A large-scale settlement system based on blockchain

Abstract

The present invention discloses a large-scale settlement system based on blockchain, which is applicable to various medical institutions, including a data source module, a medical institution module, a human resources and social security institution module, a commercial insurance institution module, a certificate chain, a storage module and a data processing module. The data source module is bidirectionally connected to the storage module, the medical institution module is bidirectionally connected to the storage module, the human resources and social security institution module is bidirectionally connected to the storage module, the commercial insurance institution module is bidirectionally connected to the storage module, the certificate chain is bidirectionally connected to the storage module, and the storage module is bidirectionally connected to the data processing module. The beneficial effects of the present invention are: identity authentication based on facial images and identity sequences is adopted, facial images are difficult to be forged or misused, and facial images correspond to identity sequences one by one, which can reduce identity theft and fraud.

Description

Technical Field

[0001] The present invention relates to the technical field of settlement systems, and in particular to a large-scale settlement system based on blockchain. Background Art

[0002] If a traditional large-scale settlement system is found to have been hacked and tampered with after settlement, it is difficult to recover the settled funds. In addition, there are currently multiple settlement methods, and users may need to perform settlement operations in different settlement systems. Therefore, a secure and efficient large-scale settlement system is needed to solve the following problems existing in the existing technology:

[0003] 1. Most of them use passwords, PIN codes and smart cards to identify identity information for identity authentication. This type of identity authentication has low security, is easy to be forgotten or lost, and is easy to be illegally invaded and tampered with, which is prone to identity theft and fraud;

[0004] 2. Most large-scale settlement systems cover too few institutions, and users may need to switch between different institutions to perform settlement operations, which increases the complexity and inconvenience of operations;

[0005] 3. Most large-scale settlement system data storage is too centralized, with many manual steps involved, lack of supervision and opaque regulation, and the risk of data leakage and tampering. Summary of the invention

[0006] The purpose of the present invention is to provide a large-scale settlement system based on blockchain to solve the problems mentioned in the above background technology that most of the large-scale settlement systems are prone to identity theft and fraud, the institutions covered are too single and the data storage is too centralized.

[0007] To achieve the above-mentioned objectives, the present invention provides the following technical solutions: a large-scale settlement system based on blockchain, suitable for various types of medical institutions, including a data source module, a medical institution module, a human resources and social security institution module, a commercial insurance institution module, a certificate chain, a storage module and a data processing module, the data source module is bidirectionally connected to the storage module, the medical institution module is bidirectionally connected to the storage module, the human resources and social security institution module is bidirectionally connected to the storage module, the commercial insurance institution module is bidirectionally connected to the storage module, the certificate chain is bidirectionally connected to the storage module, and the storage module is bidirectionally connected to the data processing module.

[0008] The medical institution module includes a face collection unit, a patient identity collection unit and a first bill acquisition unit, the human resources and social security institution module includes a first insurance policy acquisition unit and a second bill acquisition unit, and the commercial insurance institution module includes a second insurance policy acquisition unit and a third bill acquisition unit.

[0009] The storage module includes an identity information storage unit, a medical institution storage unit, a human resources and social security institution storage unit, a commercial insurance institution storage unit and a certification chain storage unit.

[0010] The identity information storage unit stores the relevant information and related data collected by the data source module, the medical institution storage unit stores the relevant information and related data collected by the medical institution module, the human resources and social security agency storage unit stores the relevant information and related data collected by the human resources and social security agency module, the commercial insurance agency storage unit stores the relevant information and related data collected by the commercial insurance agency module, and the evidence chain storage unit stores the relevant information and related data of all blocks in the evidence chain.

[0011] The data source module collects identity information, which includes face information and identity sequence. Each person corresponds to one piece of identity information, and the identity sequence is a numerical value of fixed length.

[0012] The data source module sends the facial information to the data processing module through the storage module. The data processing module processes the facial information to obtain a first feature vector of the facial information. The first feature vector is a one-dimensional vector. The data source module sends multiple first feature vectors and multiple identity sequences to the storage module for storage.

[0013] The face acquisition unit acquires face images of patients when they visit the hospital. The face acquisition unit sends the face images to the data processing module through the storage module. The data processing module processes the face images to obtain face feature vectors of the face images. The face feature vectors are one-dimensional vectors. The face feature vectors are stored in the medical institution storage unit.

[0014] The data processing module retrieves the multiple first feature vectors stored in the identity information storage unit, the data processing module compares the similarity between the facial feature vector and the multiple first feature vectors respectively, and determines the first feature vector that is most similar to the facial feature vector as the target facial information, and the data processing module retrieves the multiple identity sequences stored in the identity information storage unit to obtain the target identity sequence corresponding to the target facial information.

[0015] The patient identity collection unit can collect the patient's medical identity sequence, and the medical identity sequence is a numerical value of a fixed length, and the medical identity sequence has the same numerical length as the identity sequence. The patient identity collection unit sends the medical identity sequence to the data processing module through the storage module, and the data processing module compares the numerical value of the medical identity sequence with the numerical value of the target identity sequence.

[0016] By comparing the patient's facial image with the multiple facial information collected by the data source module, and comparing the identity sequence corresponding to the recognized facial information with the identity sequence of the patient, it is confirmed whether the patient has committed identity theft and fraud, thereby improving the accuracy of identity authentication.

[0017] The first bill acquisition unit acquires a patient's medical bill, an examination bill, and a prescription bill after seeing a doctor, and determines the medical bill, the examination bill, and the prescription bill as a first bill.

[0018] The first insurance policy acquisition unit acquires the target social insurance information of the patient according to the patient identity sequence.

[0019] The second bill acquisition unit can obtain a social insurance reimbursement bill according to the first bill and the target social insurance information, and can obtain a second bill after social insurance reimbursement through the first bill and the social insurance reimbursement bill.

[0020] The second insurance policy acquisition unit acquires the target commercial insurance information of the patient according to the patient identity sequence.

