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Digital Object Identifier 10.1109/ACCESS.2022.3141079
Blockchain-Based Electronic Health Records
Management: A Comprehensive Review
and Future Research Direction
ABDULLAH AL MAMUN 1, SAMI AZAM 2, (Member, IEEE), AND CLEMENTINE GRITTI 3
1School of Engineering and Computer Science, Victoria University of Wellington, Wellington 6012, New Zealand
2College of Engineering, IT and Environment, Charles Darwin University, Casuarina, NT 0810, Australia
3Computer Science and Software Engineering, University of Canterbury, Christchurch 8041, New Zealand
Corresponding author: Sami Azam (sami.azam@cdu.edu.au)
ABSTRACT Electronic Health Records (EHRs) are electronically-stored health information in a digital
format. EHRs are typically shared among healthcare stakeholders and face power failure, data misuse, lack of
privacy, security, and audit trail. On the other hand, blockchain is the revolutionary invention of the twentieth
century that offers a distributed and decentralized setting to communicate among nodes in a list of networks
without a central authority. It can address the limitations of EHRs management and provide a safer, secured,
and decentralized environment for exchanging EHRs data. Three categories of blockchain-based potential
solutions have been proposed by researchers to handle EHRs: conceptual, prototype, and implemented.
This study focused on a Systematic Literature Review (SLR) to find and analyze articles submitted either
conceptual or implemented to manage EHRs using blockchain. The study examined 99 papers that were
collected from various publication categories. The deep technical analysis focused on evaluating articles
based on privacy, security, scalability, accessibility, cost, consensus algorithms, and the type of blockchain
used. The SLR found that blockchain technology promises to provide decentralization, security, and privacy
that traditional EHRs often lack. Moreover, results obtained from the detailed studies would provide potential
researchers with the type of blockchain for future research. Finally, future research directions, in the end,
would direct enthusiasm to combine new blockchain-based systems to manage EHRs properly.
INDEX TERMS EHR, blockchain, P2P, DLT, encryption, interoperability, distributed ledger technology,
distributed computing, eHealth.
ABBREVIATION
EHR Electronic Health Record.
DLT Distributed Ledger Technology.
P2P Peer to Peer.
TTP Trusted Third Party.
DApps Decentralized Applications.
CA Certificate Authority.
HL7 Health Level Seven.
FHIR Fast Health Interoperability Resources.
NeHA National eHealth Authority.
vMR virtual Medical Record.
HIPAA Health Insurance Portability and
Accountability Act.
The associate editor coordinating the review of this manuscript and
approving it for publication was Sathish Kumar .
AI Artificial Intelligence.
ML Machine Learning.
IoMT Internet of Medical Things.
M2M Machine to Machine.
ABE Attribute-based Encryption.
AES Advanced Encryption Standard.
I. INTRODUCTION
Blockchain has been a buzzword in Information and Com-
munication Technology industry in recent years. The rise
of this new technology has greater potentials to solve data
privacy, security, and integrity issues. The word blockchain
came in the front line after the publication of the Bitcoin white
paper by Satoshi Nakamoto in 2008 [1]. The fundamental
mechanism behind Bitcoin is to make financial transactions
possible without the intervention of a trusted third party. The
technology is mainly considered a distributed Peer to Peer
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A. A. Mamun et al.: Blockchain-Based EHRs Management: Comprehensive Review and Future Research Direction
(P2P) network where digital data may publicly or privately be
allocated to all users on the web in a secure and verifiable way.
In traditional financial transactions, both sender and receiver
need to depend on a Trusted Third Party (TTP), e.g., bank.
It involves a few security issues and operational difficulties.
For instance, a TTP gets access to a user’s financial data,
which indicates the lack of user privacy. Moreover, the time
involved in a TTP transaction is lengthy as there are many
steps in between the operation. Furthermore, users need to
pay the TTP for their service. Bitcoin solves the above limi-
tations and makes the TTP vanish for a successful transaction
between two users.
The practical Bitcoin cryptocurrency came into the mar-
ket in 2009. However, since the code for Bitcoin was open
source, other programmers could edit and improve Bitcoin.
The blockchain technology has evolved in different phases.1
•Blockchain 1.0: The use of Distributed Ledger Technol-
ogy (DLT) contributed to the first and most noticeable
use of the technology: cryptocurrencies. Blockchain
1.0 is the first cryptocurrency that uses a transparent
mechanism to monitor bitcoin transactions on a shared
ledger.
•Blockchain 2.0: Doing transactions through some
legally binding policies, also called Smart Contracts,
which are generated from a set of small computer pro-
grams, is considered blockchain 2.0. The most promi-
nent blockchain in phase 2.0 is Ethereum.
•Blockchain 3.0: The next incarnation in this tech-
nology is blockchain 3.0, which focuses on Decen-
tralized Applications (DApps) by avoiding centralized
infrastructure. Unlike traditional apps, DApps store
and communicate through decentralized storage and
decentralized server. The aim of blockchain 3.0 was
to popularize blockchain among conventional sectors,
government, health, and education.
•Blockchain 4.0: It provides solutions and methods
that can meet several business demands of Industry
4.0, which involves automation, resource planning, and
integration of various execution programs. It requires
enhanced trust and privacy which can be met by
blockchain.
