps for obtaining the independent analysis value of the independent contract virtual node are as follows: an independent contract virtual node is selected, all contract verification logs of the independent contract virtual node are collected, and all contract verification logs are compared in pairs. When the resource consumption data of the two compared contract verification logs are combined into a resource consumption data group, the resource consumption comparison value Yavg corresponding to each resource consumption data group is obtained, where v=1, 2, ..., V-1, V, v represents a corresponding resource consumption data group, and V is the total number of resource consumption data groups. The resource consumption comparison coefficient is set to PPg, g=1, 2, ..., G-1, G, PP1<PP2<...<PPG-1<PPG, and each resource consumption comparison coefficient is set to correspond to a range of resource consumption comparison values. The range of resource consumption comparison values ​​includes (0, Yav1], (Yav1, Yav2], ..., (YavG-1, YavG], through The independent analysis value Yh(kn) of the independent contract virtual node is calculated.

[0020] Furthermore, a blockchain-based medical bill review and payment method has the following steps:

[0021] S1: Regularly collect all medical bills that have been uploaded but not yet reviewed and paid, and simultaneously determine the contracts and node configurations deployed on each blockchain node;

[0022] S2: Build a blockchain-based functional node review and payment model based on the contracts deployed by each blockchain node and the node configuration;

[0023] S3: Import all uploaded medical bills that have not yet been reviewed and paid into the functional node review and payment model, control the functional node review and payment model to perform multiple review and payment processes, and obtain the review and payment in-depth evaluation value corresponding to each review and payment process;

[0024] S4: Select the audit payment allocation method corresponding to the audit payment processing with the largest audit payment deep evaluation value, and perform audit payment on all medical bills that have been uploaded but not yet audited and paid.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] The node model deployment module of the present invention is based on the real contract configuration (data quality, fee limit, clinical rules and other contracts) and hardware parameters (CPU / memory / storage) of the blockchain node to achieve risk-free simulation processing of unaudited bills. The bill allocation analysis module reviews payment processing multiple times (each time using different node grouping, contract combination, and resource scheduling strategy) to expose in advance the resource bottlenecks (such as node memory overflow), rule conflicts (such as contradictions between medical insurance and commercial insurance clauses), and efficiency bottlenecks (such as cross-chain communication delays) that may occur in the real environment, and realize the full-link digital mapping of "physical node → virtual node → simulation strategy", solving the pain point of "strategy optimization relying on experience" in traditional blockchain systems, solving the efficiency and compliance pain points of traditional medical bill processing, and building a new review and payment model of "data-driven, intelligent decision-making" through technological innovation. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of the principle of the present invention;

[0028] Figure 2 Flowchart of the method of the present invention. DETAILED DESCRIPTION

[0029] Example 1: Reference Figure 1 ,A blockchain-based medical bill review and payment system includes a medical bill determination module, which regularly collects all medical bills that have been uploaded but not reviewed and paid, and synchronously determines the contract and node configuration deployed by each blockchain node.

[0030] The node model deployment module builds a blockchain-based functional node review and payment model based on the contracts deployed by each blockchain node and the node configuration.

[0031] The node configuration of the blockchain node includes memory configuration, CPU configuration, storage configuration, etc. Blockchain nodes under different node configurations have different audit and payment execution capabilities. The contracts deployed by the blockchain node include data quality verification contracts, cost limit comparison contracts, clinical rule verification contracts, etc.

[0032] The function of the data quality verification contract is to check the integrity, accuracy and standardization of the data in the medical bill. For example, it checks whether the patient information in the bill is complete and accurate, and whether the diagnosis code, drug code, and examination item code comply with relevant standards and specifications.

[0033] The function of the cost price limit comparison contract is to compare the various expenses in the medical bill with the pre-set price limit standards to determine whether the expenses exceed the price limit range. The price limit standard can be the maximum price limit for drugs and medical services set by the medical insurance department, or the claim cost cap set by commercial insurance institutions.

[0034] The main function of the clinical rule verification contract is to calculate the medical expenses based on the medical insurance policy, commercial insurance contract and the settlement rules of the medical institution, determine the proportion of expenses that the medical insurance fund, commercial insurance institution and patient should bear respectively, and generate corresponding account separation instructions.

[0035] Some blockchain nodes use independent contracts, that is, they only have one contract and the ability to verify only one rule, while some blockchain nodes use general contracts, that is, they have multiple contracts (such as a data quality verification contract and a fee limit comparison contract at the same time) and have the ability to verify multiple rules.