[0021] The third bill acquisition unit can obtain the commercial insurance reimbursement bill according to the second bill and the target commercial insurance information, and can obtain the third bill after commercial insurance reimbursement through the second bill and the commercial insurance reimbursement bill.

[0022] The present invention realizes information sharing among data sources, human resources and social security agencies, commercial insurance agencies and medical institutions by adding the data source module, the human resources and social security agencies and commercial insurance agencies module, and can perform identity authentication on patients in real time when they visit the hospital, thereby reducing the occurrence of identity theft and fraud. The patient's social security information and commercial insurance information can be obtained in real time, reducing the involvement of manual links, so that patients do not need to go to human resources and social security agencies and commercial insurance agencies for social security reimbursement and commercial insurance reimbursement after the consultation, making the patient settlement process more efficient.

[0023] The evidence chain is used to store data of the settlement system. The evidence chain is a database composed of nodes belonging to the data source module, the medical institution module, the human resources and social security institution module and the commercial insurance institution module. The nodes belonging to the data source module are determined as data source nodes, the nodes belonging to the medical institution module are determined as medical institution nodes, the nodes belonging to the human resources and social security institution module are determined as human resources and social security institution nodes, and the nodes belonging to the commercial insurance institution module are determined as commercial insurance institution nodes.

[0024] The evidence chain includes multiple data source nodes, multiple medical institution nodes, multiple human resources and social security institution nodes and multiple commercial insurance institution nodes. The multiple data source nodes are determined as data source blocks, the multiple medical institution nodes are determined as medical institution blocks, the multiple human resources and social security institution nodes are determined as human resources and social security institution blocks, and the multiple commercial insurance institution nodes are determined as commercial insurance institution blocks. The output end of the data source block is connected to the input end of the medical institution block, the output end of the medical institution block is connected to the input end of the human resources and social security institution block, and the output end of the human resources and social security institution block is connected to the input end of the commercial insurance institution block.

[0025] The hash algorithm converts a data into a hash value of fixed length through complex mathematical calculations. The hash algorithm can calculate and convert all the data in the evidence chain into hash values. The asymmetric encryption algorithm can obtain the public key and private key of all nodes in the evidence chain. The public key and private key correspond one to one. When the public key signs the node, it can only be decrypted using the corresponding private key. When the private key signs the node, it can only be decrypted using the corresponding public key.

[0026] It also includes a settlement process, which includes step S1: determining whether the identity of the patient is abnormal;

[0027] Step S2: The first bill acquisition unit acquires the patient's medical bill, examination bill and prescription bill after seeing a doctor, and determines the medical bill, examination bill and prescription bill as the first bill;

[0028] Step S3: Obtain the patient's social insurance reimbursement bill, and obtain a second bill after social insurance reimbursement;

[0029] Step S4: Obtain the patient's commercial insurance reimbursement bill, and obtain the third bill after commercial insurance reimbursement;

[0030] Step S5: The patient pays according to the third bill.

[0031] The step S1 comprises the following specific steps:

[0032] S1.1: Collect identity information through the data source module, the identity information includes face information and identity sequence, and the data source module sends the face information to the data processing module through the storage module;

[0033] S1.2: the data processing module extracts features from the plurality of face information by a convolutional neural network to obtain a plurality of feature vectors of the face information, and performs mean pooling on the plurality of feature vectors of the face information to obtain a first feature vector;

[0034] S1.3: The face acquisition unit acquires a face image of the patient during the visit, and the face acquisition unit sends the face image to the data processing module through the storage module;

[0035] S1.4: the data processing module extracts features from the face image through a convolutional neural network to obtain a plurality of feature vectors of the face image, and performs mean pooling on the plurality of feature vectors of the face image to obtain a face feature vector;

[0036] S1.5: The data processing module retrieves the multiple first feature vectors stored in the storage module, and the data processing module compares the similarity between the facial feature vector and the multiple first feature vectors respectively through cosine similarity, and determines the first feature vector that is most similar to the facial feature vector as the target facial information;

[0037] S1.6: The data processing module retrieves the multiple identity sequences stored in the storage module to obtain a target identity sequence corresponding to the target face information;

[0038] S1.7: The patient identity collection unit collects the patient's medical identification sequence, and the patient identity collection unit sends the medical identification sequence to the data processing module through the storage module;

[0039] S1.8: The data processing module compares the value of the patient identity sequence with the value of the target identity sequence. If the value of the patient identity sequence is the same as the value of the target identity sequence, the identity of the patient is normal. If the value of the patient identity sequence is different from the value of the target identity sequence, the identity of the patient is abnormal.

[0040] The step S3 comprises the following specific steps:

[0041] S3.1: The data processing module sends the patient's medical identification sequence to the first insurance policy acquisition unit through the storage module;

[0042] S3.2: The first insurance policy acquisition unit acquires the target social insurance information of the patient according to the patient identification sequence, and the first insurance policy acquisition unit sends the target social insurance information to the data processing module through the storage module;

[0043] S3.3: The data processing module sends the first bill and the target social security information to the second bill acquisition unit through the storage module;

[0044] S3.4: The second bill acquisition unit can obtain a social insurance reimbursement bill according to the first bill and the target social insurance information, and can obtain a second bill after social insurance reimbursement through the first bill and the social insurance reimbursement bill.

[0045] The step S4 comprises the following specific steps:

[0046] S4.1: The data processing module sends the patient's medical identification sequence to the second insurance policy acquisition unit through the storage module;

[0047] S4.2: The second insurance policy acquisition unit acquires the target commercial insurance information of the patient according to the patient identification sequence, and the second insurance policy acquisition unit sends the target commercial insurance information to the data processing module through the storage module;

[0048] S4.3: The data processing module sends the second bill and the target commercial insurance information to the third bill acquisition unit through the storage module;

[0049] S4.4: The third bill obtaining unit may obtain a commercial insurance reimbursement bill according to the second bill and the target commercial insurance information, and may obtain a third bill after commercial insurance reimbursement through the second bill and the commercial insurance reimbursement bill.