Many surveys have been published on the application
of blockchain in various areas. Among these papers, many
were systematic reviews on the application of blockchain in
healthcare sectors [2]–[6]. Researchers discussed blockchain
technology’s limitations, possible applications, and future
directions in healthcare, government, supply chain, and many
other fields. We have proposed a comprehensive SLR on the
application of blockchain to manage EHRs.
A. MOTIVATION AND CONTRIBUTION
Owing to the pandemic situation of COVID-19, an enormous
amount of digital healthcare data is 7being generated and
1Blockchain evolution: from 1.0 to 4.0’’, https://unibrightio.medium.com/
blockchain-evolution-from-1-0-to-4-0-3fbdbccfc666, Accessed 20 May
2021.
stored online worldwide through the Internet of Things (IoT)
devices by healthcare providers [7]. Tons of healthcare
data would be highly beneficial for healthcare providers
if analyzed. These data can help us in fighting the virus
through medical assistance, early notification, and recom-
mendation [8]. However, it has become a big challenge for
researchers to store and analyze health data because most are
incomplete and imperfect. Therefore verification and valida-
tion of such data are crucial for reporting, and recommenda-
tion [9]. Blockchain technology has great potentials to tackle
the pandemic crisis. It can help build a decentralized data
tracking system that can be retrieved when necessary.
In addition, this big healthcare data, especially EHRs,
is vulnerable to privacy and security breaches. Starting from
the COVID-19 outbreak, healthcare providers and academic
organizations faced several complex cyberattacks [10]. The
International Criminal Police Organization (INTERPOL)
published a report about cyber-attacks related to COVID-19
in April 2020.2Healthcare industries have been severely
affected alongside others by these attacks. On 6 May 2020,
INTERPOL released an awareness campaign where various
cyber-attacks during pandemic were listed.3Therefore, it is
crucial to take the necessary steps to tackle these threats.
Many researchers proposed to use blockchain technology
to overcome the above issues [11]–[14]. However, blockchain
is still in the developing phase, which means the solutions
offered with this technology are still not handy to root users.
There is still a lot of contributions needed from researchers in
this field.
By considering the above scenario, this paper aims to iden-
tify the potentiality of blockchain to manage EHRs and show
the challenges and future scopes. This systematic review only
explores research that offers conceptual solutions, experi-
mental results, prototypes, and blockchain implementations
for managing EHRs.
The rest of the paper is outlined as follows. In Section 2, the
background technologies are discussed. Research method-
ology, research questions, and discussion are detailed in
Section 3. Then, thoughts on directions for future work are
presented in Section 4. Section 5 concluded the paper.
II. BACKGROUND
We discuss blockchain technology, in brief, to help readers
understand the rest of the paper. A blockchain can be con-
sidered a public ledger that can be shared among peers in
a network. Cryptocurrencies like Bitcoin first adopted the
blockchain. However, gradually it becomes useful for data
storage. We discuss the essential characteristics and types in
2INTERPOL’s COVID-19 Global Threat Assessment https://www.
interpol.int/en/News-and-Events/News/2020/Preventing-crime-and-
protecting-police-INTERPOL-s-COVID-19-global-threat-assessment,
Accessed 25 May 2021.
3INTERPOL launches awareness campaign on COVID-19 cyberthreats,
https://www.interpol.int/en/News-and-Events/News/2020/INTERPOL-
launches-awareness-campaign-on-COVID-19-cyberthreats,
Accessed 25 May 2021.
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A. A. Mamun et al.: Blockchain-Based EHRs Management: Comprehensive Review and Future Research Direction
FIGURE 1. A standard structure of a blockchain.
the following subsections to best understand the survey and
blockchain concept.
A. BLOCKCHAIN FRAMEWORKS
Blockchain technology is an association of two technolo-
gies, cryptography, and P2P. A blockchain is a series of
timestamped blocks connected through a cryptographic hash.
Typically each block contains transaction records verified by
the peers, called miners. The chain is increased continuously,
and each new block is added to the end. However, each
new block contains a reference, basically a cryptographic
hash (e.g., SHA-256), of the previous block’s header. The
creation of each block ensures anonymity, transparency, and
immutability [15]. The whole operation of blockchain is held
in a P2P network. The basic structure of a blockchain is
shown in Fig. 1. Each block except the genesis block (first
block of the network) has the hash value of data from the
previous hash. Besides, each block has a difficulty value
called Nonce, a Timestamp, and other attributes (e.g., the list
of transactions).
1) P2P NETWORK
A P2P network works more or less like a BitTorrent network,4
where a peer, commonly known as a node, not only deploys
the system for its benefit but also contributes to the whole
system with its resources like storage, bandwidth, and pro-
cessing power. Depending on the blockchain network type
(discussed in a later section), the network node is restricted
to fewer people or open for all. The bright side for nodes in
the blockchain is that their identity is kept safe, as only the
user’s public key is shown to the other peers of the network.
Nodes also work as miners, who validate a transaction to be
added to the chain.
2) ROLE OF MINERS
Blockchain follows the structure of a linked list, where a new
block is added and connected to the previous block in the list.