[0036] The process of building a functional node review and payment model based on blockchain: create a blockchain model in general finite element analysis software based on the topological structure of the blockchain. The virtual nodes in the blockchain model correspond one-to-one with the blockchain nodes in the blockchain. The corresponding virtual nodes are parameterized according to the contracts deployed by the blockchain nodes and the node configuration, and finally the functional node review and payment model is built.

[0037] The bill allocation analysis module imports all medical bills that have been uploaded but not yet reviewed and paid into the functional node review and payment model, controls the functional node review and payment model to perform multiple review and payment processes (each review and payment process corresponds to an review and payment allocation method, and each review and payment process controls each virtual node in the functional node review and payment model to perform review and payment on all medical bills that have been uploaded but not yet reviewed and paid, and the review and payment allocation method corresponding to each review and payment process is different), and obtains the review and payment in-depth evaluation value corresponding to each review and payment process.

[0038] The review and payment execution module selects the review and payment allocation method corresponding to the review and payment processing with the largest review and payment deep evaluation value, and executes review and payment for all medical bills that have been uploaded but not yet reviewed and paid.

[0039] The steps for obtaining the audit payment in-depth evaluation value corresponding to an audit payment process are as follows: the control function node audit payment model starts to perform audit payment processing on all medical bills, and marks the corresponding time as the audit payment start time. During the processing, each time the virtual node completes a contract verification work, it generates a contract verification log. The contract verification log includes the virtual node ID, the verification contract name (the verification contract name is the data quality verification contract, the fee limit comparison contract, the clinical rule verification contract, etc.), and resource consumption data (resource consumption data includes CPU usage, memory usage, throughput, etc.). When all medical bills have completed the audit payment processing, the corresponding time will be marked as the audit payment termination time. At this moment, the time difference between the end time of the review and payment and the start time of the review and payment is calculated to obtain the total review and payment time Tbgs, obtain the universal analysis value of each universal contract virtual node (a universal contract virtual node is a virtual node with multiple contracts), obtain the independent analysis value of each independent contract virtual node (an independent contract virtual node is a virtual node with only one contract), sum up the universal analysis values ​​of all universal contract virtual nodes and take the average value to calculate the average universal analysis value ALLPr(fx), sum up the independent analysis values ​​of all independent contract virtual nodes and take the average value to calculate the average independent analysis value ALLYh(kn), through The audit payment deep assessment value Dz(kne) corresponding to this audit payment processing is calculated, where as3 is the auxiliary coefficient No. 3, as4 is the auxiliary coefficient No. 4, and as5 is the auxiliary coefficient No. 5. The value of the auxiliary coefficient No. 3 is 0.74, the value of the auxiliary coefficient No. 4 is 0.92, and the value of the auxiliary coefficient No. 5 is 0.95.

[0040] The steps for obtaining the general analysis value of the general contract virtual node are as follows: select a general contract virtual node, collect all the contract verification logs of the general contract virtual node, sort all the contract verification logs in the order of generation, compare the verification contract names of the two adjacent contract verification logs after sorting, and when the two verification contract names are different, combine the resource consumption data of the two contract verification logs into a resource consumption data group (when the two verification contract names are the same, do not combine them), build a resource consumption comparison model, import the resource consumption data group into the resource consumption comparison model, and the resource consumption comparison model derives a resource consumption data group. The resource consumption comparison value is set, and the resource consumption comparison threshold is set. When the resource consumption comparison value ≥ the resource consumption comparison threshold, the switching fluctuation times are increased by one, and the switching fluctuation times are marked as CLP(s). All resource consumption comparison values ​​are summed and the average value is calculated to obtain the average resource consumption comparison value EZG. The general analysis value Pr(fx) of the general contract virtual node is calculated by Pr(fx)=CLP(s)*as1+EZG*as2, where as1 is the auxiliary coefficient No. 1 and as2 is the auxiliary coefficient No. 2. The value of the auxiliary coefficient No. 1 is 1.92, and the value of the auxiliary coefficient No. 2 is 1.19.

