Blockchain applications in decentralizing healthcare data distribution
Why control of healthcare data matters
Table of Contents
- Introduction to Blockchain and NFTs
1. Problem Statement - Traditional Models in Healthcare
1. An example of healthcare data usage
2. Non-Blockchain based Systems
3. National Healthcare Systems
4. The Business Perspective - Blockchain Models
1. Projects utilizing NFTs
2. Supply chain management projects in healthcare - Design of Theoretical Project
1. Improvements to healthcare NFTs
2. Cashflow - Discussion
1. Centralized Control
2. Identity Integration
3. Security Concerns - Conclusion & Future Work
- References
1. Introduction to Blockchain and NFTs
Blockchain can be defined as having the unique properties of immutability, transparency and anonymity [7]. Blockchain is used for a wide variety of projects such as cryptocurrencies, Internet of Things as well as tokenizing art and intellectual property ownership [9].
The main components of a Blockchain includes a peer-to-peer network, which is a set of nodes that can read and write transactions on the blockchain; and a consensus protocol, which is a set of rules that determine how new transactions are added to the Blockchain. The security of the Blockchain is also paramount to its success and therefore the features of it being tamper proof are very important so that it is very easy to verify whether transactions have been manipulated after their recording or not. It should also be able to ward off any attempts to tamper with it adequately [7]. Blockchains can be either public or private [9]. In this case “Public” means that the record of transactions as well as the consensus protocol are open to anyone. To counter the lack of control on users public Blockchains must have conditions that prevents the participants form any malicious activity. As an example, in proof of work (PoW) based Blockchains (such as Bitcoin and Ethereum) this is achieved by requiring the users to use their computational power to solve a cryptographic puzzle to be allowed to append the new block (i.e., new set of transactions) to the Blockchain. Both Bitcoin and Ethereum, which are the most well known Blockchains today, use proof of work but this results in a low transaction speed and consumes lots of energy. Another consensus method that is commonly used by Blockchains today is called proof of stake (PoS). It is an alternative that does not use as much energy and instead uses economic rationality. A random process selects an entity to append the next block to the Blockchain from among the entities that stake the crypto currency [7]. Private Blockchains use classic authentication mechanisms and are used by corporations and banks. However, such implementations come at the cost of violating the for the most part, Blockchain trustlessness and decentralization compared to public Blockchains. Private Blockchains therefore result in greater speed of transactions as their consensus protocol does not have to be based on hard mathematical cryptography [7].
The non-fungible token (NFT) has been used for a variety of use cases as of 2021. NFTs represent ownership rights to a unique digital or real-world asset and are issued on the Blockchain. They can be used to make it more difficult for digital creations to be copied and shared by proving ownership through the Blockchain transactions. They have also been used to issue a limited number of digital assets which has primarily included artworks that have retained skyrocketed in value through scarcity [9].
There are both fungible as well as NFT creation standards that have been implemented. Fungible tokens are not unique and thus divisible and an example is money. NFTs are unique and technically not divisible and an example of such is an original art painting that retains its value despite duplications. Hundreds of thousands if not millions of dollars have been used to purchase NFTs. By may 2021 about 34 million United States dollars had been spent on NFT sales [9]. However by the end of 2021 about 25 billion United States dollars had been spent on NFT sales. That is an incredible amount of growth and but there are signs that it is slowing down to a certain extent. The technologies of the NFTs are still immature however the ecosystem and use cases have been growing at a great speed. The NFT was initially created from the ERC721 token standard of Ethereum which designates each token as unique and distinct [9]. This makes the token ideal secure digital property rights and for users to trade those digital properties. This could perhaps also extend to the trading of electronic health records by the owners of the records. There are legal pitfalls regarding the use of NFTs when it comes to the limitations of the governments enforcing an individuals ownership of their digital property [9]. This is because the governments do not currently use Blockchain as evidence of proof of ownership.