However, to be added to the blockchain, a block must first
be verified by a miner. Mining here doesn’t mean checking
the transaction’s eligibility; it means doing some extra work
4Bittorent Network, https://www.bittorrent.com/btt/btt-docs/BitTorrent_
(BTT)_White_Paper_v0.8.7_Feb_2019.pdf, Accessed 11 May 2021.
after that, also called Proof-of-Work (PoW). All miners in
the network compete in computing the targeted nonce value.
The nonce, short for ‘‘number used once,’’ is a random or
pseudo-random number used for authentication protocols and
makes sure that old communications never happen again [16].
To produce a hash value below a target difficulty level, the
Nonce refers to a number (32-bit unsigned integer) generated
by PoW operation on mining nodes. The difficulty level is set
to be solved within the given time limit; Bitcoin takes around
ten minutes to add a new block. As soon as a miner reaches
a value less than the given target, he becomes eligible to get
some rewards. However, as long as the nonce value is higher
than the target value, the block won’t be eligible to be added
to the blockchain.
B. TYPES OF BLOCKCHAIN
This section contains a description of different types of
blockchain. Depending on the network size, application, and
kind of consensus algorithms (seen below), blockchain has
various kinds. Commonly, three types of blockchain exist in
the market, mentioned below.
•Public
•Private
•Consortium (Hybrid)
1) PUBLIC BLOCKCHAIN
Anyone can join the network in a public blockchain and
access the block data. It uses public DLT, where anyone
with internet connectivity can join to become an authorized
miner to mine a block. However, the users’ identity address
is generated using a pseudo-anonymous hash value even in
the public blockchain network. Anyone can only know that
someone with that address exists but does not know exactly
who. After joining the network, a user can check transactions
and mine a block to be added to the network. This kind
of public blockchain normally offers financial incentives to
the successful miner for helping to solve PoW. Example
of this type of blockchain includes Bitcoin [1], Ethereum
(public) [17], and Litecoin [18]. Public blockchains impose
some interaction costs (i.e., transaction fees), so whenever
someone wants to upload or download a document such as
EHRs, they will be charged for it. Besides, public blockchain
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A. A. Mamun et al.: Blockchain-Based EHRs Management: Comprehensive Review and Future Research Direction
is designed in a way that any anonymous user can join the
chain anytime, and it is slow in adding blocks, which is not
ideal for EHRs management. Hence, this type of blockchain
is not recommended for managing EHRs.
2) PRIVATE BLOCKCHAIN
Private blockchain has several similarities with a public one
in terms of operation and algorithms. However, it differs in
purpose. In simple terms, a private blockchain is a restrictive
or permissioned blockchain. It is operated based on some
access control rules in a closed network, which is distributed
yet centralized. This type of blockchain is usually used within
an organization or company where one or more nodes control
which node can perform transactions, act as miners or per-
form smart contracts. The security, accessibility, permissions,
and authorization are controlled by a TTP organization. This
type of blockchain is used normally for supply chain man-
agement, electronic voting, digital asset management, and
data preservation. Hyperledger Fabric [19] and Ripple [20]
are excellent examples of private blockchains. Nobody can
join a private blockchain network without an invitation from
authorized personnel. In addition, it consumes less power
than the public blockchain, and it is faster in adding blocks
to the chain. As a result, a private blockchain is suggested to
manage EHRs.
3) CONSORTIUM BLOCKCHAIN
The consortium blockchain can be best understood by com-
paring it with public and private blockchains, as the term
itself sometimes sounds confusing. We can define this type
as partly centralized and partly decentralized. Firstly, it is not
used by a single organization; rather, it is expanded in several
organizations. On the other hand, it is only accessible to
groups of previously registered nodes, so one cannot directly
access the network without first being a registered member.
A single organization in a consortium blockchain cannot
make any illegal activity, as, without the consent of other
organizations, one cannot perform any operation. The whole
concept of consortium blockchain came in to help enterprises
collaborate to improve their business. The example of consor-
tium blockchain are Hyperledger Fabric [19], Quorum [21],
and Corda [22].
C. CONSENSUS ALGORITHMS FOR BLOCKCHAIN
The consensus algorithm is a decision-making process in
a group of nodes in the blockchain which needs to be
followed by the rest of the nodes. To understand this in
detail, let us consider the following example. Suppose there
are 20 people in a business meeting to decide on an upcoming
project. Everyone can suggest their own opinion regarding the
project, but the thought that benefits most people will get a
higher preference. Similarly, if we consider a cryptocurrency,
e.g., Bitcoin, the miners need to solve mathematical puzzles
to meet PoW consensus and get some rewards in the form
of Bitcoin. In most blockchains, consensus algorithms are
the vote of majority participants. The primary purpose of
a consensus algorithm is to allow nodes to communicate
among them and provide valid transactions to be added to the
blockchain. Some of the standard consensus algorithms are
discussed below:
1) PoW (PROOF-OF-WORK)
PoW [1] is the first, currently most popular, and highly robust
consensus algorithm. A miner must find a hash value that
is less than the difficulty target and then share it with other
miners before the block is added to the blockchain. However,
PoW has certain limitations. The algorithm is resource hun-
gry, and as the blockchain grows more prominent with time,
the algorithm needs lots of computational power [1].