[0041] The steps for obtaining the independent analysis value of the independent contract virtual node are as follows: select an independent contract virtual node, collect all contract verification logs of the independent contract virtual node, compare all contract verification logs in pairs, and when the resource consumption data of the two compared contract verification logs are combined into a resource consumption data group, obtain the resource consumption comparison value Yavg corresponding to each resource consumption data group, v=1, 2, ..., V-1, V, v represents a corresponding resource consumption data group, V is the total number of resource consumption data groups, set the resource consumption comparison coefficient to PPg, g=1, 2, ..., G-1, G, PP1<PP2<...<PPG-1<PPG, set each resource consumption comparison coefficient to a range of resource consumption comparison values, the range of resource consumption comparison values ​​includes (0, Yav1], (Yav1, Yav2], ..., (YavG-1, YavG], when the resource consumption comparison value Yavg∈(0, Yav1], the resource consumption comparison coefficient is PP1, through The independent analysis value Yh(kn) of the independent contract virtual node is calculated.

[0042] The process of building a resource consumption comparison model: build a deep learning model and obtain L resource consumption data groups. Each resource consumption data group contains two resource consumption data. Use the resource consumption data group as the basic data to train the built deep learning model. In this process, each resource consumption data group is assigned a resource consumption comparison value. The value range of the resource consumption comparison value is set between 0 and 5. It should be emphasized that the size of the resource consumption comparison value has a clear meaning. The larger the value, the greater the difference between the two resource consumption data in the resource consumption data group. Then, we divide the collected L resource consumption data groups into training set, validation set and test set according to a specific ratio. The specific division ratio is determined to be 70%:20%:10%. This division method facilitates comprehensive and scientific model training, verification, and final performance testing. After training is complete and the data set is divided, the deep learning model is first repeatedly trained using the training set. During the training process, the validation set is used to timely verify the model's performance during the training phase. Based on the verification results, the model parameters are adjusted in a timely manner to optimize the model structure and develop it in a more accurate and stable direction. When the model's performance on the training and validation sets meets the expected results, the test set is used to conduct a final performance test of the model to verify the model's generalization ability and accuracy on data that was not involved in the training. After this series of rigorous training, verification, and testing processes, when all model indicators meet the requirements, a resource consumption comparison model is successfully built.

[0043] The node model deployment module of the present invention is based on the real contract configuration (data quality, fee limit, clinical rules and other contracts) and hardware parameters (CPU / memory / storage) of the blockchain node to achieve risk-free simulation processing of unaudited bills. The bill allocation analysis module reviews payment processing multiple times (each time using different node grouping, contract combination, and resource scheduling strategy) to expose in advance the resource bottlenecks (such as node memory overflow), rule conflicts (such as contradictions between medical insurance and commercial insurance clauses), and efficiency bottlenecks (such as cross-chain communication delays) that may occur in the real environment, and realize the full-link digital mapping of "physical node → virtual node → simulation strategy", solving the pain point of "strategy optimization relying on experience" in traditional blockchain systems, solving the efficiency and compliance pain points of traditional medical bill processing, and building a new review and payment model of "data-driven, intelligent decision-making" through technological innovation.

[0044] Example 2: Reference Figure 2 , a blockchain-based medical bill review and payment method, the steps are as follows:

[0045] S1: Regularly collect all medical bills that have been uploaded but not yet reviewed and paid, and simultaneously determine the contracts and node configurations deployed on each blockchain node.

[0046] S2: According to the contract deployed by each blockchain node and the node configuration, a function node review payment model based on the blockchain is built.

[0047] S3: All medical bills uploaded and not executed review payment are imported into the function node review payment model, and the function node review payment model is controlled to execute multiple review payment processes to obtain the review payment deep evaluation value corresponding to each review payment process.

[0048] S4: Select the review payment allocation mode corresponding to the review payment process with the maximum review payment deep evaluation value, and execute review payment on all medical bills uploaded and not executed review payment.

[0049] The above formulas are dimensionless to calculate the numerical value, the formula is obtained by software simulation of a large amount of data to obtain the latest real situation, and the preset parameters in the formula are set by the person skilled in the art according to the actual situation.

[0050] The above embodiments can be realized wholly or partially by software, hardware, firmware or any other combination. When realized by software, the above embodiments can be realized wholly or partially in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are wholly or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable devices. The computer instructions can be stored in a computer readable storage medium or transferred from one computer readable storage medium to another, for example, the computer instructions can be transferred from one website, computer, server or data center to another website, computer, server or data center through wired or wireless (such as infrared, wireless, microwave, etc.) mode. The computer readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center and the like containing one or more available medium sets. The available medium can be magnetic medium (such as floppy disk, hard disk, magnetic tape), optical medium (such as DVD) or semiconductor medium. The semiconductor medium can be a solid state disk.