A Blockchain solution instead of a traditional database is not always the right choice for the storage and validation of data because is an energy inefficient way to store data [3]. When data must be kept confidential and all the participants are registered and authenticated users then a Blockchain is not needed [7]. Blockchain solutions are best used when a decentralized solution is required to mediate between trustless entities.
There are many different ways with which Blockchain based startups decide to raise funds for development. Initial coin offerings (ICOs) have declined and been replaced by Initial exchange offerings (IEOs) which are more scrutinized forms of fund raising where an exchange oversees the process of selling the tokens and projects have to submit white papers that are held to a certain standard. Initial decentralized-exchange offerings (IDOs) are a cheaper and less stringent alternative to IEOs which utilize decentralized exchanges that do not demand sums of payments and exclusive availability of the token on only that exchange.
1.1 Problem Statement
The amount of publicly available healthcare data has been exponentially increasing over the past few years and this has opened the possibility of bioinformatics and commercial research on a scale that was unprecedented. Blockchain technology has likewise advanced a lot in applications as well attracted enormous amounts of financial attention. The mechanisms of distributed ledger technology, tokenization and decentralized finance have also provided the opportunity for patients to take back control of their medical data as well as monetize the access to it. Blockchain has the potential to revolutionize healthcare data management.
In this project we will analyse entrepreneurial endeavors that are taking place at the intersection of healthcare data and Blockchain technology and how these projects are utilizing technologies such as nonfungible tokens and the mechanisms of decentralized finance to track and/or monetize data. The feasibilities of the projects and the challenges faced by them will be dissected and improvements will be suggested. Future opportunities will also be theorized and explored.
To summarize, the main research questions in this study are going to be:
To what extent can a Blockchain system contribute to decentralizing medical data sharing?
Can genomic data be further monetized through Blockchain financial aspects?
To this end, in section 2, we investigate the state of healthcare data exchange the way it works in the developed world using traditional databases and without Blockchain technology. In section 3 we describe the different types of cutting edge Blockchain solutions that are operating at the intersection of healthcare data sharing and its monetisation through both supply chain management as well as NFTs and their marketplaces. In section 4 we propose an improved system that builds upon as well as improves upon the projects named in section 3. In section 5 there is a discussion of the different concerns in regards to the flaws and possible solutions as well as future improvements that can take place.
2. Traditional Models in Healthcare
2.1 An example of healthcare data usage
In order to give examples about the usage of healthcare data it is important to describe that healthcare data is typically generated through clinics and hospitals when patients visit and describe their symptoms and socio economic conditions as well as get physically tested for their internal and external conditions. The data gathered from this is stored in electronic health record systems in the patient journals and may include doctors visit transcripts, blood test results, vaccination results, drugs and medicine prescribed and so on. In some healthcare systems the genome of the patients could be stored in the patient journals as well is it essential to the treatment of the patient in the case that the patient has a genetically inherited disease.
This data can be anonymized by replacing or censoring certain parts of the data such as the name and address, which makes it more difficult to track or identify the patient. Once the data is anonymized it can be transferred to certain parties or companies that have an agreement with the clinic or hospital. The transfer of data could require GDPR (General Data Protection Regulation) compliance depending on the country where the data transfer is taken place and whether the data still counts as having belonged to the patient even when it is anonymized, and therefore consent might be required from the corresponding patients. If the health care provider intends to distribute the data and that it is planned from the beginning (before the treatment) then it could be possible that all patients are to sign a declaration which states that they agree with any future anonymized healthcare data transfers if they are to undergo treatment. Obtaining consent before treatment could have psychologically higher probabilities of success due to the healthcare provider being able to withhold treatments. When healthcare providers redistribute data they can then be paid for the data by the stakeholders who buy it. The data can then be used by the stakeholders for research regarding drug discovery when it comes to genomic data, hospital efficiency and disease tracking with it comes to the healthcare data among other uses. It could even be used by insurance companies to determine which types of patients are admitted to hospitals and claim their insurances more which might lead to the companies charging a premium for their services regarding those patients. Insights obtained from healthcare data has all types of uses in decision making which can range from insurance policy determination and loan repayment probabilities, to determining which public safety measures are to be taken in regards to people vulnerable to certain pandemics.