[0050] The evidence storage method of the evidence storage chain includes:

[0051] Step P1: The data source block broadcasts the relevant information and data collected by the data source module to the evidence chain;

[0052] Step P2: The medical institution block broadcasts the relevant information and data collected by the medical institution module to the evidence chain;

[0053] Step P3: The human resources and social security agency block broadcasts the relevant information and data collected by the human resources and social security agency module to the evidence chain;

[0054] Step P4: The commercial insurance agency block broadcasts the relevant information and data collected by the commercial insurance agency module to the evidence chain.

[0055] The step P1 comprises the following specific steps:

[0056] P1.1: The data source block calculates the multiple data source nodes through the asymmetric encryption algorithm to obtain multiple first public keys and multiple first private keys of the multiple data source nodes;

[0057] P1.2: The data source node calculates the first feature vector through a hash algorithm to obtain a first hash value, and the data source node calculates the identity sequence through a hash algorithm to obtain a second hash value;

[0058] P1.3: The data source node uses the first private key to sign the first hash value and the second hash value.

[0059] The remaining data source nodes in the data source block can use the corresponding first public key for verification to ensure the security and credibility of the data.

[0060] The step P2 comprises the following specific steps:

[0061] P2.1: The medical institution block calculates multiple medical institution nodes through an asymmetric encryption algorithm to obtain multiple second public keys and multiple second private keys of the multiple medical institution nodes;

[0062] P2.2: The medical institution node calculates the facial feature vector through a hash algorithm to obtain a third hash value, the medical institution node calculates the medical identity sequence through a hash algorithm to obtain a fourth hash value, and the medical institution node calculates the first bill through a hash algorithm to obtain a fifth hash value;

[0063] P2.3: The medical institution node uses the second private key to sign the third hash value, the fourth hash value and the fifth hash value.

[0064] The remaining medical institution nodes in the medical institution block can use the corresponding second public key for verification to ensure the security and credibility of the data.

[0065] The step P3 comprises the following specific steps:

[0066] P3.1: The human resources and social security agency block calculates multiple human resources and social security agency nodes through an asymmetric encryption algorithm to obtain multiple third public keys and multiple third private keys of the multiple human resources and social security agency nodes;

[0067] P3.2: The human resources and social security agency node calculates the target social security information through a hash algorithm to obtain a sixth hash value, and the human resources and social security agency node calculates the second bill through a hash algorithm to obtain a seventh hash value;

[0068] P3.3: The human resources and social security agency node uses the third private key to sign the sixth hash value and the seventh hash value.

[0069] The remaining human resources and social security agency nodes in the human resources and social security agency block can use the corresponding third public key for verification to ensure the security and credibility of the data.

[0070] The step P4 comprises the following specific steps:

[0071] P4.1: The commercial insurance agency block calculates multiple commercial insurance agency nodes through an asymmetric encryption algorithm to obtain multiple fourth public keys and multiple fourth private keys of the multiple commercial insurance agency nodes;

[0072] P4.2: The commercial insurance agency node calculates the target commercial insurance information through a hash algorithm to obtain an eighth hash value, and the commercial insurance agency node calculates the third bill through a hash algorithm to obtain a ninth hash value;

[0073] P4.3: The commercial insurance agency node uses the fourth private key to sign the eighth hash value and the ninth hash value.

[0074] The remaining commercial insurance agency nodes in the commercial insurance agency block can use the corresponding fourth public key for verification to ensure the security and credibility of the data.

[0075] All nodes in the evidence chain can input information in real time. When a node has a problem, other nodes will continue to operate as usual, allowing the evidence chain to operate normally. After the settlement is completed, the regulator can check the relevant information and data of each block in the evidence chain to avoid data unreliability caused by human tampering.

[0076] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure.

[0077] Compared with the prior art, the present invention has the following beneficial effects:

[0078] 1. Identity authentication based on face images and identity sequences is adopted. Face images are difficult to be forged or used fraudulently, and face images correspond to identity sequences one by one, which can reduce identity theft and fraud;

[0079] 2. Covering multiple institutions, it can provide a more convenient settlement method, making settlement efficient and accurate;

[0080] 3. Large-scale settlement systems using blockchain can achieve decentralized point-to-point writing through hash algorithms and asymmetric encryption algorithms, thereby solving the common problems of unreliable data and insecure data storage in centralized institutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the drawings required for the implementation methods or the prior art descriptions are briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0082] Figure 1 It is the overall system block diagram of the present invention;

[0083] Figure 2 It is the overall flow chart of the present invention;

[0084] Figure 3 This is a block diagram of the evidence chain of the present invention;

[0085] Figure 4 This is the evidence storage flow chart of the evidence storage chain of the present invention.

[0086] Among them, 1. Data source module; 2. Medical institution module; 3. Human resources and social security institution module; 4. Commercial insurance institution module; 5. Evidence chain; 6. Storage module; 7. Data processing module; 201. Face collection unit; 202. Patient identity collection unit; 203. First bill acquisition unit; 301. First insurance policy acquisition unit; 302. Second bill acquisition unit; 401. Second insurance policy acquisition unit; 402. Third bill acquisition unit; 501. Data source block; 502. Medical institution block; 503. Human resources and social security institution block; 504. Commercial insurance institution block; 601. Identity information storage unit; 602. Medical institution storage unit; 603. Human resources and social security institution storage unit; 604. Commercial insurance institution storage unit; 605. Evidence chain storage unit. DETAILED DESCRIPTION

[0087] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices consistent with some aspects of the present disclosure as detailed in the appended claims.

[0088] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0089] See also Figure 1As shown, the present invention provides a large-scale settlement system based on blockchain, which is suitable for various types of medical institutions, including a data source module 1, a medical institution module 2, a human resources and social security institution module 3, a commercial insurance institution module 4, a certificate chain 5, a storage module 6 and a data processing module 7. The data source module 1 is bidirectionally connected to the storage module 6, the medical institution module 2 is bidirectionally connected to the storage module 6, the human resources and social security institution module 3 is bidirectionally connected to the storage module 6, the commercial insurance institution module 4 is bidirectionally connected to the storage module 6, the certificate chain 5 is bidirectionally connected to the storage module 6, and the storage module 6 is bidirectionally connected to the data processing module 7.