2) PoS (PROOF-OF-STAKE)
PoS [23] is the substitute for PoW as it deals with the main
drawback of PoW, i.e., consumption of lots of CPU power.
Unlike PoW, where any node can mine a transaction, in PoS,
a miner is chosen based on its wealth, also called stake. Gen-
erally, a pseudorandom selection process is used to select the
node allocation. In PoS, there is no incentive for mining; alter-
natively, the chosen miner collects the transaction fee [24].
Blockchains that use PoS are NEO5and Polkadot [25].
3) DPoS (DELEGATED PROOF-OF-STAKE)
In DPoS [26], tokens or stakeholders don’t work to validate
blocks. Instead, they elect delegates to validate blocks. The
selection process works so that the stakeholders are always
in control, as they lose a lot if the network doesn’t function
properly. Stakeholders can vote to remove a delegate and add
another if they find any anomaly in block creation. Delegates
can work together to validate a block and get the transaction
reward accordingly [27]. Bitshre [28], Steem [26], Tezos6are
some examples of blockchain projects that use DPoS.
4) PoA (PROOF-OF-AUTHORITY)
PoA7is an amalgamation of PoW and PoS. It values the rep-
utation of the identity of a stakeholder. Hence, a stakeholder
is not directly supported with a stake but their reputation.
Therefore, the building blocks in the blockchain are secured
by authentic and trustworthy participants. Decred [29] is an
example using this algorithm.
5) PoV (PROOF OF VOTE)
The PoV [30] algorithm is a bit different from all other
consensus algorithms. In a group of enterprises, they need
to mutually share business data, to create transaction blocks
in the blockchain. As a result, they elect a third-party team
to work for them. The team will forward the block to each
company under the network for verification through voting,
5Neo White Paper, https://docs.neo.org/docs/en-us/basic/whitepaper.
html, Accessed 15 May 2021.
6Tezos Whitepaper, https://tezos.com/whitepaper.pdf, Accessed 26 May
2021.
7POA Network Whitepaper, https://github.com/poanetwork/wiki/wiki/
POA-Network-Whitepaper, Accessed 12 May 2021.
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A. A. Mamun et al.: Blockchain-Based EHRs Management: Comprehensive Review and Future Research Direction
which ensures the decentralized property of blockchain. The
work of the hired team is supersized from time to time by
the owners of enterprises. This algorithm was developed to
be used in consortium blockchains [30].
6) PBFT (PRACTICAL BYZANTINE FAULT TOLERANCE)
PBFT [31] is the first proposed consensus algorithm to handle
Byzantine fault tolerance, where a distributed network can
achieve even if some node is malicious. It can be highly effec-
tive where non-deterministic chain-codes are executed [30].
Stellar [32], Hyperledger Fabric [19], and Ripple [20] are
examples of PBFT.
7) PoI (PROOF-OF-IMPORTANCE)
In PoI8the miner is decided not based on the amount of work
nor the amount of stake he carries, but he is chosen depending
on the productivity. The reward is not given to users with
a high balance but brings the number of transactions into
the account. Each user in the PoI network is given a trust
score. The higher the value, the higher the chance of getting
a reward. NEM9blockchain platform use this algorithm.
D. SMART CONTRACTS
Smart contracts make our daily life contracts in a digital form.
These are small computer programs written for different
blockchains to be implemented automatically for healthcare,
government organizations, and so on, based on some previous
agreements [33]. The need for smart contracts is to eradicate
trust problems, third parties, and fraud in financial transac-
tions. One may find the difference between a smart contract
and a standard business agreement. Theoretically, both are
the same, but smart contracts support automatic execution of
the predefined agreement, and this can be done for multiple
business organizations at a time.
E. DIGITAL SIGNATURES
A digital signature brings authenticity and integrity to dig-
ital assets like messages, software, documents, etc. Asym-
metric cryptography enables to authenticate transactions in
an untrustworthy environment [34]. Blockchain uses asym-
metric cryptography to sign digital transactions—the user’s
private key signs the transaction before being shared with the
distributed network. Once the transaction is signed, it is then
sent to all other peers in the network for verification. Peers
then verify it with the available public key of the transaction
initiator. If the transaction signature is valid from maximum
nodes, it is added in a new block in the blockchain; otherwise,
the transaction is discarded.
F. ELECTRONIC HEALTH RECORDS
The EHR collects patients’ medical diagnostic reports in
electronic form (e.g., JPEG, PDF). Electronic Medical
8What is POI?: https://docs.nem.io/ja/gen-info/what-is-poi, Accessed 19
May 2021.
9NEM, https://docs.nem.io/en, Accessed 11 May 2021.
Record (EMR) can serve as a collection of data sources
for EHR in different medical organizations. It also contains
personal health information collected from wearable devices
(e.g., smartwatches, smart bands), which patients manage.
EHRs are real-time, patient-centered records available to
authorized users (e.g., doctors, health providers) as required.
EHRs may comprise a wide range of data, including the diag-
nosis reports, immunity level of patients, medication history,
age, weight, and demographic history.