2.2 Non-Blockchain based Systems
The diagnoses and practical clinical decision making within healthcare require high standards for data sharing. It can summarized with the initials of SSS (secure, safe as well as scalable) [6]. The way that data is shared is essential to make sure that the data that concerns the patient is quickly transferred to where it is needed which could be where the patient is currently about to undergo treatment. The healthcare workers as well as the physicians have to be capable to send the clinical patient data in a private and efficient way, so that patients are always receiving treatment based on their updated health conditions. Tele-medicine and e-health are domains within healthcare where the data is sent to corresponding and relevant specialists for an expert opinion that wouldn’t be able to be received at the current physician of the patient. In these domains which are online clinical conditions, a patient’s data can be sent via different methods such as store-and-forward technology, or online real-time clinical monitoring based technology which can incorporate tele-monitoring among other things. Patients can be remotely diagnosed and at the same time be treated by experts. Sensitivity, security as well as privacy are very important because the data is very sensitive. In addition to previously mentioned concerns, there are interoperability challenges. This is because when it comes to sharing data in practicality there needs to be a lot of cooperation between the stakeholders and involved parties. Data sharing agreements, patient matching and stratifying algorithms, ethical and governing rules are only some of the important concerns that all parties need to agree to before clinical data sharing can be as smooth as in order for e-health to work in practicality [6]. Implementing applications new and upcoming technology such as artificial intelligence/machine learning, IT and cognition as well as Internet of Things in a clinical setting to assist physicians are also being worked upon [6].
Electronic health record (EHR) systems are the key components of healthcare systems which consist of a large variety of different health related systems which can include prescribing systems, health information exchange systems, and clinical decision support systems [4]. In the future these systems could also deploy real time clinical AI models. An example of how EHR systems work is how a doctor notes down the symptoms of a patient that has visited into the EHR system and then also uses the system to prescribe medication to the patient that the patient would be able to buy at a local pharmacy. The records as well as the reason for the prescription would be present in the EHR system.
There is a distinction between clinical informatics and bioinformatics. Clinical informatics consists of the technology that supports healthcare services while bioinformatics is the development of methods that optimize and analyze biomedical data to improve healthcare [1].
Clinical informatics has been expanding as personalized precision medicine that targets individual patients for specific treatments becomes more commonplace. Training and expertise regarding electronic medical and health records is required to make the entire process more efficient and to make sure that resources and economics of scale can cause the technology to mature [1].
Bioinformatics has remained primarily research based but has been expanding exponentially due to the increasing biological data that’s been produced worldwide. The focus within bioinformatics used to focused on the gathering of data but now has shifted to curating and analysis of the data that is already available and growing exponentially with both biological experiments as well as electronic healthcare records [1]. The costs of genome analysis have gone down as well and it can cost less than 300 dollars in 2022 and this has resulted in production of large amounts of genomic data which can be used for researching genetic diseases as well as assist pharmaceutical companies in developing drugs that can target the genes of the board population to increase drug effectiveness. Bioinformatics as well as clinical informatics can be integrated into electronic healthcare records to improve precision medicine and allow insights from either field to inspire the other and shorten the time it takes to produce clinical applications of new laboratory based discoveries. [1].
2.3 National Healthcare Systems
There are many different electronic healthcare systems in use around the world and there is no uniform or widely accepted definition of electronic health records and what such records should contain [4]. There are many National EHR (NEHR) systems that have been deployed. NEHRs require the ability to be inter-operable with other EHR systems which have been developed by other healthcare providers [4]. Out of the European countries, the leading countries that had implemented a NEHR by 2017 are Denmark, Sweden, the Netherlands and Switzerland while the rest were facing challenges and still at the planning stages. The countries that were facing challenges at that point were Norway, Germany and Austria [4]. Outside of Europe Australia, New Zealand and Israel are considered one of the best in the world at NEHR implementation while Korea and Canada were rapidly implementing more EHR at their public hospitals [4].