[0090] The medical institution module 2 includes a face collection unit 201, a patient identity collection unit 202 and a first bill acquisition unit 203, the human resources and social security institution module 3 includes a first insurance policy acquisition unit 301 and a second bill acquisition unit 302, and the commercial insurance institution module 4 includes a second insurance policy acquisition unit 401 and a third bill acquisition unit 402.

[0091] The storage module 6 includes an identity information storage unit 601, a medical institution storage unit 602, a human resources and social security institution storage unit 603, a commercial insurance institution storage unit 604 and a proof chain storage unit 605. The identity information storage unit 601 stores the relevant information and relevant data collected by the data source module 1, the medical institution storage unit 602 stores the relevant information and relevant data collected by the medical institution module 2, the human resources and social security institution storage unit 603 stores the relevant information and relevant data collected by the human resources and social security institution module 3, the commercial insurance institution storage unit 604 stores the relevant information and relevant data collected by the commercial insurance institution module 4, and the proof chain storage unit 605 stores the relevant information and relevant data of all blocks in the proof chain 5.

[0092] The data source module 1 collects identity information, and the identity information includes facial information and an identity sequence. Each person corresponds to one piece of identity information, that is, each person corresponds to one piece of facial information and one identity sequence, and the identity sequence is a value of a fixed length.

[0093] The data source module 1 sends the facial information to the data processing module 7 through the storage module 6. The data processing module 7 extracts features of the facial information through a convolutional neural network to obtain multiple feature vectors of the facial information. The multiple feature vectors of the facial information are mean-pooled to obtain a first feature vector, which is a one-dimensional vector. Multiple first feature vectors and multiple identity sequences are stored in the identity information storage unit 601.

[0094] The face acquisition unit 201 acquires a face image of a patient when the patient visits the hospital. The face acquisition unit 201 sends the face image to the data processing module 7 through the storage module 6. The data processing module 7 extracts features of the face image through a convolutional neural network to obtain multiple feature vectors of the face image. The multiple feature vectors of the face image are mean-pooled to obtain a face feature vector. The face feature vector is a one-dimensional vector. The face feature vector is stored in the medical institution storage unit 602.

[0095] The data processing module 7 retrieves the multiple first feature vectors stored in the identity information storage unit 601, and the data processing module 7 compares the similarity between the facial feature vector and the multiple first feature vectors through cosine similarity, determines the first feature vector most similar to the facial feature vector as the target facial information, and determines the identity sequence corresponding to the target facial information as the target identity sequence. The data processing module 7 retrieves the multiple identity sequences stored in the identity information storage unit 601 to obtain the target identity sequence corresponding to the target facial information.

[0096] The patient identity collection unit 202 can collect the patient's medical identity sequence, and the medical identity sequence is a numerical value of a fixed length, and the numerical length of the medical identity sequence is the same as the identity sequence. The patient identity collection unit 202 sends the medical identity sequence to the data processing module 7 through the storage module 6. The data processing module 7 compares the numerical length of the medical identity sequence with the numerical length of the target identity sequence, and can determine whether the numerical length of the medical identity sequence is the same as the numerical length of the target identity sequence.

[0097] By comparing the patient's facial image with the multiple facial information collected by the data source module 1, and comparing the identity sequence corresponding to the identified facial information with the identity sequence of the patient, it is confirmed whether the patient has committed identity theft and fraud, thereby improving the accuracy of identity authentication.

[0098] The first bill acquisition unit 203 acquires the patient's medical bill, examination bill and prescription bill after medical treatment, and determines the medical bill, the examination bill and the prescription bill as the first bill. The first bill acquisition unit 203 sends the first bill to the data processing module 7 through the storage module 6.

[0099] The first insurance policy acquisition unit 301 can acquire the social security information of the patient. The data processing module 7 sends the patient's medical identity sequence to the first insurance policy acquisition unit 301 through the storage module 6. The first insurance policy acquisition unit 301 acquires the target social security information of the patient based on the patient's medical identity sequence. The first insurance policy acquisition unit 301 sends the target social security information to the data processing module 7 through the storage module 6.

[0100] The data processing module 7 sends the first bill and the target social security information to the second bill acquisition unit 302 through the storage module 6. The second bill acquisition unit 302 obtains the social security reimbursement bill based on the first bill and the target social security information, and calculates the second bill after social security reimbursement through the first bill and the social security reimbursement bill.

[0101] The second insurance policy acquisition unit 401 can acquire the commercial insurance information of the patient, and the data processing module 7 sends the patient's medical identity sequence to the second insurance policy acquisition unit 401 through the storage module 6. The second insurance policy acquisition unit 401 acquires the target commercial insurance information of the patient according to the patient's medical identity sequence, and the second insurance policy acquisition unit 401 sends the target commercial insurance information to the data processing module 7 through the storage module 6.

[0102] The data processing module 7 sends the second bill and the target commercial insurance information to the third bill acquisition unit 402 through the storage module 6. The third bill acquisition unit 402 can obtain the commercial insurance reimbursement bill based on the second bill and the target commercial insurance information, and calculate the third bill after commercial insurance reimbursement through the second bill and the commercial insurance reimbursement bill.

[0103] The present invention realizes information sharing among data sources, human resources and social security agencies, commercial insurance agencies and medical institutions by adding the data source module 1, the human resources and social security agency module 3 and the commercial insurance agency module 4, and can perform identity authentication on patients in real time when they visit the hospital, thereby reducing identity theft and corresponding fraudulent behaviors such as insurance fraud. At the same time, the settlement system can obtain the patient's social security information and commercial insurance information in real time, reducing the involvement of manual links, so that patients do not need to go to human resources and social security agencies and commercial insurance agencies for social security reimbursement and commercial insurance reimbursement after the medical treatment, making the patient settlement process more efficient.