EHR should comply with three essential attributes: con-
fidentiality, integrity, and availability. EHR must only be
accessible by authorized users (e.g., medical practitioners
and nurses) with proper access control mechanisms. Imple-
mentation of EHR systems can reduce the loss of medi-
cal history, data malfunction, etc. However, ensuring the
privacy and security of these critical data is challenging.
In addition, cyber-attacks on smart healthcare devices [35]
are increasingly a concern because they could pose severe
life-threatening implications for patient safety. For instance,
malicious users will target patients’ wearable devices that
are connected to EHR servers. Afterward, hackers can install
some malicious program in those devices and acquire control
over them.10
1) BENEFIT OF EHR
About the benefit of EHR, the New England Journal of
Medicine published a study report in 2011, where the study
found that the use of EHR provides better care [36]. More-
over, EHR ensures the availability of many medical records
at a single point, which can be used to design machine
learning algorithms and predict better medical advice for
patients. Since with EHR, anyone with access rights can have
access to a patient’s entire chart, reducing the probability
of guessing medical history and consulting with multiple
specialists. Emergency care can be provided to any patients
more efficiently by consulting EHRs from anywhere.11
III. MANAGING EHR USING BLOCKCHAIN
EHR contains sensitive personal data (e.g., medical history
of patients). Therefore, the security and privacy of such data
are crucial. In developing countries, medical institutions are
bound to obey the rules set by the government. As a result,
storing and distributing EHR data are challenging. On the
other hand, EHR management faces lots of technical dif-
ficulties. For instance, central medical servers are low in
capacity, susceptible to single-point failure, and vulnerable
to insider attacks. Even patients do not know exactly where
their sensitive data is being stored and how it is shared.
However, this has become important as people nowadays are
mobile, so inseparability among various healthcare providers
can provide better health suggestions.
10Cyber safety and resilience, https://www.raeng.org.uk/publications/
reports/cyber-safety-and-resilience, Accessed 20 May 2021.
11Improve Care Coordination, https://www.healthit.gov/topic/health-it-
basics/improve-care-coordination, Accessed 22 May 2021.
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By considering the above scenario, Health Insurance Porta-
bility and Accountability Act (HIPAA)12 was built in the
USA. HIPAA created five sections of the act to guaran-
tee electronic protected health information [37]. Along with
ensuring confidentiality, integrity, and availability of health
information, it makes sure that healthcare providers and
other authorized individuals can have access to it. Besides,
a framework (and relevant standards) for the sharing, syn-
chronization, distribution, and retrieval of electronic health
information is provided by Health Level Seven (HL7)13 and
its members. This is committed to offering a comprehensive
structure and associated criteria for exchanging, synchroniz-
ing, transmitting, and retrieving electronic health informa-
tion to facilitate clinical practice, health care administration,
implementation, and assessment. The vision of HL7 is to
make an environment where everybody can access and use
the best health data safely when they need to.
On the other hand, the standard ISO 18308:201114 spec-
ifies the collection of specifications to be fulfilled by the
processing, maintenance, and communication of EHR infor-
mation architecture for systems and services. This standard
is made to ensure the trustworthiness of EHR for health-
care delivery, clinically valid and reliable, ethically sound,
and to support data analysis for various purposes. The EHR
is defined according to this standard as: ‘‘one or more
repositories, physically or virtually integrated, of informa-
tion in computer processable form, relevant to the well-
ness, health, and healthcare of an individual, capable of
being stored and communicated securely and of being acces-
sible by multiple authorized users, represented according
to a standardized or commonly agreed logical information
model. Similarly, the standard ISO 27789:201315 provides a
joint audit trails framework for EHR. In summary, specific
requirements should be met for the next-generation EHR
systems. Those requirements include accuracy, integrity, pri-
vacy, security, user accessibility, availability, auditability, and
accountability.
The above properties can be achieved through blockchain,
thanks to its properties like immutability, transparency, secu-
rity, auditability, and incentive mechanisms.
A. RESEARCH METHODOLOGY
We adopt SLR guidelines [38], and the Reporting Items for
Systematic Reviews and Meta-Analyses (PRISMA) guide-
lines [39] in conducting this review. An SLR refers to a
methodology for discovering, analyzing, and assessing all
recent literature related to a research issue or subject field.
12Health Information Privacy, https://www.hhs.gov/hipaa/index.html,
Accessed 23 May 2021.
13HL7 Standards - Section 1b: EHR - Electronic Health Records,
https://www.hl7.org/implement/standards/product_section.cfm?section=11,
Accessed 20 May 2021.
14Health informatics — Requirements for an electronic health record
architecture, https://www.iso.org/obp/ui/#iso:std:iso:18308:ed-1:v1:en,
Accessed 15 May 2021.
15Audit trails for Electronic Health Records, https://www.nrces.in/
standards/iso/iso-27789, Accessed 11 May 2021.
All review papers were selected by searching for rel-
evant and reliable academic repositories like PubMed,
Google Scholar, IEEE, ACM, Science Open, Science Direct,
Springer, Hindawi, Wiley Online Library, and MDPI in
December 2020.
FIGURE 2. Publications per year between 2016 and 2020.