Denmark uses IT at all sections of its healthcare system [2] and is one of the leading countries in the world regarding healthcare services. There are also unique electronic personal identifiers for every patient as well as health cards integrated with all the healthcare databases in the country. The municipalities and regions have health agreements so they can coordinate healthcare together [2] [4]. It can be claimed that healthcare is managed at the national level in Denmark and that it is quite centralized. Overall many countries have EHR systems but interoperability between them is low especially where healthcare providers have politically oriented relationships. Interoperability with insurance providers within these countries is also low. Many countries use citizen numbers as unique identifiers for patients and even then many countries do not have universal patient identifiers [4].
2.4 The Business Perspective
The healthcare industry is huge and comprises of around 8.3 trillion USD and big tech companies have also taken an interest in it as well as invested around 6.8 billion USD in the beginning of 2020. Big tech already has lots of data available due to the amount they can parse from their control over social media. Big tech including facebook, google, amazon and microsoft have access to advanced analytics which allows them to make sense of the data that they have. There are also unorthodox solutions such as virtual reality and oculus rift that are aiding in training of healthcare workers [8].
The prices of healthcare data per person have been estimated to cost around a thousand dollars. This could have huge implications if the each patients healthcare data is converted into an NFT through Blockchain technology and then licensed or sold to entities that want to utilize it as well as analyse it [8].
Many startups are moving into the healthcare industry and have been creating healthcare marketplaces. This is due to healthcare even when anonymized can fetch a hefty price. Pharmaceutical companies such as pfizer spend more than ten million dollars a year on acquisition of healthcare data from different sources. Healthcare data marketplaces such as Segmed have gotten millions of dollars in seed funding. Another company called Burstchain has been working with big data in more than 600 hospitals today however it is a Blockchain based solution so it will be elaborated upon in the corresponding chapter.
3. Blockchain Models
There are a few different ways that Blockchain technology can reduce costs in healthcare systems worldwide. One of the ways is by reducing bureaucratic red tape because a significant portion of the costs of healthcare are bloated due to inefficient insurance structures, bureaucracies as well as fiscal policies that are both based on debt and inflation [5]. By utilizing the functions of Blockchain in order to make medical records available to many healthcare providers and electronic healthcare systems, there could be a reduction in the prices of healthcare. This would take place by utilizing the decentralized plus the financial nature of Blockchain technology which is both trustless and deflationary. The costs of healthcare would become more associated with performance rather than misallocation [5].
EHRs could be stored on NFTs through encrypted IPFS which would result in immutable records which are are confirmed to be authentic due to being associated with the correct patients as well as being nonfungible and therefore unique to the patients which also solves the issue with many EHR systems not having universal patient identifiers.
Many private companies involved in personal genomics monetize their data and the patients as well as users are not able to benefit from this and therefore not compensated for it. The data sharing rules and permissions could then be set by the owners of the data. There is networks such as Oasis network working on developing features that allow users to selectively grant permission to third parties that are willing to pay to get access to the data. There could be some concerns about how the monetization of medical data could result in higher prices for the data thus making it difficult for researchers paying for the data with their limited funds. However the way monetization could still work is the same way that payments for research papers work through organizations such as universities having prepaid for all the research papers available through certain websites and journals. This would enable large pools of funds to pay for medical data.
3.1 Projects utilizing NFTs
Many Blockchain based healthcare platforms have been emerging that allow people to monetize their healthcare data. Among these marketplaces is EncrypGen which released a token called DNA that also aims at allowing individuals to make their genomics data available for research while profiting from it at the same time. Another Such company is Longenesis an AI healthcare based company as well as Open Health Network where consumers can monetize their healthcare data and also take advantage of AI and big data analytics enhanced products [8].
