Personal health records (PHRs) are a form of electronic health records (EHRs). PHRs are unique in that patients themselves can access, manage, and share their health information [1]. The benefits of PHRs include patient empowerment, which leads to improved outcomes and reduced health care costs [2,3]. Although interest in PHRs has been increasing, their adoption remains low [4,5]. One of the oft-cited reasons is related to privacy and security concerns owing to an increasing trend of health information breaches [6,7]. Another reason is the lack of perceived usefulness to patients [7].

Blockchain technology was introduced through Bitcoin in 2008 [8]. It is considered a general-purpose technology and has since been successfully applied across several different industries [9,10]. In the health care industry, EHRs were found to be the most commonly used case for blockchain applications [11-14]. Compared with conventional data management methods that rely on on-premise data servers or third-party cloud services, blockchain’s distributed ledger technology offers a novel alternative. This could potentially address the privacy and security concerns surrounding EHRs [15]. Specifically for application to PHRs, blockchain also has the ability to decentralize control and incorporate incentive mechanisms through smart contracts, which can further entice its general use and increase adoption [16]. These advantages, among others, have motivated efforts to test the feasibility and implement blockchain PHRs [17-19].

The research space in which EHRs and blockchain intersect is still in its infancy, with the first blockchain EHR introduced in 2016 [20]. Systematic reviews covering this space so far have considered EHRs as a collective entity. Mayer et al [21] provided an overview of the ecosystem of blockchain EHRs while also proposing a taxonomy for the space. Shuaib et al [22] looked at the main areas of focus when implementing a blockchain EHR and the remaining issues to be addressed, whereas Vazirani et al [23] assessed the feasibility of blockchain as a method of managing health care records efficiently.

Given that one of the inherent properties of blockchain is its decentralized nature, in which data ownership is placed in the hands of individual users, some have proposed that blockchain may be more suitably applied to PHRs specifically rather than EHRs in general [19,24-26]. In this paper, we aim to systematically review the following: (1) the current landscape and trends of blockchain-based PHRs (blockchain PHRs), (2) the attributes of various blockchain PHRs that have been described, and (3) the current limitations and future directions for blockchain PHRs. To the best of our knowledge, this is the first systematic review examining blockchain with PHRs. We hope that this review will serve as a useful reference, especially for those intending to develop a blockchain PHR and for future reviews in this area.

To provide more context for subsequent sections of this paper, we will first explain pertinent blockchain concepts and take the opportunity to introduce some terminology specific to blockchain. This is by no means an exhaustive explanation of blockchain.

A blockchain can be thought of as a shared (or distributed) database that is spread across multiple sites and participants. For new data to be added to a blockchain, they are first compiled into a block, which is simply a collection of records to be added to the database. The block is then combined with some data (a hash key) from the previous block through a cryptographic technique called hashing before it is added. As it combines the previous block’s hash key, each new block is tied to all its predecessors in the form of a chain—hence the term blockchain (Figure 1).

Before data can be added to a blockchain, its users need to agree or reach consensus. This is achieved through a consensus algorithm. A well-known consensus algorithm is the proof of work (PoW) algorithm. PoW is used in the Bitcoin and Ethereum blockchain network protocols [8,27]. In the PoW algorithm, users (also known as miners) compete in computational tasks to reach consensus. The winning miner of each block’s task is usually given a reward [28].

Blockchains can be classified into the following three types, depending on which participants are allowed in the consensus algorithm [28]:

Public blockchains are sometimes referred to as permissionless blockchains, whereas consortium and private blockchains are collectively termed permissioned blockchains.

The three types of blockchains differ in the following properties:

Table 1 provides a summary of the different types of blockchains and their properties, with an example of each type in the health care setting.

Finally, we will briefly explain the two concepts of scalability and smart contracts, which will be relevant to subsequent parts of this paper.

Scalability refers to the capacity of a blockchain to store and process transactions. It generally relates to the size and frequency of transactions a blockchain can handle. For example, Bitcoin’s block size is limited to 1 megabyte, and each block is added every 10 minutes. This translates to a rate of approximately 7 transactions per second. Various solutions have been proposed to improve scalability. One such solution is to store data off-chain (instead of on-chain), and another solution is to use side-chains (linked to the main chain) to enable larger transaction volumes to be processed in parallel. Given that health care data are estimated to reach as much as 2314 exabytes generated yearly by 2020, it is crucial for almost all blockchain-based health care applications to achieve a certain level of scalability [32].

Smart contracts are programmable computer rules. Blockchain is a digital database that allows for the implementation of smart contracts, which can be automatically triggered to execute when predefined conditions are satisfied. For example, a smart contract can be programmed to issue tokens on the blockchain each time a user records his or her blood pressure. These tokens can then be used to pay for health care services. Such smart contracts can thus potentially be used to enable incentive structures to encourage certain positive user behaviors.

In this systematic review, particularly focused on the blockchain component of blockchain PHRs, we will pay particular attention to the (1) type of blockchain, (2) scalability solutions, and (3) smart contract–based incentive structures.

While conducting and reporting this systematic literature review, the guidelines described in the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) statement were adopted [33]. This type of literature review was selected because the goal was to identify articles on blockchain PHRs and to summarize the current landscape, design choices, limitations, and future directions. Unlike a meta-analysis, this review did not require any data synthesis. Quality assessment was not performed because the intention was to achieve a collective understanding of the efforts and ideas rather than judging the quality of various blockchain PHRs.