FIGURE 3. Number of articles according to publishers.
B. RESEARCH QUESTIONS
The objective of the study was to address the following
research questions:
1) RQ1: To what extent is the blockchain developed for
managing EHRs and how has it changed over time?
2) RQ2: What standardization is followed for storing
EHRs in the blockchain?
3) RQ3: How big data related to EHRs were handled?
4) RQ4: What platforms/mechanisms of blockchain were
used to handle EHRs Management?
C. SCREENING THE ARTICLES
Selected papers are presented in this segment after screening
from various categories. The selection query for articles was
purposely long enough to consider as many research ques-
tions as possible as described in Section III-B. Using the
searching mechanism, we were able to retrieve 1282 research
articles from the scientific repositories, as shown in Fig. 4.
After the first screening step, we removed duplicates and
retrieved 139 papers. Using the second and third screening
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A. A. Mamun et al.: Blockchain-Based EHRs Management: Comprehensive Review and Future Research Direction
FIGURE 4. PRISMA chart for the SLR process.
methods (here, exclusion was based on title and abstract),
a total of 24 articles were deleted accordingly, leav-
ing 115 papers for further processing. We uploaded the
remaining papers to the Mendeley software16 for thorough
reading. Finally, all articles that did not serve the purpose of
the SLR were deducted, and a total of 99 articles was there.
Table 1includes a complete list of selected papers and
some essential details on those articles. Necessary details
include authors’ initials, year of publication, number of cita-
tions per paper up to 05 June 2021, type of publication,
a blockchain platform, blockchain type, class (1 =Concep-
tual, 2 =Prototype or Experimental, 3 =Implementation),
and the consensus algorithm. The number of articles from
several publishers has been shown in Fig. 3. It is mentionable
from the Fig. 3that IEEE and Springer published a maximum
number of articles related to EHRs, whereas MDPI and Wiley
Online Library equally published a fewer number of papers.
Several publications per year have been shown in Fig. 2. The
publication has increased gradually over five years. In 2020,
the highest number of papers had been published, 41% to be
precise.
Further analysis for the selected papers are shown in
Table 2. The table compares papers chosen based on five
16Mendeley Desktop for Windows, https://www.mendeley.com/
download-desktop-new/, Accessed 11 May 2021.
essential properties. These properties are really crucial for
EHRs. The properties are discussed below:
1) PRIVACY
Privacy refers to the right that someone can decide when, how
and at which levels accessing the personal EHRs, transform-
ing them and sharing them with others are given. [40]. Privacy
can be breached in various situations; for example, a health-
care provider may either intentionally or by mistake abuse
EHRs [41]. In a survey paper, Win [42] mentioned that around
two-thirds of patients pay attention to their personal EHRs.
In another survey, Ancker et al. [43] mentioned that close
to fifty percent of the participants believe that exchanging
health data would worsen their data privacy. Thus, privacy is
a great factor to consider when comparing blockchain-based
solutions that claim to maintain the privacy of EHRs.
2) SECURITY
Security, on the other hand, defines the level at which some-
one’s EHRs are restricted and allowed only to authorized per-
sonnel. Perera et al. [44], in their study, mentioned that around
fifty percent of the patients are worried about the security
of their EHRs as these need to travel through the Internet.
Wikina [45] mentioned that physicians are more interested in
the security of EHRs than patients, and a majority portion
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of doctors prefer paper-based records than EHRs as they
think they are more secure. Indeed, to support doctors’ pref-
erence, digital forms of health records are exposed to security
breaches [46]. That is why Liu et al. [47] suggested that
methods of providing security that is related to EHRs need to
be well understood first. These factors indicate that we should
consider security related to EHRs seriously.
3) STORAGE SCALABILITY
As blockchain technology has grown over the last few years,
it has raised scalability issues. When Nakamoto [1] started
the Bitcoin blockchain, the data storage for a single block was
limited to 1MB only. However, since then, the blockchain has
grown in popularity & participants and its blocks. A partic-
ipant has to download all the chains to learn and validate a
transaction that requires huge memory and time. However,
general blockchain applications have two solutions to miti-
gate storage scalability: on-chain and off-chain. The on-chain
storage means all data a user uploads will be directly stored
in the blockchain. On the other hand, off-chain storage means
the real data is stored somewhere other than the blockchain
such that it is linked to the main chain. However, off-chain
storage has weaker security. While storing EHRs on-chain
requires a large data space. Therefore, hosting data outside the
blockchain and maintaining high-level security is a concern
to look at.
4) ACCESSIBILITY
Accessibility requires to control and manage access to critical
or sensitive data [48]. It provides the technique for restrictive
access to data. Commonly known techniques for healthcare
systems are role-based, attribute-based, and identity-based
access control [49]. Since EHRs deal with patients’ health
data containing very sensitive information, access control is
a significant factor to consider.
5) COST ANALYSIS
Apart from the legal and ethical aspects, the cost for EHRs is
one of the most significant factors for which the widespread
adoption is still failing. A major issue is that who pays for the
implementation of EHRs is still unresolved [50]. The cost for
five-person practice to implement an EHR system is close to
$162,000 in the first year and an annual maintenance cost of
around $85,000. These can touch millions or even more for
an individual hospital.17
D. DISCUSSION
From the selected articles, this section provides a discussion
about how the papers answer the research questions from
Section III-B.