One of the NFT based solutions for healthcare monetization that have recently had an IEO (initial exchange offering) and implementing a healthcare platform that will function as an NFT marketplace is Aimedis. They have estalished the first medical and scientific NFT marketplace called DataXChange where prices per NFT can range up to several thousand dollars per NFT. Their NFTs also contain all types of data including pharmaceutical, research related as well socio economic data that pertains to patients. Their solution is based on the fact that interested parties will be able to sell as well as buy data directly from the platform and then use it. They have allowed for multiple owners of the same NFTs so that stakeholders will be able to use the data in tandem. The providers of the data would also be incentivized to continue to host and/or mint the NFTs through acquisition of fees from the sale and usage of the NFTs. The security of the NFTs is maintained through private access keys that are regenerated whenever the data is resold and that private key would allow only the current buyer to access the data. The NFTs are encrypted and stored on the private Blockchain of Aimedis. The token that Aimedis has implemented is also supposed to be earned through usage of NFTs and that token would be able to be staked which allow NFT prizes to be acquired.
3.2 Supply chain management projects in healthcare
There are also companies that deal with the management of the chain of control in regards to the data and its ownership. One such company is BurstIQ. Burstchain is another Blockchain based system built by the company BurstIQ which is operating with more than 600 hospitals in the united states today and provides rights management of the chain of custody of the healthcare data which also includes revocable consent as well as granular ownership of the data. The platform that they have created can enable data to be shared regardless of its size which could be from one datapoint to very large datasets in the petabytes and the data that is shared can have its permissions revoked in a conditional and trigger-based consentual way. Multidimensional blockchains could be created through these methods which can form interdependence between both system efficiency as well as health [8].
4. Design of Theoretical Project
A possible proposal for a project that would expand upon the aforementioned Blockchain platforms is the possible fractionalization and liquidation of NFTs. Currently NFTs are sold for fixed prices and they have to be sold as whole pieces which are in some cases thousands of dollars and they are therefore illiquid and the wealth is trapped within them and cannot be used for other purposes very easily. When medical NFTs containing healthcare and socioeconomic data in the future have a confirmed value and can function as assets it would be important to allow the wealth that is illiquid within the asset to be released. One of the methods by this could be done is through fractionalizing the different portions of the NFT and selling or renting the pieces individually to different stakeholders that would want them. Fractionalization in the case of Image NFTs would be dividing up portions of the JPEG or PNG file into pieces while in the case healthcare NFTs it would be dividing the lists of data into smaller lists of relevance (socioeconomic data, disease data, medical prescription data).
An example of the proposal would be renting the socio economic portion of the NFT to social media or insurance companies and renting the genomics and healthcare portion to bioinformatics research groups. The aggregated rent of the NFT fractions would give a much more accurate estimate of the true value of the NFT as compared to renting the whole NFT because it provides the portions of the NFT that are in demand by certain stakeholders to those stakeholders.
Once the value of the NFTs has been established, it could be possible to develop a Blockchain platform smartcontract that can allow data providers to take out a loan against their respective NFTs thus offering the ownership of the NFT as collateral to platform. As long as the NFT is owned by the platform, any rent and subscriptions and fees that are accumulated by the reselling and usage of the NFTs are instead acquired by the platform and not the individual who is the data provider. The data provider would be able to reacquire the rights to the NFT by paying off the loan and after that the subscriptions and fees accumulated by the platform would be again sent directly to the data providers.
4.1 Improvements to healthcare NFTs
In order to incentivize the buyers of the data to continue to treat NFTs as valuable and not just cease payment of subscriptions and also to prevent susceptibility to data leakage; it would be useful to implement constant updates to existing NFTs based on the constantly changing healthcare data and the status of the data providers or patients. As patients continually visit both doctors and patients their status changes and some acquire new diseases while others recover from their health issues thus the true value of the healthcare NFTs would be to have continuous access to an ever changing and ever improving data store. The quality of this data would be further improved upon by the slew of Internet of things applications that will be present in the world of the future that can measure the different physical parameters of the patients through external sensors that may be set up in various appliances such as smartphones. Companies and Research groups as well as other healthcare data stakeholders would want data that is updated semi regularly in order to make sure all their AI and big data models are up to date and it highly likely that they would pay a subscription for continuous access.
