CN113808694A - Game theory-based block chain medical data sharing excitation method - Google Patents
Game theory-based block chain medical data sharing excitation method Download PDFInfo
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Abstract
The invention provides a game theory-based block chain medical data sharing excitation method, which is used for solving the problem that the current medical data cannot be freely transmitted and shared among different medical institutions; the method comprises the following steps: establishing a health chain system of the medical alliance by using an alliance chain technology; patients share their own medical data, and medical institutions manage and share the medical data in a health chain system; establishing a game model between medical data pricing and transaction amount, setting initial pricing by a medical institution according to medical data characteristics, and bidding by medical data consumers according to own requirements; calculating Nash equilibrium points of the game model by using a reverse derivation method to obtain an optimal data price and a data transaction amount; the transaction is determined and the shared transaction record is verified, broadcast and linked up into the health chain system. The invention can quickly realize the optimal pricing of medical data, and the data consumer obtains the data volume of the maximized income, and the health chain system can realize the maximization of the medical data resource benefit.
Description
Technical Field
The invention relates to the technical field of block chains, in particular to a block chain medical data sharing excitation method based on a game theory.
Background
The medical health service system mainly collects and manages the electronic medical records of patients, currently, each different medical institution has a respective independent medical health service system platform and stores and manages respective electronic medical record data, and due to respective benefits and competition among different medical institutions, the cross-institution sharing capability of the electronic medical record data is very limited. The electronic medical record contains sensitive information of patients, doctors, medical institutions and the like, and the traditional medical health service system is easy to cause problems of user privacy disclosure, EMR data loss or falsification, data islanding and the like due to a centralized storage and management mode. In order to break through the limitation of data sharing in the current healthcare service system, it is urgently needed to find a technology for promoting cooperation between different healthcare institutions and establishing deep mutual trust between each other. In recent years, an emerging technology called blockchain is a promising approach to efficient management of electronic medical records and secure sharing among different medical institutions.
The block chain is a novel data recording, storing and transmitting technology, and can achieve mutual trust and realize value transfer without depending on a third-party trust mechanism. The block chain is public, data and transactions are packaged and verified by different nodes and are recorded on a distributed account book unified in the whole network, and any node in the system can look up and verify the validity of the transactions in the public account book; the system is reliable, the common recognition of trust removal of the whole network is realized through mechanisms such as workload certification, rights and interests certification and the like, and after chain registration of data and transaction records, the records become non-falsifiable records, and anyone cannot maliciously change the records. Meanwhile, a reliable guarantee is established for the traceability of the data; the method is also safe, the safety of data and transaction in the transmission and storage process is guaranteed through a cryptographic algorithm, the transaction contains the signature of a user, and any user cannot repudiate the transaction record with the signature.
The block chain based medical health service system remarkably promotes the development of the medical health care industry, such as a health chain. The distributed storage model can effectively weaken malicious behaviors of a centralized medical institution and avoid leakage or damage of electronic medical record data caused by single-node storage faults. Secondly, the openness and verifiability of the blockchain transaction can ensure the authenticity and accuracy of the electronic medical record and prevent the operation and damage of a malicious third party. In addition, the anonymous transaction address form can strictly protect the privacy and the safety of the user on the premise of not influencing the statistical characteristics of the electronic medical record data. Although a distributed medical data management system such as a health chain can provide a distributed medical big data sharing platform for different medical institutions and users. However, how to maximize the value of medical data resources in the health chain, balance the supply and demand of medical data resources, and optimize the benefits of data providers and consumers is a problem that needs to be solved urgently.
Disclosure of Invention
In order to solve the problem that the current medical data cannot be freely transferred and shared among different medical institutions, the invention provides a block chain medical data sharing incentive method based on a game theory, the relation between an electronic medical record provider and a consumer is defined by using an economics strategy game of a Stainberg game, the optimal pricing and transaction amount of medical data resources are achieved through the game between the pricing and demand amount of the medical data resources, the sharing and transfer of the medical data among different medical institutions and users are promoted, and the economic benefit and the social benefit of the medical data resources are maximized.