RQ1:To what extent is the blockchain developed for man-
aging EHRs, and how has it changed over time?
17Electronic health records were supposed to be everywhere..,
https://www.washingtonpost.com/news/wonk/wp/2014/08/07/electronic-
health-records-were-supposed-to-be-everywhere-this-year-theyre-not-but-
its-okay/, Accessed 7 April 2021.
The study reviewed the current extent of blockchain tech-
nology and the transition for managing EHRs, over five years
(2016-2020). Among all papers reviewed, more than half are
prototype or experimental, around one-third are conceptual,
and the rest are implemented as shown in Fig. 5. The highest
proportion of articles in this review is published after 2018,
which indicates that blockchain technology is still emerg-
ing. As blockchain technology is going through the devel-
opment phases and the usability in real-time is still under
development, most articles focused on designing a prototype
for managing EHRs. Researchers highly focused on manag-
ing EHRs using the blockchain, mainly after 2018, and the
research trend skyrocketed during the pandemic situation of
COVID-19 in 2020.
FIGURE 5. Classifications of published papers.
For managing EHRs, the authors tried to propose solu-
tions from various perspectives. While most authors focused
on the access control mechanism using Certificate Author-
ity (CA) in storing and managing EHRs using blockchain,
others focused only on EHRs data encryption mechanisms
before uploading EHRs into the blockchain. Many followed
symmetric encryption schemes for data encryption, while
others used asymmetric encryption schemes. A few authors
provided solutions for the scalability of the blockchain when
managing EHRs. Some people came with smart contracts, but
some used chain-code for EHR preserving mechanisms.
Regarding the storage of EHRs, two types of solutions
were found, such as on-chain storage and off-chain storage.
While an on-chain storage scheme focused on storing data
over the blockchain, an off-chain storage scheme stored data
either over the cloud or in the local database and linked
the data’s address to the blockchain. Current development
for storing data in blockchain involves a high cost, and the
solutions need more research as it is not yet up to the mark.
From 2016, which was the starting year for providing
the blockchain-based solutions for managing EHRs, until
2020, there has been an enormous development. In 2016,
two articles [51], [52] started the idea of using blockchain
as a platform to manage health data. Later in 2017, two
articles [53], [54] mentioned about the applicability of pri-
vate blockchain for EHRs. Afterward, researchers tried to
prove the applicability of blockchain for handling EHRs.
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TABLE 1. List of selected articles.
In the rest of the paper, most papers proposed using
either Ethereum or Hyperledger Fabric, those are private
blockchains. The practical implementation with blockchain
started with Ethereum blockchain in 2018 [55], [56].
Between 2019 and 2020 more 9 papers proposed imple-
mented solutions [57]–[64]. The authors proved that the
blockchain is a better solution for managing EHR data by
this time. While there were only two papers in 2016, the
number was 40 in 2020. Though most publications focused
on prototype designing, a few articles tried to implement the
ideas. As time passed, the interest has grown in blockchain
technology for EHR management.
RQ2:What standardization is followed for storing EHRs
in the blockchain?
The standards related to the data format and interoper-
ability principle remain an issue for sharing and storing
EHRs. While most authors did not even consider any of the
standards provided by HIPAA, Fast Health Interoperability
Resources (FHIR), and HL7, some authors either discussed
or applied the standards in their proposed solutions. Most
authors consider FHIR and HL7 when they defined standard
for EHRs data format [51], [55], [103], [107], [145]. A sig-
nificant number of authors followed HIPAA standard for their
proposed framework [81]–[83], [120], [122], [134]. However,
only a few authors followed the standard of HL7 [12], [77],
[97], [144], whereas a small number considered the standard
of FHIR [95], [96], [128]. A standard from NeHA (National
eHealth Authority) that works as a promotional, regulatory
and standard-setting organization in the health sector in India
applied in [116]. vMR (Virtual Medical Record) found in [59]
is a simplified, standardized EHR data model designed to
support interfacing to the clinical decision support system.
Among the rest of the papers, authors in [61] described the
standard of ISO 18308: 2011, HL7 and HIPAA, but did
not implement those principles. Finally, researchers in [62]
followed the openEHR standard. By contrast, the remaining
papers did not follow or describe the EHRs standards.
Having mentioned the above references, the expected
standard for EHRs exchanging, uploading, storing, authen-
ticity checking, and formatting remain a crucial issue for
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TABLE 1. (Continued.) List of selected articles.
blockchain-enabled EHRs solutions until now. It may be
because of the evolving nature of blockchain and the lack
of standardized developing platforms. While blockchain is
a promising technology for EHR management, it still needs
to go on a long run to reach a stable position to maintain a
standardized framework.
RQ3:How big data related to EHRs were handled?
EHRs generate big data continuously as the number of
people, hospitals, and healthcare centers is countless. Every
moment, thousands of patients are taking medical care from
hospitals worldwide, and EHRs are generated for diagno-
sis purposes. Handling these large amounts of data itself is
a big challenge. When it comes to handling this big data
through blockchain, it becomes more challenging as storing
data over the blockchain is expensive. The blockchain was
initially developed to keep data tiny in size, basically the
financial transaction information. However, to enjoy the mer-
its of blockchain and overcome the limitations of data storing
capacity, researchers came with several ideas.