4.2 Cashflow
The cashflow of such a project would be best shown through a diagram that depicts how NFTs are being subscribed to resulting in flow of money to the wallet to which the NFT is assigned to. Once the NFT is offered as collateral in another system, then the money is rerouted to the platform and in exchange the data provider is given the sum of money that corresponds to a certain percentage of the value of the NFT according to its estimated price. The data provider is free to do what they wish with the loan. When they decide to regain access to the subscription payments being provided to the NFT owner, they can redeposit the loaned amount and then the subscription payments are again routed to the data provider. This provides a closed system of cashflow and as long as the NFT retains value it is possible for the data provider to regain access to the NFT subscription payments and the NFT ownership. However a method of “liquidation” can be implemented where the NFT cannot be regained as long as the price of the NFT has dipped far below the value at which the loan was taken out. Another method of liquidation would be by making the data provider lose the NFT if the payment of the loan has not taken place within a certain time period. Loans would have to be a certain percentage of the value of the NFT in order to make sure that both sides are incentivized to take the risk yet at the same time fulfill the conditions of the loan that were agreed upon.
Allowing this NFT collateral and fractionalization platform to work would require integration with the marketplaces and systems that the data providers used to generate or mint their healthcare NFTs to make sure that the new fractions of the NFTs can actually be created through parsing of the original NFT. The fractionalized fragments of the NFTs should also be in a format that makes it easy for stakeholders to buy the data and make use of it. Lots of close work with the stakeholders of the entire original NFT process is required. The routing of the fees and subscription payments must also be implemented in a similar way as the original NFT sales would work. Smart contracts would be coded in solidity and deployed on the Ethereum virtual machine for the sake of creating a minimum viable product.
There is also the a risk of this type of project being implemented by the stakeholders who are already in the healthcare NFT space and have already created marketplaces. These improvements and considerations could easily be implemented by them. There are already platforms that have been created for the NFTs that have high value and one of them is Nftfi. Nftfi is a platform that has provided a way for people to lend out their NFTs for fixed terms in exchange for Dai or Wrapped Eth. The NFT is used as collateral for the loan and if the loan is not paid back, the borrower loses their NFT but gets to keep the wrapped Eth. Meanwhile the lender gets to have the NFT. The marketplace supports a large variety of NFTs but does not support every single NFT. The loans that are agreed upon have a fixed apy (annual percentage yield) as well as a fixed time period.
5. Discussion
5.1 Centralized Control
In order for healthcare NFT based marketplaces to exist for NFTs to be vetting so they are providing the correct data and not falsified data as well as to hold NFTs up to a certain standard, the marketplaces have to be centralized or be subject to centralized authorities such as governments and hospitals. The governments and hospitals could set standards that the NFTs and their validity have to live up to in order to be useful. And this results in centralization issues which end up, in a way, undermining the decentralized nature of Blockchain technology. Is it possible for the NFTs to have many different formats and standards however this would stifle adoption as healthcare providers would be averse to adopting many different forms of a data sharing and entry system.
5.2 Identity Integration
Know your customer also known as KYC is a process of identification to prevent fraud. Doing KYC from one hospital to another is very complicated and time consuming and Blockchain is a solution to this issue because it can allow easier verification through immutable ledgers and would also decentralize the security of the database. KYC is also important in order for healthcare providers to coordinate treatments for patients with healthcare history of a patient.