[0051] It should be understood that in various embodiments of the present application, the size of the serial number of each process does not mean the order of execution, and the execution order of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0052] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0053] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0054] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0055] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0056] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A blockchain-based medical bill review and payment system, characterized by: include The medical bill confirmation module regularly collects all medical bills that have been uploaded but not yet reviewed and paid, and simultaneously determines the contract and node configuration deployed on each blockchain node; The node model deployment module builds a blockchain-based functional node review and payment model based on the contracts deployed by each blockchain node and the node configuration; The bill allocation analysis module imports all medical bills that have been uploaded but not yet reviewed and paid into the functional node review and payment model, controls the functional node review and payment model to execute multiple review and payment processes, and obtains the review and payment in-depth evaluation value corresponding to each review and payment process; The review and payment execution module selects the review and payment allocation method corresponding to the review and payment processing with the largest review and payment deep evaluation value, and executes review and payment for all medical bills that have been uploaded but not yet reviewed and paid.

2. A blockchain-based medical bill review and payment system according to claim 1, characterized in that: The steps for obtaining the audit payment deep evaluation value corresponding to an audit payment process are as follows: the control function node audit payment model starts to perform audit payment processing on all medical bills, and the corresponding time is marked as the audit payment start time. During the processing, each time the virtual node completes a contract verification work, it generates a contract verification log. When all medical bills complete the audit payment processing, the corresponding time is marked as the audit payment end time, and then the total audit payment time Tbgs and the average general analysis value ALL are obtained. and the average independent analysis value ALLYh(kn), by Calculate the audit payment deep evaluation value corresponding to this audit payment process ,in, is the third auxiliary coefficient, is the fourth auxiliary coefficient, and as5 is the fifth auxiliary coefficient.

3. A blockchain-based medical bill review and payment system according to claim 2, characterized in that: The contract verification log includes the virtual node ID, verification contract name, and resource consumption data.

4. A blockchain-based medical bill review and payment system according to claim 2, characterized in that: Steps for obtaining the total review and payment time Tbgs: Calculate the time difference between the review and payment end time and the review and payment start time to obtain the total review and payment time Tbgs.

5. A blockchain-based medical bill review and payment system according to claim 2, characterized in that: Average universal analysis value ALL Acquisition steps: Get the universal analysis value of each universal contract virtual node, get the independent analysis value of each independent contract virtual node, sum up the universal analysis values ​​of all universal contract virtual nodes and take the average value to calculate the average universal analysis value ALL .

6. A blockchain-based medical bill review and payment system according to claim 5, characterized in that: The steps for obtaining the universal analysis value of the universal contract virtual node are as follows: select a universal contract virtual node, collect all contract verification logs of the universal contract virtual node, sort all contract verification logs in the order of generation, compare the verification contract names of the two adjacent contract verification logs after sorting, and when the two verification contract names are different, combine the resource consumption data of the two contract verification logs into a resource consumption data group, build a resource consumption comparison model, import the resource consumption data group into the resource consumption comparison model, and derive a resource consumption comparison value from the resource consumption comparison model. Set the resource consumption comparison threshold, and when the resource consumption comparison value ≥ the resource consumption comparison threshold, increase the switching fluctuation number by one, and mark the switching fluctuation number as CLP (s). Sum all resource consumption comparison values ​​and take the average value to calculate the average resource consumption comparison value EZG. Calculate the general analysis value of the general contract virtual node , where as1 is the first auxiliary coefficient and as2 is the second auxiliary coefficient.

7. A blockchain-based medical bill review and payment system according to claim 2, characterized in that: Steps for obtaining the average independent analysis value ALLYh (kn): sum up the independent analysis values ​​of all independent contract virtual nodes and take the average value to calculate the average independent analysis value ALLYh (kn).

8. A blockchain-based medical bill review and payment method, applied to a blockchain-based medical bill review and payment system according to any one of claims 1 to 7, characterized in that: Here are the steps: S1: Regularly collect all medical bills that have been uploaded but not yet reviewed and paid, and simultaneously determine the contracts and node configurations deployed on each blockchain node; S2: Build a blockchain-based functional node review and payment model based on the contracts deployed by each blockchain node and the node configuration; S3: Import all uploaded medical bills that have not yet been reviewed and paid into the functional node review and payment model, control the functional node review and payment model to perform multiple review and payment processes, and obtain the review and payment in-depth evaluation value corresponding to each review and payment process; S4: Select the audit payment allocation method corresponding to the audit payment processing with the largest audit payment deep evaluation value, and perform audit payment on all medical bills that have been uploaded but not yet audited and paid.

Images