The technical scheme of the invention is realized as follows:
a game theory-based block chain medical data sharing excitation method comprises the following steps: establishing a health chain system of the medical alliance, which comprises patients, doctors, medical institutions, banks and insurance institutions, by using the alliance chain technology; the patient chooses to share his own medical data, and the medical institution collects, manages and shares the medical data in the health chain system; establishing a game model between medical data pricing and transaction amount in a health chain system, setting initial pricing by a medical institution according to medical data characteristics, and bidding by medical data consumers according to own requirements; calculating Nash equilibrium points of the game model by using a reverse derivation method to obtain an optimal data price and a data transaction amount; the transaction is determined and the shared transaction record is verified, broadcast and linked up into the health chain system.
Preferably, the health chain system refers to a distributed health chain system formed by different medical institutions by using alliance chain technology; the health chain system comprises a consensus node, a system node and other nodes; the consensus nodes refer to different medical institutions and participate in the management and maintenance of the health chain system; the system node refers to a patient and a doctor, and uploads, manages and deals with own medical data; other nodes are referred to as banks and insurance agencies.
Preferably, the patient visits a medical institution, and a medical data file is established; the medical data comprises information of the patient, treatment information, information of an inquiry doctor, diagnosis result information, medical institution information and insurance information;
ownership of the medical data belongs to the patient, the patient can selectively share the medical data of the patient, and sensitive information data are hidden in the sharing process; meanwhile, in the process of managing and sharing the medical data by the medical institution, the medical data are stored in the local server, and the index of the medical data is uploaded to the health chain system;
the doctor participates in the construction of medical data and can view the medical data on the health chain system;
the medical institution is responsible for collecting and managing the medical data shared by the patients and storing the shared medical data into the health chain system;
the bank participates in the cost support required during the generation of the medical data and in the verification of the medical data in the health chain system;
the insurance agency is involved in the expense reimbursement support required during the generation of the medical data and in the verification of the medical data in the health chain system.
Preferably, the index of medical data comprises keywords, a server storage address and user signature information.
Preferably, the gaming model between pricing of medical data and transaction amount comprises:
setting initial price and interval of medical data resources according to the holding amount, demand amount and rarity degree factors of medical data and constructing a benefit function of the medical data resource provider;
the bidding strategy of the medical data resource consumer adjusts the demand of the consumer according to the bidding rule of the medical data resource provider and constructs the benefit function of the medical data resource consumer.
Preferably, the medical data resource provider is a medical institution, and the medical institution shares the collected medical data into the health chain system, and performs integration and decentralization on the medical data to exert the maximum value of the medical data resource; the medical data resource consumer is a researcher who utilizes medical data to conduct scientific research, drug research and development, and medical device manufacturing.
Preferably, the method for calculating nash equilibrium points of the game model by using the reverse derivation method is as follows:
calculating first and second derivatives of the benefit function of the medical data resource consumers, judging the convergence of the benefit function of the medical data resource consumers, and calculating to obtain the optimal medical data resource demand;
substituting the obtained optimal medical data resource demand into a benefit function of a medical data resource provider, calculating first and second derivatives of the benefit function of the medical data resource provider, judging the convergence of the benefit function of the medical data resource provider, and calculating to obtain an optimal medical data resource price;
judging whether the sum of the benefit of the medical data resource provider and the benefit of the medical data resource consumer reaches the maximum;
and when the maximization is reached, obtaining Nash equilibrium points of the game model, namely the optimal data price and the optimal transaction amount.
Preferably, the benefit function of the medical data resource provider is:
RL＝λidi-γdi；
wherein R isLIs a benefit function of the medical data resource provider, λiIs the price of the ith medical data consumer, diIs the demand of the ith medical data consumer, gamma is the coefficient of the extra operation and maintenance cost, i belongs to N, and N is the number of medical data consumers;
the benefit function of the medical data resource consumer is as follows:
RF＝Ssat-λidi；
wherein R isFIs a benefit function of the medical data resource consumer, Ssat＝αiln(di-dmin+ci) A satisfaction function representing the ith medical data consumer, ciIs a predetermined factor, dminIs the lowest demand of the ith medical data consumer, alphaiIs a preset non-zero positive factor.
