Keywords

1 Introduction

Building a decentralized patient information management system to be able to share them among the different medical centers is an urgent requirement today, not only in developed countries but also in other developing countries [8]. While developed countries have a specific set of laws and policies regarding the sharing and use of personal/medical data of patients other than diagnostic and therapeutic purposes (eg, GDPR for European countriesFootnote 1, Privacy Act for AustraliaFootnote 2), developing countries have not focused on synchronizing patient medical records [10]. In developing countries, personal data (i.e., including medical data) is not given due attention. Specifically, all information related to medical history and test results is stored locally at medical treatment facilities [6]. In addition, patients are not well aware of the process for handling and sharing their personal information - affecting patient privacy [5].

For medical data processing in developing countries (eg, Vietnam, India), most systems store information in the form of centralized storage. We also surveyed several hospitals in the Mekong Delta provinces (i.e., Ben Tre, Vinh Long) to observe how information about medical test results is stored. We found that the frontline hospitals in large cities store information (called electronic data) only focusing on the treatment route (i.e., patients undergoing internal medicine). inpatient) - for outpatient (i.e., home) tests or treatment results are recorded in paper form (called paper data - ie, the procedure is described in Sect. 3).

Nevertheless, centralized storage carries with it many risks [18], for example easily being lost due to patient error or due to natural causes (eg, flood, fire). The loss of medical test results directly affects the diagnosis and treatment process. Hence, a solution is needed to store all this diagnostic information on electronic data. To solve this problem just focusing on infrastructure is not enough. Indeed, Sharma et al. [19] argue that centralized storage limits scalability and limits patient choice. We also note an example in Vietnam related to hospital transfer. Severe cases that cannot be treated at provincial hospitals (eg, Vinh Long, Ben Tre) are transferred to the larger hospitals in Ho Chi Minh City. Information related to testing results will be transferred based on paper documents (instead of directly retrieving from upper-level hospitals).

To solve the above problems, several approaches have combined Blockchain technology and smart contracts to store and process medical data, respectively. For example, Xiao et al. [30] has proposed a system called HGD (Health Care Data Gateway). Thanks to the transparency and decentralized storage of blockchain technology, patients can easily and securely store and share their data. Similarly, Kassab et al. [11] has provided analysis to demonstrate how the benefits of blockchain technology (i.e., synchronous processing, decentralized storage) can enhance data processing and storage capacity for healthcare systems. In addition to the above two preliminary studies, we also summarize some research directions on the same topic based on blockchain technology and smart contract in the related work section of the research paper.

One of the problems that the existing approaches have not solved (i.e., applied to developed countries) is the background of the users. In particular, it is not possible to require users (i.e., patients) to install a series of sharing policies for authorized users [22, 28]. In addition, several studies have evaluated the feasibility of storing all medical data on-chain [31]. Most of the above studies provide an off-chain storage solution of information that is not directly related to the patient’s treatment. This has two purposes: (a) restricts on-chain storage - reduces the cost of query execution (i.e., data access) [4]; (b) restricts privacy violations because data stored on-chain is only accessible to users of the same system [16]. However, the above approach still faces problems when sharing their medical records with medical centers (i.e., medical staff: doctors, nurses, laboratory staff).

Our research problem in this paper is to fill the limitations on sharing medical data (i.e., medical test results) that apply to Vietnam. We have actually surveyed the testing process and its results storage of 2 large hospitals in Ho Chi Minh City (i.e., the University of Medicine and Pharmacy Hospital and Cho Ray Hospital) 2 hospitals in Can Tho (i.e., central general hospital, the Children’s Hospital); 1 hospital in Ben Tre (i.e., Nguyen Dinh Chieu Hospital); and 1 hospital in Vinh Long Province (i.e., Vinh Long General Hospital) in November 2022. Our records range from the time the patient gets tested to the time the results are received and treatment at the hospital. Therefore, our work contributes on five aspects, namely (a) collecting procedures for handling and storing test results of patients at hospitals in Ho Chi Minh City and Mekong Delta (b) proposing a mechanism for sharing test results based on blockchain and smart contract technologies; (c) presenting an NFT tool-based generation model for storing medical test results; (d) providing the proof-of-concept of the proposed model; and (e) deploying our implement on 4 (ERC721 and ERC20)-supported platforms including BNB Smart Chain, Fantom, Polygon, and Celo to choose the most suitable platform for our proposed model.Footnote 3

2 Related Work

To the best of our knowledge, most of the articles focus on proposing a model to protect personal information and medical data based on two approaches (i) authorization (i.e., access control) and blockchain technology. In this section we categorize state-of-the-arts based on the above two themes. Thereby, analyze the shortcomings in the current work and propose our model.