[0104] See also Figure 2 As shown, it also includes a settlement process, and the settlement process includes step S1: determining whether the identity of the patient is abnormal;

[0105] Step S2: The first bill acquisition unit 203 acquires the patient's medical bill, examination bill and prescription bill after the patient's visit, and determines the medical bill, examination bill and prescription bill as the first bill;

[0106] Step S3: Obtain the patient's social insurance reimbursement bill, and obtain a second bill after social insurance reimbursement;

[0107] Step S4: Obtain the patient's commercial insurance reimbursement bill, and obtain the third bill after commercial insurance reimbursement;

[0108] Step S5: The patient pays according to the third bill.

[0109] If the patient's identity is normal in step S1, step S2 is performed; if the patient's identity is abnormal, the settlement process is terminated.

[0110] The step S1 comprises the following specific steps:

[0111] S1.1: Collect identity information through the data source module 1, the identity information includes face information and identity sequence, and the data source module 1 sends the face information to the data processing module 7 through the storage module 6;

[0112] S1.2: the data processing module 7 extracts features from the plurality of face information by using a convolutional neural network to obtain a plurality of feature vectors of the face information, and performs mean pooling on the plurality of feature vectors of the face information to obtain a first feature vector;

[0113] S1.3: The face acquisition unit 201 acquires a face image of the patient during the visit, and the face acquisition unit 201 sends the face image to the data processing module 7 through the storage module 6;

[0114] S1.4: the data processing module 7 extracts features from the face image through a convolutional neural network to obtain a plurality of feature vectors of the face image, and performs mean pooling on the plurality of feature vectors of the face image to obtain a face feature vector;

[0115] S1.5: The data processing module 7 retrieves the multiple first feature vectors stored in the storage module 6, and the data processing module 7 compares the similarity between the facial feature vector and the multiple first feature vectors respectively through cosine similarity, and determines the first feature vector that is most similar to the facial feature vector as the target facial information;

[0116] S1.6: The data processing module 7 retrieves the plurality of identity sequences stored in the storage module 6 to obtain a target identity sequence corresponding to the target face information;

[0117] S1.7: The patient identity collection unit 202 collects the patient's medical identification sequence, and the patient identity collection unit 202 sends the medical identification sequence to the data processing module 7 through the storage module 6;

[0118] S1.8: The data processing module 7 compares the value of the patient identity sequence with the value of the target identity sequence. If the value of the patient identity sequence is the same as the value of the target identity sequence, the identity of the patient is normal. If the value of the patient identity sequence is different from the value of the target identity sequence, the identity of the patient is abnormal.

[0119] The step S3 comprises the following specific steps:

[0120] S3.1: the data processing module 7 sends the patient's medical identification sequence to the first insurance policy acquisition unit 301 through the storage module 6;

[0121] S3.2: The first insurance policy acquisition unit 301 acquires the target social security information of the patient according to the patient identification sequence, and the first insurance policy acquisition unit 301 sends the target social security information to the data processing module 7 through the storage module 6;

[0122] S3.3: The data processing module 7 sends the first bill and the target social security information to the second bill obtaining unit 302 through the storage module 6;

[0123] S3.4: The second bill obtaining unit 302 can obtain a social insurance reimbursement bill according to the first bill and the target social insurance information, and can obtain a second bill after social insurance reimbursement through the first bill and the social insurance reimbursement bill.

[0124] The step S4 comprises the following specific steps:

[0125] S4.1: the data processing module 7 sends the patient's medical identification sequence to the second insurance policy acquisition unit 401 through the storage module 6;

[0126] S4.2: The second insurance policy acquisition unit 401 acquires the target commercial insurance information of the patient according to the patient identification sequence, and the second insurance policy acquisition unit 401 sends the target commercial insurance information to the data processing module 7 through the storage module 6;

[0127] S4.3: The data processing module 7 sends the second bill and the target commercial insurance information to the third bill obtaining unit 402 through the storage module 6;

[0128] S4.4: The third bill acquisition unit 402 can obtain the commercial insurance reimbursement bill according to the second bill and the target commercial insurance information, and can obtain the third bill after commercial insurance reimbursement through the second bill and the commercial insurance reimbursement bill. Social insurance and commercial insurance are connected to each other, and the third bill is directly issued to the patient. After the social insurance and commercial insurance are reimbursed, the remaining self-paid funds are paid by the patient in one lump sum, avoiding the traditional social insurance and commercial insurance that require patients to settle separately, which is cumbersome, and realizes the efficiency of online services.

[0129] See also Figure 3 As shown, the evidence chain 5 is used to store the data of the settlement system. The evidence chain 5 is a database composed of the nodes belonging to the data source module 1, the medical institution module 2, the human resources and social security institution module 3 and the commercial insurance institution module 4. The node belonging to the data source module 1 is determined as the data source node, the node belonging to the medical institution module 2 is determined as the medical institution node, the node belonging to the human resources and social security institution module 3 is determined as the human resources and social security institution node, and the node belonging to the commercial insurance institution module 4 is determined as the commercial insurance institution node.

[0130] The evidence chain 5 includes multiple data source nodes, multiple medical institution nodes, multiple human resources and social security institution nodes and multiple commercial insurance institution nodes. The multiple data source nodes are determined as data source blocks 501, the multiple medical institution nodes are determined as medical institution blocks 502, the multiple human resources and social security institution nodes are determined as human resources and social security institution blocks 503, and the multiple commercial insurance institution nodes are determined as commercial insurance institution blocks 504. The output end of the data source block 501 is connected to the input end of the medical institution block 502, the output end of the medical institution block 502 is connected to the input end of the human resources and social security institution block 503, and the output end of the human resources and social security institution block 503 is connected to the input end of the commercial insurance institution block 504.

[0131] Multiple data source nodes are used to enter relevant information and related data of the data source module 1, multiple medical institution nodes are used to enter relevant information and related data of the medical institution module 2, multiple human resources and social security agency nodes are used to enter relevant information and related data of the human resources and social security agency module 3, and multiple commercial insurance agency nodes are used to enter relevant information and related data of the commercial insurance agency module 4.