Preferably, the method for validating, broadcasting and linking the shared transaction record to the health chain system comprises:
the medical data sharing transaction is verified, after the sharing is completed, a new transaction is formed by the sharing action, and a legal transaction is formed and stored on a health chain account book after the verification of the health chain verification node;
the medical data sharing transaction broadcasting, the index uploading transaction of the medical data and the sharing behavior transaction are broadcasted to the health chain whole network node by a leader node in the verification nodes after passing the verification of all the verification nodes of the health chain;
and sharing the uplink of the transaction by the medical data, wherein the transaction after broadcasting is linked to the tail end of the longest chain of the health chain whole-network unique account book along with the temporary block, the transaction also completes uplink registration, and the transaction becomes a record which can not be tampered.
Compared with the prior art, the invention has the following beneficial effects: the invention ensures the ownership of the patient user to the personal medical data, and the income generated by sharing the personal medical data is also fed back to the patient user, thereby reducing the burden of the patient for seeing a doctor and seeking a doctor; the patient can go to the doctor and ask for a doctor in any other medical institution with the personal medical data, and the authorized doctor can check the personal historical medical data to obtain more accurate diagnosis and treatment; the medical data resources are fully utilized, the improvement of the medical level, the development of medical technology, the research of medical machinery, the research and development of medicines and the like are promoted.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a medical data distributed sharing model of the present invention;
FIG. 3 is a game model of the blockchain medical data sharing incentive method of the present invention;
fig. 4 is a flow chart of the medical data sharing transaction uplink registration according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive effort based on the embodiments of the present invention, are within the scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a game theory-based blockchain medical data sharing excitation method, which includes the following steps: establishing a health chain system of the medical alliance, which comprises patients, doctors, medical institutions, banks and insurance institutions, by using the alliance chain technology; the health chain system is a distributed health chain system formed by different medical institutions by utilizing a alliance chain technology; the health chain system comprises a consensus node, a system node and other nodes; the consensus nodes refer to different medical institutions and participate in the management and maintenance of the health chain system; the system node refers to a patient and a doctor, and uploads, manages and deals with own medical data; other nodes are referred to as banks and insurance agencies. Besides, the health chain of the medical alliance also comprises other nodes, such as an account center, an audit center and the like.
The patients choose to share their own medical data, and medical institutions collect, manage and share the medical data in a health chain system; the patient visits a doctor in a medical institution and establishes a medical data file; the medical data comprises information of the patient, treatment information, information of an inquiry doctor, diagnosis result information, medical institution information and insurance information;
fig. 2 depicts the following blockchain data sharing scenario: generating medical data, wherein a patient user sees a doctor in a certain medical institution, and a medical data archive is established, wherein the ownership of the medical data belongs to the patient; local storage of medical data, medical data shared by patients, stored on a local server of the medical institution and managed by the medical institution; the cochain registration of the medical data, and the uploading of the medical data index to a record in a health chain account book for legal system users to inquire; cross-facility sharing of medical data, shared medical data being transferable between different medical facility nodes of the health chain.
S201: the patient user forms the medical data file after the medical institution visits, and the medical data file comprises information of the patient, visiting information, information of an inquiry doctor, information of a diagnosis result, information of the medical institution, insurance information and the like.
S202: and the patient selects to share own medical data and the health chain system, the medical data is encrypted by the system, and the corresponding data cipher text is stored in a local server of the medical institution, so that URL information of the storage position is generated.
S203: the medical data index is generated according to the generated medical data local storage position information URL, key words, patient signatures and other information. And the medical data index is uplink registered to the health chain account book in a searchable encryption mode.
S204: after the generated medical data is shared in the health chain system, the medical data becomes an open record, and the medical data can be retrieved by all nodes in the health chain system.
S205: the patient can view his or her medical data records at different medical institutions authorizing the different doctors that are required. And other health chain nodes can access the storage address of the medical data only through the searchable and encrypted trapdoor test, can decrypt the ciphertext data only after obtaining the medical data viewing authority, and view and use original medical data.