The presented systematic review was carried out by defining the following activities:

The search performed on July 6, 2020, yielded 325 articles, of which 158 were unique articles. From the article selection process, 51 articles were selected for review. An additional 7 articles were added via snowballing (review of the references from the included articles) of the full texts screened (Figure 2).

A total of 58 studies were included in the final review [17,19,37-92]. The complete list of articles, with identifiers used in this study, are presented in Table 3. The completed data collection form for these articles can be found in Multimedia Appendix 1. An overview of the articles with the publication year, publisher, article type, country, and interest group is presented in Multimedia Appendix 2 [17,19,37-92].

In this first ever systematic review on blockchain PHRs, we adopted a broad search strategy across medical and CS and engineering databases and included gray literature. We focused on the scope of blockchain PHRs to allow for more targeted data abstraction. Through our study, we found that there was a growing interest in blockchain PHRs and that the space has been steadily maturing over the past few years, albeit still much in the conceptual stage. As the space is still fairly new, a lion’s share of the research and innovation has been happening at the technical level to discover new ways to solve problems. This is evidenced by the overwhelming proportion of articles that have come from the CS and engineering domain.

One of the major areas regarding blockchain PHRs that is still undergoing much research is scalability. We came across a few ideas such as Proof-of-Authority, novel BFT consensus mechanisms, and other modified blockchain architectures such as tiered-chains and side-chains [40,44,56,57,64,67]. Apart from blockchain PHR teams working on this, the space may also benefit from parallel innovations from the larger blockchain ecosystem. As Ethereum is looking forward to a new version release (version 2), it is considering various scaling solutions, of which rollups is a strong contender [93]. Rollups solution essentially involves keeping transaction data on-chain while pushing the computational load off-chain. If adopted into Ethereum 2.0, this could automatically benefit many Ethereum-based PHRs.

Although some areas are actively evolving, others are beginning to consolidate. As found in other systematic reviews, most blockchain PHR project teams have gravitated toward Ethereum and HF as their blockchains of choice [22]. In addition, in terms of data storage, we see more projects opting for IPFS as a complementary off-chain data store for their blockchain PHRs [68,72,83,92]. Outside of this review, we are also aware that there are efforts happening in other public blockchains. An example is NEO, whose core developers are developing a similarly distributed, decentralized object storage network known as NEO file storage system (NeoFS), which will seamlessly integrate with its native blockchain [94,95]. We did not come across any NEO-based PHRs in this review. NeoFS could potentially be a game changer, so it would be interesting to track its development in this area.

In this review, we also identified some current limitations that blockchain PHRs need to address. We broadly classified them into scalability, privacy, and usability limitations. In addition to identifying the current limitations, this review also revealed some possible solutions. For example, to address the privacy issue of inferring information from chain analysis, Ray Chawdhuri [54] introduced zero-knowledge provable mixing, whereas Park et al [17] proposed the zero-knowledge succinct non-interactive argument of knowledge technique. Another example is the solution of using biometric authentication mentioned by Tian [75] to address the issues of verifiable user authentication and patients losing their private keys. Medicalchain has also described an emergency bracelet that can be scanned, giving access to essential health information in unconscious patients who are unable to access their private keys [47].

The first blockchain PHR has already been piloted, and this will undoubtedly augur a move of the space toward deployment [19]. With this in mind, blockchain PHRs will need to comply with the privacy standards within the jurisdictions they intend to become operational. In addition, to enable integration with existing health care EMR systems, it is necessary to design blockchain PHRs that follow established semantic standards such as HL-7 and FHIR. Looking further ahead, to realize true decentralization, it may be necessary to consider building a PHR atop public blockchains.

Finally, in terms of geographic interest, we found that although interest in blockchain PHR was multinational, there were obvious leaders in this space. Looking deeper among the leading countries, we noticed that since 2018 there has been an increase in publications from India, whereas those from China, South Korea, and the United States started to level off or decrease. A possible reason for this could be that in 2017, in the midst of an initial coin offering (ICO) fever that drove unusually high interest in blockchain, the latter 3 countries’ relevant authorities had issued bans or indicated legal restrictions on ICO activities with stiff penalties [96-98]. This may suggest further research into the different factors, including sociopolitical, economic, and cultural factors, which could significantly impact the development of this space. In terms of interest groups, our findings should also provide a sense of where most of the developments are occurring, and this may guide government and private sector funders in their allocation of resources.

We acknowledge that this review is not exhaustive and that there are many other areas that were excluded. These areas include other smart contract uses, performance evaluation, and the type of vocabulary standard such as Systematized Nomenclature of Medicine Clinical Terms, 10th revision of the International Classification of Diseases, and Logical Observation Identifiers Names and Codes. We also recognize that greater detail about the read and write models could be studied, such as their validity periods and whether other stakeholders (eg, researchers and insurance companies) were given access. Future reviews should consider delving deeper into these areas.

Furthermore, despite our best efforts to capture as much material available as possible, we are aware that the exclusion of articles whose full text was not in English would have limited the scope of this review. In addition, there may also be other developments in this space that have not been made publicly available for commercial or other reasons.

This cross-disciplinary systematic review on the blockchain PHR space has revealed that as of now, much of the development is still in the conceptual stage. However, there is a trend of growth and maturation. We believe that this provides consolidated evidence for researchers to continue following this space and, more optimistically, to spur them to contribute ideas and efforts to accelerate its development. Those in the medical informatics community will undoubtedly play an increasingly larger role in the development and implementation of blockchain PHRs, especially when the need to integrate with EMR systems and adopt health care data standards becomes more prominent. In addition, as the first systematic review covering blockchain PHRs, we expect this to be an important basis for subsequent reviews to track how the space has progressed in the future.