An example for this would be that When a patient is brought to a hospital through an emergency, healthcare professionals might ask the patient about their details. These details include any injuries, diseases and the status of the body of the patient and whether the patient is at a certain propensity for certain conditions such as a high blood pressure or has autoimmune issues such as allergies. These details also include medications. Patients may consider certain conditions and medications irrelevant to their current predicament and the harm that this consideration can cause depends on the judgment and education of the patient in regards to medicine. Healthcare professionals could rarely have the time to coordinate with all the different institutions such as private clinics and other hospitals that the patient has previously visited to confirm the the patients self professed image of their medical history. Lots of information may also lie within the patients journal where the physicians at clinics typically record the visits and would require extensive reading or data mining in order to extract even if it’s present in as an EHR.
In order to overcome the obstacles that have been explained in the aforementioned example it could be useful to integrate Blockchain technology for one integrated solution such as an NFT generated from parsed data from EHRs. Such solutions have been mentioned in section 3 and many Blockchain based companies are working with hospitals. In order for their NFT based solutions to succeed it would be extremely important to agree on one format for which data should be included on the healthcare data NFT. This format could be informally decided by picking the most popular and accessible one that sees the most use through the competitive market however the process would be sped up if the Blockchain companies worked with each other more closely. Deciding on one type of format for healthcare is also a global problem do to the widely varying EHR systems of various countries that are unwilling to adopt each others systems.
5.3 Security Concerns
The possibility of the NFT data falling into the wrong hands through leakage of the data is an issue that cannot be tackled in the digital sphere and requires the aid of regulatory bodies such as governments and the justice systems of various countries to enforce. Perhaps an intersection of verification and regulations would be able to provide a solution by making parties sign legally binding documents before buying and selling the NFTs; however this solution would not be feasible for large volume reselling.
There are limited amounts of security measures that can be taken against irrational acts that seek to undermine the innovative healthcare data systems. However the most that can be done is to assume that most individuals and parties that interact with the system are rational actors and therefore are not going to undermine the system for little to no gain. Leaking medical healthcare data of patients would not, in many cases, benefit a party that has already paid for a subscription or bought limited access to the data. Due to the nature of Blockchain technology it would be easy to determine who has leaked the data, and this would cause that party to lose credibility.
One of the reasons why healthcare data NFTs could be valuable is because they are constantly changing due to the changing health of the data provider and therefore increasing in value over time. Another reason is that the authenticity of the NFT can be verified by the Blockchain. Leaked data would not have the same level of security if the party that has leaked the data has tried to remove or mask any traces of their access. Removing traces of Blockchain access would also result in removing authenticity because would not really be a way to verify the data integrity through the Blockchain and therefore the leaks cannot be trusted. In order for the data to have the most value, it is required to be accessed the correct way through having been paid for.
When it comes to the infringement of digital property rights regarding healthcare data it can be argued that unauthorized copying of NFTs would be protected by GDPR. This could enable duplicated or copied NFTs to be considered stolen digital property by the government and thus allow people to use law enforcement and the legal systems in place to sue and/or recover their digital property. As of yet NFTs are not recognizable as under copyright laws and patent laws. However the recognition of NFTs as being digital property will probably take place in the future with the increasing mainstream of crypto currencies and Blockchain technologies becomes increasingly mainstream.
6. Conclusion & Future Work
The future of healthcare data distribution depends heavily on interconnecting many different healthcare providers together so that their data can be seamlessly shared. NFTs are one way to bring the healthcare providers together through financial incentives and also a viable way to engage the patients as well. Data and technology based healthcare is very dynamic and personalized however it would take a few years for adoption to take place but Blockchain could accelerate the existing efforts to integrate data based technology such as artificial intelligence and machine learning models by engaging and financially incentivizing patients. The future of healthcare will probably be revolutionized from the ground up when patients utilize their newfound control over their data which could also accelerate research and treatment development. There are many Blockchain based platforms that have produced a wide array of tools and formed partnerships with hospitals so it can be claimed that all the tools to revolutionize the healthcare of the world are already there. They just have to be adopted.
7. References
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