[0132] The hash algorithm converts a data into a hash value of a fixed length through complex mathematical calculations. The hash algorithm can calculate and convert all the data in the evidence chain 5 into hash values. The asymmetric encryption algorithm can obtain the public key and private key of all nodes in the evidence chain 5. The public key and private key correspond one to one. When the public key signs the node, it can only be decrypted using the corresponding private key. When the private key is used to sign the node, it can only be decrypted using the corresponding public key.

[0133] See also Figure 4 As shown, the evidence storage method of the evidence storage chain 5 includes:

[0134] Step P1: The data source block 501 broadcasts the relevant information and data collected by the data source module 1 to the evidence storage chain 5;

[0135] Step P2: The medical institution block 502 broadcasts the relevant information and data collected by the medical institution module 2 to the evidence chain 5;

[0136] Step P3: The human resources and social security agency block 503 broadcasts the relevant information and data collected by the human resources and social security agency module 3 to the evidence storage chain 5;

[0137] Step P4: The commercial insurance agency block 504 broadcasts the relevant information and data collected by the commercial insurance agency module 4 to the evidence chain 5.

[0138] The step P1 comprises the following specific steps:

[0139] P1.1: The data source block 501 calculates the multiple data source nodes through an asymmetric encryption algorithm to obtain multiple first public keys and multiple first private keys of the multiple data source nodes;

[0140] P1.2: The data source node calculates the first feature vector through a hash algorithm to obtain a first hash value, and the data source node calculates the identity sequence through a hash algorithm to obtain a second hash value;

[0141] P1.3: The data source node uses the first private key to sign the first hash value and the second hash value.

[0142] The remaining data source nodes in the data source block 501 can use the corresponding first public key for verification to ensure the security and credibility of the data.

[0143] The step P2 comprises the following specific steps:

[0144] P2.1: The medical institution block 502 calculates the plurality of medical institution nodes through an asymmetric encryption algorithm to obtain a plurality of second public keys and a plurality of second private keys of the plurality of medical institution nodes;

[0145] P2.2: The medical institution node calculates the facial feature vector through a hash algorithm to obtain a third hash value, the medical institution node calculates the medical identity sequence through a hash algorithm to obtain a fourth hash value, and the medical institution node calculates the first bill through a hash algorithm to obtain a fifth hash value;

[0146] P2.3: The medical institution node uses the second private key to sign the third hash value, the fourth hash value and the fifth hash value.

[0147] The remaining medical institution nodes in the medical institution block 502 can use the corresponding second public key for verification to ensure the security and credibility of the data.

[0148] The step P3 comprises the following specific steps:

[0149] P3.1: The human resources and social security agency block 503 calculates multiple human resources and social security agency nodes through an asymmetric encryption algorithm to obtain multiple third public keys and multiple third private keys of the multiple human resources and social security agency nodes;

[0150] P3.2: The human resources and social security agency node calculates the target social security information through a hash algorithm to obtain a sixth hash value, and the human resources and social security agency node calculates the second bill through a hash algorithm to obtain a seventh hash value;

[0151] P3.3: The human resources and social security agency node uses the third private key to sign the sixth hash value and the seventh hash value.

[0152] The remaining human resources and social security agency nodes in the human resources and social security agency block 503 can use the corresponding third public key for verification to ensure the security and credibility of the data.

[0153] The step P4 comprises the following specific steps:

[0154] P4.1: The commercial insurance agency block 504 calculates multiple commercial insurance agency nodes through an asymmetric encryption algorithm to obtain multiple fourth public keys and multiple fourth private keys of the multiple commercial insurance agency nodes;

[0155] P4.2: The commercial insurance agency node calculates the target commercial insurance information through a hash algorithm to obtain an eighth hash value, and the commercial insurance agency node calculates the third bill through a hash algorithm to obtain a ninth hash value;

[0156] P4.3: The commercial insurance agency node uses the fourth private key to sign the eighth hash value and the ninth hash value.

[0157] The remaining commercial insurance agency nodes in the commercial insurance agency block 504 can use the corresponding fourth public key for verification to ensure the security and credibility of the data.

[0158] All nodes of the evidence chain 5 can input information in real time. When a node has a problem, other nodes will continue to operate as usual, so that the evidence chain 5 can operate normally. After the settlement is completed, the supervisor can check the relevant information and data of each block in the evidence chain 5 to avoid data unreliability caused by human tampering.

[0159] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

[0160] The information and data of the subjects involved in the application are all information and data authorized by the subjects. The collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0161] The present invention and its embodiments are described above, which is not restrictive. What is shown in the accompanying drawings is only one of the embodiments of the present invention, and the actual content is not limited to this. In short, if ordinary technicians in this field are inspired by it and do not deviate from the purpose of the invention, they can creatively design structural methods and embodiments similar to the technical scheme, which should all fall within the scope of protection of the present invention.

Claims

1. A large-scale settlement system based on blockchain, suitable for various medical institutions, characterized by: The system comprises a data source module (1), a medical institution module (2), a human resources and social security institution module (3), a commercial insurance institution module (4), a certificate chain (5), a storage module (6) and a data processing module (7), wherein the data source module (1) is bidirectionally connected to the storage module (6), the medical institution module (2) is bidirectionally connected to the storage module (6), the human resources and social security institution module (3) is bidirectionally connected to the storage module (6), the commercial insurance institution module (4) is bidirectionally connected to the storage module (6), the certificate chain (5) is bidirectionally connected to the storage module (6), and the storage module (6) is bidirectionally connected to the data processing module (7); The medical institution module (2) includes a face acquisition unit (201), a patient identity acquisition unit (202) and a first bill acquisition unit (203); the human resources and social security institution module (3) includes a first insurance policy acquisition unit (301) and a second bill acquisition unit (302); and the commercial insurance institution module (4) includes a second insurance policy acquisition unit (401) and a third bill acquisition unit (402); The storage module (6) includes an identity information storage unit (601), a medical institution storage unit (602), a human resources and social security institution storage unit (603), a commercial insurance institution storage unit (604) and a certificate chain storage unit (605); The identity information storage unit (601) stores the relevant information and relevant data collected by the data source module (1); the medical institution storage unit (602) stores the relevant information and relevant data collected by the medical institution module (2); the human resources and social security institution storage unit (603) stores the relevant information and relevant data collected by the human resources and social security institution module (3); the commercial insurance institution storage unit (604) stores the relevant information and relevant data collected by the commercial insurance institution module (4); and the evidence chain storage unit (605) stores the relevant information and relevant data of all blocks in the evidence chain (5).