Ownership of the medical data belongs to the patient, the patient can selectively share the medical data of the patient, and sensitive information data are hidden in the sharing process; the sharing behavior of the patient can obtain certain income and reward, and the doctor can authorize different legal medical institution nodes to check the historical medical data in the health chain, so that the doctor can diagnose the state of an illness more accurately. Meanwhile, in the process of managing and sharing the medical data by the medical institution, the medical data are stored in the local server, and the index of the medical data is uploaded to the health chain system; the index of the medical data comprises keywords, a server storage address and user signature information.
In the local storage process of the medical data, after the generated medical data is encrypted by the system, the corresponding data cipher text is stored in the local server of the medical institution, and the URL information of the storage position is generated.
After obtaining the data access authorization, the medical data consumer can obtain the real data through the URL information, and finally view and use the original data through decrypting the ciphertext.
In the medical data uplink registration process, a medical data index is generated according to the generated information such as the medical data local storage location information URL, the keywords, the patient signature and the like. And the medical data index is uplink registered to the health chain account book in a searchable encryption mode.
After a medical data consumer searches target data through medical data keywords, the medical data consumer can obtain the URL information of the storage position of the medical data through the trapdoor test capable of searching encryption, and then the ciphertext data information of the medical data is downloaded.
In the medical data cross-institution sharing process, after the generated medical data are shared in the health chain system, the medical data can be retrieved by all nodes in the health chain system, and patients can check their medical data records by different doctors required by different medical institution authorization. And other health chain nodes can access the storage address of the medical data only through the searchable and encrypted trapdoor test, can decrypt the ciphertext data only after obtaining the medical data viewing authority, and view and use original medical data.
The doctor participates in the construction of medical data and can view the medical data on the health chain system. The medical institution is responsible for collecting and managing the medical data shared by the patients and storing the shared medical data into the health chain system. The bank, participating in the cost support required during the generation of the medical data, participates in the verification of the medical data in the health chain system. The insurance agency is involved in the expense reimbursement support required during the generation of the medical data and in the verification of the medical data in the health chain system.
Establishing a game model between medical data pricing and transaction amount in a health chain system, setting initial pricing by a medical institution according to medical data characteristics, and bidding by medical data consumers according to own requirements;
both the medical data resource provider and the consumer want to maximize their interests, i.e., the medical data resource provider wants to sell more data at a higher price and the consumer wants to obtain more data at a lower price. Therefore, the problem becomes a problem of optimizing the game. The medical data resource provider preferentially sets a bidding rule and calculates the self maximum benefit; the medical data resource consumer adjusts the self demand according to the bidding rule of the provider to bid and calculates the self maximum income; through the mutual game between the price and the demand between the two parties, the optimal data price and the optimal transaction amount are finally achieved, the two parties respectively achieve respective maximized benefits, and meanwhile, the system also achieves the maximized benefits. At this time, the sharing of the medical data resource is realized under the incentive of interest. The gaming model between pricing of medical data and transaction amount comprises:
setting initial price and interval of medical data resources according to the holding amount, demand amount and rarity degree factors of medical data and constructing a benefit function of the medical data resource provider; the medical data resource provider is a medical institution, the medical institution shares the collected medical data to the health chain system, and the medical data is integrated and dispersed, so that the maximum value of medical data resources is exerted.
The maximum benefit of the medical data resource provider calculates the profit of the medical data resource sold, and removes the expenses such as compensation and management consumption paid to the original patient of the medical data resource.
The bidding strategy of the medical data resource consumer adjusts the demand of the consumer according to the bidding rule of the medical data resource provider and constructs the benefit function of the medical data resource consumer. The medical data resource consumer is a researcher who utilizes medical data to conduct scientific research, drug research and development, and medical device manufacturing.
Maximizing revenue for a consumer of medical data resources, calculating the cost of the medical data resources purchased, and adding the additional required operational and maintenance costs.