2.1 The Approaches Based on Access Control Models

Most state-of-the-arts exploit access control models (RBAC, ABAC, ABE) to ensure access to patient medical data. In particular, data retrieval requests must be approved by the data owner (i.e., patient). For example, Makubalo et al. [14] has synthesized access control model-based approaches to empowering patients to share medical information. Specifically, policies will help patients manage who (eg, nurses, doctors) is allowed to access their medical data and use it for a specific purpose (eg, treatment). Another example applying attribute-based encryption (ABE) was introduced by Barua et al. [1] and Yin et al. [32] to encrypt all medical data before storing it in the cloud. Only objects that satisfy the required attribute have the key to decrypt them. In addition, based on the Role-based Access Control model Chen et al. [2] described a requester role-based access management model. Besides, some methods apply dynamic policy model to increase flexibility in medical environment [9, 21] or design two layers of policy, ie, i) security policy - protect data patient data from intrusion by users outside the system, and ii) privacy policy that protects patient information from agents in the system [28]. Combining dynamic policy-based approaches and the ABAC model, son et al. introduced a two-layer access control model based on medical environments [22].

2.2 The Approaches Based on Blockchain Technology

Chen et al. [3] proposed a model based on Blockchain technology applied to healthcare environment to store and control mining data from IoT devices. These devices store real-time medical data. All information stored on the chain is authenticated and controlled by the user. Madin et al. [13] has proposed a model of storing medical record information on blockchain and storing details of that information on IPFS. The purpose of this group of authors is to protect the privacy of patient data (i.e., limit access from users of the same system). MedAccess introduced the patient Health Record management system [15]. The proposed system focuses on protecting patient information from being altered (i.e., transparency) and privacy (offchain storage). Similar to the approach of [15], to minimize the amount of information stored on the chain, Zyskind et al. [33] presents an onchain and offchain patient data and information storage model.

For actual deployed solutions, HealthBankFootnote 4 combined blockchain and IPFS to propose a patient-centric model for sharing medical data. Several solutions are introduced to comply with privacy constraints (eg, GDPR). For example, HealthNautica and Factom Announce PartnershipFootnote 5 presented a decentralized data storage solution. and protect personal information based on Blockchain technology. Another approach based on data streaming is also proposed by IRYOFootnote 6 based on NuCypher KMS (ie [7]).

All of the above evaluation directions face two major challenges for both the access control model-based approach and the Blockchain and IPFS-based approach. Specifically, with the first approach of empowering users based on access policies, the approaches are limited when users have to create a series of policies to control access accordingly. These policies are prone to conflicts or redundancies if the number of access objects is large and there are many properties [28]. Moreover, getting used to a completely new system (i.e., defining security policies) also makes users encounter some obstacles due to lack of necessary background (especially for casual users) in developing countries. As for the second approach (blockchain and IPFS-based), it is agreed that this method brings a lot of efficiency in the process of storing and processing medical data, but on-chain data storage solutions and out-of-string also brings a lot of complications for the average user when they want to share. To limit the above risks, within the framework of the problem of sharing medical test results at medical centers in Vietnam, we combine a series of modern platforms including blockchain, smart contracts, and NFT. Specifically, instead of sharing policies to define groups of people who can retrieve test results or patient history, we create corresponding NFTs. This approach restricts the strict requirements of the technology platform such as security policy-based methods. The next section presents our proposed model based on NFT technology to share information with the respective objects.

3 The Blockchain-Based Medical Test Results Management System

In this section, we summarize the traditional test results management process applied in Vietnam (i.e., in provinces and cities in the Mekong Delta) as well as propose a model based on blockchain technology. and smart contracts to solve the limitations of the traditional model as well as NFT technology to generate electrical test results for easy sharing in the medical environment.