2. A large-scale settlement system based on blockchain according to claim 1, characterized in that: The data source module (1) collects identity information, wherein the identity information includes face information and an identity sequence, each person corresponds to one piece of identity information, and the identity sequence is a numerical value of a fixed length; The data source module (1) sends the facial information to the data processing module (7) through the storage module (6); the data processing module (7) processes the facial information to obtain a first feature vector of the facial information, wherein the first feature vector is a one-dimensional vector; the data source module (1) sends a plurality of the first feature vectors and a plurality of the identity sequences to the storage module (6) for storage; The face acquisition unit (201) acquires a face image of a patient when visiting a doctor. The face acquisition unit (201) sends the face image to the data processing module (7) via the storage module (6). The data processing module (7) processes the face image to obtain a face feature vector of the face image. The face feature vector is a one-dimensional vector. The face feature vector is stored in the medical institution storage unit (602). The data processing module (7) retrieves a plurality of the first feature vectors stored in the identity information storage unit (601), the data processing module (7) performs a similarity comparison between the face feature vector and the plurality of the first feature vectors, and determines the first feature vector that is most similar to the face feature vector as the target face information, and the data processing module (7) retrieves a plurality of the identity sequences stored in the identity information storage unit (601) to obtain the target identity sequence corresponding to the target face information; The patient identity collection unit (202) can collect the patient's medical identification sequence, the medical identification sequence is a fixed-length value, and the medical identification sequence has the same numerical length as the identity sequence. The patient identity collection unit (202) sends the medical identification sequence to the data processing module (7) through the storage module (6), and the data processing module (7) compares the numerical value of the medical identification sequence with the numerical value of the target identity sequence; The first bill acquisition unit (203) acquires the patient's medical bill, examination bill and prescription bill after seeing a doctor, and determines the medical bill, examination bill and prescription bill as the first bill; The first insurance policy acquisition unit (301) acquires the target social insurance information of the patient according to the patient identity sequence; The second bill acquisition unit (302) can obtain a social insurance reimbursement bill according to the first bill and the target social insurance information, and can obtain a second bill after social insurance reimbursement through the first bill and the social insurance reimbursement bill; The second insurance policy acquisition unit (401) acquires the target commercial insurance information of the patient according to the patient identification sequence of the patient; The third bill acquisition unit (402) can obtain a commercial insurance reimbursement bill according to the second bill and the target commercial insurance information, and can obtain a third bill after commercial insurance reimbursement through the second bill and the commercial insurance reimbursement bill.

3. A large-scale settlement system based on blockchain according to claim 1, characterized in that: The evidence chain (5) is used to store the data of the settlement system. The evidence chain (5) is a database composed of the nodes belonging to the data source module (1), the medical institution module (2), the human resources and social security institution module (3) and the commercial insurance institution module (4). The node belonging to the data source module (1) is determined as the data source node, the node belonging to the medical institution module (2) is determined as the medical institution node, the node belonging to the human resources and social security institution module (3) is determined as the human resources and social security institution node, and the node belonging to the commercial insurance institution module (4) is determined as the commercial insurance institution node; The evidence chain (5) includes multiple data source nodes, multiple medical institution nodes, multiple human resources and social security institution nodes and multiple commercial insurance institution nodes. The multiple data source nodes are determined as data source blocks (501), the multiple medical institution nodes are determined as medical institution blocks (502), the multiple human resources and social security institution nodes are determined as human resources and social security institution blocks (503), and the multiple commercial insurance institution nodes are determined as commercial insurance institution blocks (504). The output end of the data source block (501) is connected to the input end of the medical institution block (502), the output end of the medical institution block (502) is connected to the input end of the human resources and social security institution block (503), and the output end of the human resources and social security institution block (503) is connected to the input end of the commercial insurance institution block (504).

4. A large-scale settlement system based on blockchain according to claim 1, characterized in that: It also includes a settlement process, which includes step S1: determining whether the identity of the patient is abnormal; Step S2: the first bill acquisition unit (203) acquires the patient's medical bill, examination bill and prescription bill after seeing a doctor, and determines the medical bill, examination bill and prescription bill as the first bill; Step S3: Obtain the patient's social insurance reimbursement bill, and obtain a second bill after social insurance reimbursement; Step S4: Obtain the patient's commercial insurance reimbursement bill, and obtain the third bill after commercial insurance reimbursement; Step S5: The patient pays according to the third bill; If the patient's identity is normal in step S1, step S2 is performed; if the patient's identity is abnormal, the settlement process is terminated.