The maximum benefit of the health chain system refers to the sum of the maximum benefit of the medical data resource provider and the maximum benefit of the medical data resource consumer.
Calculating Nash equilibrium points of the game model by using a reverse derivation method to obtain an optimal data price and a data transaction amount; calculating a resource demand by first calculating convergence and an extreme point of a revenue function of the medical data resource consumer according to an initial price set by the medical data resource provider; substituting the obtained value into a benefit function of the medical data resource provider to calculate a benefit value; and adjusting the price of the medical data resource, and iterating the calculation processes of the two steps until the latest revenue function is no longer greater than the last revenue value, namely achieving Nash balance of the game model. At this time, the price and the demand of the medical data resource at the last time are the optimal price of the data resource and the optimal transaction amount of the data resource, and the profit value of the medical data resource consumer and the benefit value of the provider at the last time are the optimal profit value and benefit value of the data resource. The specific operation is as follows:
the convergence and the extreme points of the profit function of the medical data resource consumers are that the first-order and second-order derivatives of the profit function of the medical data resource consumers are calculated, the convergence of the profit function of the medical data resource consumers is judged, and the optimal medical data resource demand is calculated;
calculating the benefit value of the medical data resource provider, namely substituting the obtained optimal medical data resource demand into a benefit function of the medical data resource provider, calculating the first-order and second-order derivatives of the benefit function of the medical data resource provider, judging the convergence of the benefit function of the medical data resource provider, and calculating to obtain the optimal medical data resource price;
and Nash equilibrium of the game model is the optimal data price and the optimal transaction amount. Namely, the medical data resource provider achieves the maximum benefit, the medical data resource consumer achieves the maximum benefit, and the health chain system achieves the maximum benefit.
Judging whether the sum of the benefit of the medical data resource provider and the benefit of the medical data resource consumer reaches the maximum;
and when the maximization is reached, obtaining Nash equilibrium points of the game model, namely the optimal data price and the optimal transaction amount.
On the basis of the distributed medical service health chain described in fig. 2, fig. 3 shows a block chain medical data sharing excitation method of game theory, which includes the steps of:
s301: first, a medical facility is selected as the "leader". Setting one of said medical data price policies { λ ═ λi]i∈N:λmin≤λi≤λmaxIn which λ isiIs the price, lambda, of the ith said medical data consumermaxAnd λminThe highest and lowest prices, respectively. Here the lowest price lambdaminIs the lowest revenue guarantee for the healthcare data resource provider to record. Thus, in addition to removing the extra operating and maintenance costs γ, the expected benefits of the medical institution are:
RL＝λidi-γdi (1)
wherein d isiIs the ith said medical data consumer's demand.
S302: and the medical data resource consumers adjust the medical data resource demand amount to bid according to the bidding strategy of the providers.
A "follower" is generally a user of data, such as a researcher, medical company, or other institution that needs to use medical data for research. According to the bidding rule of the leader, the follower decides the data purchasing amount of the follower. Assuming that there are N data consumers to bid together for a data, when the additional required operating and maintenance costs (preset factor c) are addedi) This can then be expressed as:
Ssat＝αiln(di-dmin+ci) (2)
wherein d isminIs the lowest demand of the ith data consumer, αiIs a preset non-zero positive factor.
Since the payment cost of the ith data consumer for each piece of data is lambdaidi. Thus, the revenue function for a data consumer may be expressed as:
RF＝Ssat-λidi (3)
s303: calculating first and second derivatives of the medical data resource consumer revenue function, judging the convergence of the revenue function, and calculating to obtain the optimal medical data resource demand;
and calculating the optimal data resource demand of the ith data consumer. By deriving equation (3), the benefit function R can be obtainedFFor resource demand d*The first and second derivatives of (a) are as follows:
therefore, the benefit function R is obtained by the formula (5)FAre strictly convergent. At the same time, calculate
The optimal data resource demand can be obtained:
s304: substituting the obtained optimal medical data resource demand into a benefit function of the medical data resource provider, calculating first and second derivatives of the benefit function, judging the convergence of the benefit function, and calculating to obtain an optimal medical data resource price; an optimal metadata price for the data resource is calculated.