3.1 Traditional Medical Test Results Management Model

Fig. 1.
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Traditional medical test results management model

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Figure 1 shows the traditional process of testing and getting results based on four steps (i.e., depending on the hospital in the city or the country, the process is different). At provincial/major city hospitals, the waiting time to get tested and receive test results is very long. In particular, according to our perception at the University of Medicine and Pharmacy Hospital in Ho Chi Minh City. In Ho Chi Minh City, some patients have to be present from the hospital from 1:00 AM to queue to receive the order number even though the opening time there is 8:00 AM. Therefore, the procedure shown in Fig. 1 shows only the general steps and omits the detailed steps depending on the hospital. Specifically, the patient creates an archive of health information called medical record book at the medical center.Footnote 7 The patients undergo the necessary medical examinations before proceeding with the treatment. This information is extremely important - the doctor’s diagnoses and judgments are based on the changes in the patient’s health status through the test results. After receiving the results from the laboratory staff, the patient brings the results to the doctors and nurses to make judgments about their health status and corresponding treatments. All information about the diagnosis and treatment results are updated in the medical record book. Therefore, the loss of the patient’s medical record book seriously affects the treatment process. Therefore, there is a need for a comprehensive solution to the problems related to the storage and sharing of patients’ medical record books for both electronic and paper formats. The following section presents our solution based on current popular technologies: blockchain, smart contract and NFT applied to the Vietnamese environment.

3.2 Medical Test Results Management Model Based on Blockchain Technology, Smart Contract and NFT

Fig. 2.
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Medical test results management model based on blockchain technology, smart contract and NFT

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Figure 2 shows nine steps to build a medical test result management system based on blockchain technology, smart contract and NFT. Specifically, the patient must create a global patience_ID that is shared by the entire medical system in Vietnam (step 1). According to our observations, the role of patience_ID global is not considered in the current system at the medical facility in Vietnam. Specifically, each patient can only receive one identification code (i.e., valid for the day) at each different hospital. The storage of patient information in medical facilities is not supported. Step 2 Synchronize patience_ID global with the medical record book to store all information about the medical record and test results as well as the patient’s medical history. This information is displayed on the user interface based on our provided services (UI services) in step 3. Other users can access patient information to get a list of test requests. of the patient (step 4); update test results (step 5); or get feedback on your doctor/nurse’s medical condition, diagnosis, and treatment steps (step 6). All these steps are performed and managed based on pre-designed methods in smart contracts (step 7) and updated to the distributed ledger (step 8). The content of the NFTs is created in step 9 (i.e., the content of the NFTs - medical test results are presented in the Introduction) and shared with doctors and nurses for the purpose of patient care and treatment.

4 Evaluation Scenarios

4.1 EVM-Supported Platforms

Fig. 3.
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The transaction info (e.g., BNB Smart Chain)

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Because the model for generating medical test results makes it easy for patients to manage test results (i.e., can be extended to medical records) as well as easily share them with other objects that users want. We want instead of defining security policies (eg, access control), we implement the proposed model on EVM-enabled blockchain platforms instead of exploiting Hyperledger eco-system platforms because they are easy to open. wide (i.e., using existing platforms and systems). In addition, assessments based on system responsiveness (i.e., number of requests responded successfully/failed, system latency - min, max, average) have been evaluated by us in the previous research paper. Therefore, in this paper we determine the suitable platform for our proposed model. Specifically, we install a recommendation system on four popular blockchain platforms today, supporting Ethereum Virtual Machine (EVM), including Binance Smart Chain (BNB Smart Chain)Footnote 8; PolygonFootnote 9; FantomFootnote 10; and CeloFootnote 11. Our implementations on these four platforms are also shared as a contribution to the article to collect transaction fees corresponding to the four platforms’ supporting coinsFootnote 12, ie, BNBFootnote 13; MATICFootnote 14; FTMFootnote 15; and CELOFootnote 16. For example, Fig. 3 details our three assessments of a successful installation on BNB Smart Chain (i.e., similar settings are shown for the other three platforms). Our implementations to evaluate the execution cost of smart contracts (i.e., designed based on Solidity language) run on testnet environments of four platforms in order to choose the most cost-effective platform to deploy. Our detailed assessments focus on the cost of performing contract creation, NFT generation, and NFT retrieval/transfer presented in the respective subsections related to i) Transaction Fee; ii) Gas limit; and iii) Gas used by transaction.