5. A large-scale settlement system based on blockchain according to claim 4, characterized in that: The step S1 comprises the following specific steps: S1.1: collecting identity information through the data source module (1), the identity information including facial information and identity sequence, and the data source module (1) sending the facial information to the data processing module (7) through the storage module (6); S1.2: the data processing module (7) extracts features from the plurality of face information by means of a convolutional neural network to obtain a plurality of feature vectors of the face information, and performs mean pooling on the plurality of feature vectors of the face information to obtain a first feature vector; S1.3: The face acquisition unit (201) acquires a face image of the patient during the consultation, and the face acquisition unit (201) sends the face image to the data processing module (7) via the storage module (6); S1.4: the data processing module (7) extracts features from the face image using a convolutional neural network to obtain a plurality of feature vectors of the face image, and performs mean pooling on the plurality of feature vectors of the face image to obtain a face feature vector; S1.5: the data processing module (7) retrieves the plurality of first feature vectors stored in the storage module (6), and the data processing module (7) compares the similarity between the facial feature vector and the plurality of first feature vectors respectively by using cosine similarity, and determines the first feature vector that is most similar to the facial feature vector as the target facial information; S1.6: the data processing module (7) retrieves the plurality of identity sequences stored in the storage module (6) to obtain a target identity sequence corresponding to the target face information; S1.7: The patient identity collection unit (202) collects the patient's medical identification sequence, and the patient identity collection unit (202) sends the medical identification sequence to the data processing module (7) through the storage module (6); S1.8: The data processing module (7) compares the value of the patient identity sequence with the value of the target identity sequence. If the value of the patient identity sequence is the same as the value of the target identity sequence, the patient's identity is normal. If the value of the patient identity sequence is different from the value of the target identity sequence, the patient's identity is abnormal.

6. A large-scale settlement system based on blockchain according to claim 4, characterized in that: The step S3 comprises the following specific steps: S3.1: the data processing module (7) sends the patient's medical identification sequence to the first insurance policy acquisition unit (301) through the storage module (6); S3.2: The first insurance policy acquisition unit (301) acquires the target social security information of the patient according to the patient identification sequence of the patient, and the first insurance policy acquisition unit (301) sends the target social security information to the data processing module (7) through the storage module (6); S3.3: The data processing module (7) sends the first bill and the target social security information to the second bill acquisition unit (302) through the storage module (6); S3.4: The second bill acquisition unit (302) can obtain a social insurance reimbursement bill according to the first bill and the target social insurance information, and can obtain a second bill after social insurance reimbursement through the first bill and the social insurance reimbursement bill.

7. A large-scale settlement system based on blockchain according to claim 4, characterized in that: The step S4 comprises the following specific steps: S4.1: the data processing module (7) sends the patient's medical identification sequence to the second insurance policy acquisition unit (401) through the storage module (6); S4.2: The second insurance policy acquisition unit (401) acquires the target commercial insurance information of the patient according to the patient identification sequence of the patient, and the second insurance policy acquisition unit (401) sends the target commercial insurance information to the data processing module (7) through the storage module (6); S4.3: The data processing module (7) sends the second bill and the target commercial insurance information to the third bill acquisition unit (402) through the storage module (6); S4.4: The third bill obtaining unit (402) can obtain the commercial insurance reimbursement bill according to the second bill and the target commercial insurance information, and can obtain the third bill after commercial insurance reimbursement through the second bill and the commercial insurance reimbursement bill.

8. A large-scale settlement system based on blockchain according to claim 1, characterized in that: The evidence storage method of the evidence storage chain (5) includes: Step P1: The data source block (501) broadcasts the relevant information and data collected by the data source module (1) to the evidence storage chain (5); Step P2: The medical institution block (502) broadcasts the relevant information and data collected by the medical institution module (2) to the evidence chain (5); Step P3: The human resources and social security agency block (503) broadcasts the relevant information and data collected by the human resources and social security agency module (3) to the evidence storage chain (5); Step P4: The commercial insurance agency block (504) broadcasts the relevant information and data collected by the commercial insurance agency module (4) to the evidence chain (5).

9. A large-scale settlement system based on blockchain according to claim 8, characterized in that: The step P1 comprises the following specific steps: P1.1: The data source block (501) calculates the multiple data source nodes through the asymmetric encryption algorithm to obtain multiple first public keys and multiple first private keys of the multiple data source nodes; P1.2: The data source node calculates the first feature vector through a hash algorithm to obtain a first hash value, and the data source node calculates the identity sequence through a hash algorithm to obtain a second hash value; P1.3: The data source node signs the first hash value and the second hash value using the first private key; The remaining data source nodes in the data source block (501) can use the corresponding first public key for verification to ensure the security and credibility of the data; The step P2 comprises the following specific steps: P2.1: The medical institution block (502) calculates the plurality of medical institution nodes through an asymmetric encryption algorithm to obtain a plurality of second public keys and a plurality of second private keys of the plurality of medical institution nodes; P2.2: The medical institution node calculates the facial feature vector through a hash algorithm to obtain a third hash value, the medical institution node calculates the medical identity sequence through a hash algorithm to obtain a fourth hash value, and the medical institution node calculates the first bill through a hash algorithm to obtain a fifth hash value; P2.3: The medical institution node signs the third hash value, the fourth hash value and the fifth hash value using the second private key; The remaining medical institution nodes in the medical institution block (502) may use the corresponding second public key for verification to ensure the security and credibility of the data; The step P3 comprises the following specific steps: P3.1: The human resources and social security agency block (503) calculates multiple human resources and social security agency nodes through an asymmetric encryption algorithm to obtain multiple third public keys and multiple third private keys of the multiple human resources and social security agency nodes; P3.2: The human resources and social security agency node calculates the target social security information through a hash algorithm to obtain a sixth hash value, and the human resources and social security agency node calculates the second bill through a hash algorithm to obtain a seventh hash value; P3.3: The human resources and social security agency node signs the sixth hash value and the seventh hash value using the third private key; The remaining human resources and social security agency nodes in the human resources and social security agency block (503) can use the corresponding third public key for verification to ensure the security and credibility of the data; The step P4 comprises the following specific steps: P4.1: The commercial insurance agency block (504) calculates the multiple commercial insurance agency nodes through an asymmetric encryption algorithm to obtain multiple fourth public keys and multiple fourth private keys of the multiple commercial insurance agency nodes; P4.2: The commercial insurance agency node calculates the target commercial insurance information through a hash algorithm to obtain an eighth hash value, and the commercial insurance agency node calculates the third bill through a hash algorithm to obtain a ninth hash value; P4.3: The commercial insurance agency node signs the eighth hash value and the ninth hash value using the fourth private key; The remaining commercial insurance agency nodes in the commercial insurance agency block (504) can use the corresponding fourth public key for verification to ensure the security and credibility of the data.

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