Substituting the optimal data resource demand result in the step (6) into an equation (1), and obtaining a revenue function R of the data resource providerLCan be converted into:
then, meterCalculating a profit function RLFor metadata price lambda*The first and second derivatives of (a) are:
when d ismin＜ciIs provided with
And
at the same time, it can be derived:
as shown in the formula (10), the revenue function RLThe price of the metadata increases and then decreases along with the transformation of the price of the metadata. The revenue function is strictly convergent, i.e. at the time
The data resource reaches the optimal metadata price as follows:
in addition, due to λiRepresents the price of the ith data consumer, and therefore d is not consideredmin＞ci，λiCase < 0.
S305: the medical data resource provider maximizes benefits, the medical data resource consumer maximizes benefits, and the health chain system maximizes benefits.
Suppose there are te {1, 2.. eta., T } medical nodes in the health chain network that are collectors of electronic medical record data and traders. The node serves as a maintainer of the system, benefits are created through medical big data resources, the return of an original data generator is paid, the system is strived to achieve overall balance, and the maximum benefit is obtained. At this point, the maximized system benefit of the health chain system can be represented as the following optimization problem C:
determining the transaction and validating, broadcasting and uploading the shared transaction record to the health chain system, fig. 4 shows the process of shared transaction uplink registration based on the distributed health chain of medical services described in fig. 2, including the steps of:
the medical data sharing transaction verification, the legality of the medical data needs to be verified in the uplink registration process of the medical data, a legal transaction is formed and stored on a health chain account through the verification of a health chain verification node for the generated medical data index, but the index transaction is different from the common sharing transaction, and the index transaction forms a data list independently and can be retrieved by a data consumer. The transaction of the sharing behavior needs to be verified, after the sharing is completed, the sharing behavior forms a new transaction, and a legal transaction is formed and stored on a health chain account book after the verification of the health chain verification node.
The medical data sharing transaction broadcasting, the index uploading transaction of the medical data and the sharing behavior transaction are broadcasted to the health chain whole network node by a leader node in the verification nodes after passing the verification of all the verification nodes of the health chain; the agreed upon transaction record is broadcast to all consensus nodes on the health chain.
And sharing the medical data on the transaction uplink, wherein through the transaction after broadcasting, when the temporary block is verified to achieve consensus through all consensus nodes on the health chain, the temporary block is linked to the tail end of the longest chain of the account book which is the only block of the health chain in the whole network, the transaction also completes uplink registration, and the transaction becomes a record which cannot be tampered.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (9)
1. A block chain medical data sharing excitation method based on game theory is characterized by comprising the following steps: establishing a health chain system of the medical alliance, which comprises patients, doctors, medical institutions, banks and insurance institutions, by using the alliance chain technology; the patient chooses to share his own medical data, and the medical institution collects, manages and shares the medical data in the health chain system; establishing a game model between medical data pricing and transaction amount in a health chain system, setting initial pricing by a medical institution according to medical data characteristics, and bidding by medical data consumers according to own requirements; calculating Nash equilibrium points of the game model by using a reverse derivation method to obtain an optimal data price and a data transaction amount; the transaction is determined and the shared transaction record is verified, broadcast and linked up into the health chain system.
2. The game theory-based blockchain medical data sharing excitation method according to claim 1, wherein the health chain system is a distributed health chain system formed by different medical institutions by using alliance chain technology; the health chain system comprises a consensus node, a system node and other nodes; the consensus nodes refer to different medical institutions and participate in the management and maintenance of the health chain system; the system node refers to a patient and a doctor, and uploads, manages and deals with own medical data; other nodes are referred to as banks and insurance agencies.