4.2 Transaction Fee

Table 1. Transaction fee
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Table 1 shows the cost of creating contracts for the four platforms. It is easy to see that the highest transaction fee of the three requirements is contract creation for all four platforms. In which, the cost of BNB Smart Chain is the highest with the highest cost when creating a contract is 0.0273134 BNB ($8.43); whereas, the lowest cost recorded by the Fantom platform with the highest cost for contract initiation is less than 0.00957754 FTM ($0.001849). Meanwhile, the cost to enforce Celo’s contract initiation requirement is lower than Polygon’s with only $0.004 compared to $0.01. For the remaining two requirements (Create NFT and Transfer NFT), we note that the cost of implementing them for all three platforms, Polygon, Celo, and Fantom is very low (i.e., negligible) given the cost. trades close to $0.00. However, this cost is still very high when deployed on BNB Smart Chain with 0.00109162 BNB ($0.34) and 0.00057003 BNB ($0.18) for Create NFT and Transfer NFT, respectively.

4.3 Gas Limit

Table 2. Gas limit
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Table 2 shows the gas limit for each transaction. Our observations show that the gas limits of the three platforms (i.e., BNB, Polygon, and Fantom) are roughly equivalent - where Polygon and Fantom are similar in all three transactions. The remaining platform (i.e., Celo) has the highest gas limit with 3,548,922; 142,040; and 85,673 for all three transaction types.

4.4 Gas Used by Transaction

Table 3. Gas Used by Transaction
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Table 3 shows the amount of gas used when executing the transaction (i.e., what percentage of gas in total gas is shown in Table 2). Specifically, three platforms BNB, Polygon, and Fantom use 100% of Gas Limit for two transactions Contract Creation and Create NFT. Meanwhile, Celo uses 76.92% of the Gas limit for the above two transactions. For the last transaction of Transfer NFT, the highest Gas level was recorded by Fantom and Polygon with 93.41% of Gas limit; while BNB and Celo use 79.17% and 69.8% of Gas limit.

5 Discussion

According to our observation, the transaction value depends on the market capitalization of the respective coin. The total market capitalization of the 4 platforms used in our review (i.e., BNB (Binance Smart Chain); MATIC (Polygon); FTM (Fantom); and CELO (Celo)) are $50,959,673,206 respectively. $7,652,386, 190; $486,510,485; and $244,775,762.Footnote 17 This directly affects the coin value of that platform – although the number of coins issued at the time of system implementation also plays a huge role. The total issuance of the four coins BNB, MATIC, FTM, and CELO is 163,276,974/163,276,974 coins; 8,868,740,690/10,000,000,000 coins; 2,541,152,731/3,175,000,000 coins and 473, 376,178/1,000,000,000 coins. The coin’s value is conventionally based on the number of coins issued and the total market capitalization with a value of $314.98; $0.863099; $0.1909; and $0.528049 for BNB, MATIC, FTM, and CELO respectively.

Based on the measurements and analysis in 4 section, we have concluded that the proposed model deployed on Faltom brings many benefits related to system operating costs. In particular, generating and receiving NFTs has an almost zero (i.e., negligible) fee. Also, the cost of creating contracts with transaction execution value is very low (i.e., less than $0.002). In future work, we plan to implement complex methods/algorithms (i.e., encryption and decryption) and more complex data structures to observe the costs for the respective transactions. Deploying the proposed model in a real environment is also a possible approach (i.e., implementing the recommendation system on the FTM mainnet). In our current analysis, we have not considered issues related to the privacy policy of users [23] (i.e., access control [21, 22], dynamic policy [20, 29]) - a possible approach would be implemented in upcoming work. Finally, infrastructure-based approaches (i.e., gRPC [12, 25]; Microservices [17, 26]; Dynamic transmission messages [27] and Brokerless [24]) can be integrated into the model of us to increase user interaction (i.e., API-call-based approach).

6 Conclusion

Our article aims at a solution to share test result data in the medical environment based on the benefits of current technologies such as blockchain, smart contracts, and NFT. Our solution aims to replace the paper documents used in hospitals in the South of Vietnam, including hospitals in Ho Chi Minh City. Ho Chi Minh and the Mekong Delta. Specifically, these results are stored off-chain and generate corresponding NFTs upon request from treatment facilities. To reduce patient effort, we replace policy-based approaches with data-sharing solutions for disease care and treatment. Our solution is implemented on the Ethereum platform and Solidity language (i.e., smart contract development). In order to optimize the execution cost of basic transactions (i.e., contract creation, NFT creation, NFT transfer), we deploy proof-of-concept on four EVM-enabled platforms, including BNB, MATIC, FTM, and CELO. According to our observations (i.e., executed at the time of system evaluation), smart contracts deployed on Fantom bring more economic value (i.e., cost savings in execution) than the other three platforms. The future directions of the current work are presented in the Discussion section.