3. A game theory-based blockchain medical data sharing excitation method according to claim 1 or 2, wherein the patient visits a medical institution to establish a medical data archive; the medical data comprises information of the patient, treatment information, information of an inquiry doctor, diagnosis result information, medical institution information and insurance information;
ownership of the medical data belongs to the patient, the patient can selectively share the medical data of the patient, and sensitive information data are hidden in the sharing process; meanwhile, in the process of managing and sharing the medical data by the medical institution, the medical data are stored in the local server, and the index of the medical data is uploaded to the health chain system;
the doctor participates in the construction of medical data and can view the medical data on the health chain system;
the medical institution is responsible for collecting and managing the medical data shared by the patients and storing the shared medical data into the health chain system;
the bank participates in the cost support required during the generation of the medical data and in the verification of the medical data in the health chain system;
the insurance agency is involved in the expense reimbursement support required during the generation of the medical data and in the verification of the medical data in the health chain system.
4. The game theory-based blockchain medical data sharing incentive method according to claim 3, wherein the index of the medical data comprises keywords, server memory addresses and user signature information.
5. A game theory-based blockchain medical data sharing incentive method according to claim 1,2 or 4, wherein the game model between the pricing of the medical data and the transaction amount comprises:
setting initial price and interval of medical data resources according to the holding amount, demand amount and rarity degree factors of medical data and constructing a benefit function of the medical data resource provider;
the bidding strategy of the medical data resource consumer adjusts the demand of the consumer according to the bidding rule of the medical data resource provider and constructs the benefit function of the medical data resource consumer.
6. The game theory-based blockchain medical data sharing incentive method according to claim 5, wherein the medical data resource providers are medical institutions, the medical institutions share the collected medical data in the health chain system, and the medical data are integrated and dispersed to exert the maximum value of the medical data resources; the medical data resource consumer is a researcher who utilizes medical data to conduct scientific research, drug research and development, and medical device manufacturing.
7. The game theory-based block chain medical data sharing excitation method according to claim 5, wherein the method for calculating the nash equilibrium points of the game model by using the reverse derivation method comprises the following steps:
calculating first and second derivatives of the benefit function of the medical data resource consumers, judging the convergence of the benefit function of the medical data resource consumers, and calculating to obtain the optimal medical data resource demand;
substituting the obtained optimal medical data resource demand into a benefit function of a medical data resource provider, calculating first and second derivatives of the benefit function of the medical data resource provider, judging the convergence of the benefit function of the medical data resource provider, and calculating to obtain an optimal medical data resource price;
judging whether the sum of the benefit of the medical data resource provider and the benefit of the medical data resource consumer reaches the maximum;
and when the maximization is reached, obtaining Nash equilibrium points of the game model, namely the optimal data price and the optimal transaction amount.
8. A game theory-based blockchain medical data sharing incentive method according to claim 1, 6 or 7, wherein the benefit function of the medical data resource provider is:
RL＝λidi-γdi；
wherein R isLIs a benefit function of the medical data resource provider, λiIs the price of the ith medical data consumer, diIs the ith medical treatment numberAccording to the demand of consumers, gamma is a coefficient of extra operation and maintenance cost, i belongs to N, and N is the number of medical data consumers;
the benefit function of the medical data resource consumer is as follows:
RF＝Ssat-λidi；
wherein R isFIs a benefit function of the medical data resource consumer, Ssat＝αiln(di-dmin+ci) A satisfaction function representing the ith medical data consumer, ciIs a predetermined factor, dminIs the lowest demand of the ith medical data consumer, alphaiIs a preset non-zero positive factor.
9. The game theory-based blockchain medical data sharing incentive method according to claim 1, wherein the method of validating, broadcasting and uploading the shared transaction records into the health chain system comprises:
the medical data sharing transaction is verified, after the sharing is completed, a new transaction is formed by the sharing action, and a legal transaction is formed and stored on a health chain account book after the verification of the health chain verification node;
the medical data sharing transaction broadcasting, the index uploading transaction of the medical data and the sharing behavior transaction are broadcasted to the health chain whole network node by a leader node in the verification nodes after passing the verification of all the verification nodes of the health chain;
and sharing the uplink of the transaction by the medical data, wherein the transaction after broadcasting is linked to the tail end of the longest chain of the health chain whole-network unique account book along with the temporary block, the transaction also completes uplink registration, and the transaction becomes a record which can not be tampered.
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