While many haven’t considered the scalability issue of
blockchain for data storage, others focused on storing data
either over the cloud or in local databases and linking the
address from that storage to the blockchain.
Among the papers we have analyzed for the review,
slightly less than 50% of papers haven’t considered the big
data storage issue. Authors in 5 papers [105], [107], [113],
[124], [135] have considered the issue, but they haven’t
mentioned about the data storage services. In addition, there
were seven papers where authors have chosen the Inter-
planetary File System (IPFS) as a medium of data stor-
age and then linked the address with the blockchain [72],
[79], [85], [87], [116], [117], [120], [144]. Among all the
papers, only three proposed to use Amazon Cloud services
before uploading data into the blockchain network [59],
[96], [100]. Around one-fourth of the total papers sug-
gested using the local database for storing EHRs data before
blockchain. The rest of the papers proposed using pri-
vate blockchain or off-chain storage to handle scalability
issues.
The solutions provided above to overcome the big data
issues are significant, but it needs more research to handle
a considerable amount of EHRs data.
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TABLE 1. (Continued.) List of selected articles.
RQ4:What platforms/mechanisms of blockchain were
used to handle EHRs management?
Various platforms/mechanisms exist now to offer
blockchain-based solutions. Different categories of existing
blockchains are explained in Section 11 II-B. Among all the
various types, Ehtereum (public and private), Hyperledger
Fabric [19], and consortium blockchains [21], [22] is by far
the most popular for EHR data management. Due to the
nature of EHRs, which contain sensitive personal informa-
tion, a private blockchain resides on top of the popularity
index. Moreover, a private blockchain can provide access
control rules, so only specific people can join the network
by following good security policies. By contrast, a pub-
lic blockchain does not provide strict access control rules,
so anybody can join the web and get access to the data. Apart
from that, a consortium blockchain also provides a private
network and limits access to network data. Therefore, these
three types are found appealing among researchers.
Several proposed models or architectures have been
offered in the literature review. Most of the authors focused
on the integrity, availability, transparency, privacy, and secu-
rity of EHRs. Almost all the proposed models support the
storage of EHRs from medical institutions and wearable
devices. Various types of blockchain platforms used in the
literature review are shown in Fig. 7. A significant number
of papers used the Ethereum platform for the proposed
solutions. The number was equal for Hyperledger Fabric
and Not Defined (N/D), 24 in each category. The rest
of the offered solutions include Bitcoin [13], [89], [145],
consortium blockchain [67], [85], [86], [107], [112], [133],
private & consortium blockchain [91], [120], [141],
Multichain [106], [119], private blockchain [54], [108], User-
chain and Docchain [117], Permissioned Blockchain [58],
Polkadot [75], and KSI [77].
It includes numerous consensus algorithms for finding
an agreement among miners before adding a block to
the blockchain. Various consensus algorithms used in the
given literature review are shown in Section II-C. Var-
ious types of consensus algorithms found in literature
review is shown in Fig. 8. Among all the different con-
sensus used for adding EHRs in the blockchain, PoW has
been found by far the most popular. Authors chose the
PoW as the consensus algorithm in twelve research arti-
cles [11], [51], [68], [81], [87], [89], [99], [100], [103],
[127], [141], [143]. Researchers used PoA in 8 papers [61],
[76], [95], [106], [107], [109], [115], [116], whereas PBFT
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TABLE 2. Comparison of articles.
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TABLE 2. (Continued.) Comparison of articles.
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FIGURE 6. Taxonomy for five unique properties of blockchain based EHR solutions.
was suggested in 7 research papers [66], [84], [94], [96],
[97], [104], [136]. DPoS, BFT, and improved DPoS were
less popular, the number was three [12], [13], [139], two
[75], [124], and two [108], [133] accordingly. Other algo-
rithms found in the SLR were DPoS-Qoram, KAFKA, PoI,
PoS, PoV, POW and PBFT, PoW and PoS, Proof of Primi-
tiveness of data, Proof of Conformance, QuorumChain, and
Hybrid Consensus, each of these found in a single paper
among all. However, among more than 50% papers, authors
haven’t mentioned or used any consensus algorithms.
RQ5:How Privacy, Security, Storage Scalibility, Accessi-
bility, and Cost analysis were handled?
We intended to find how researchers handled privacy,
Security, Storage Scalability, Accessibility, and Cost analysis
properties in blockchain-enabled EHR solutions. These five
unique characteristics are very crucial when it comes to pro-
viding a solution for EHRs using blockchain. The mindmap
for the details of these characteristics is shown in Fig. 6.
privacy is the primary concern for blockchain-based solu-
tions as the EHRs involve sensitive personal information that
patients may or may not wish to share in public. We found
that authors in the list of papers used three properties to
ensure privacy, such as Pseudo-anonymity, Smart Contract,
and Audit trail. Pseudo-anonymity is a property of blockchain
transactions where an alphanumeric number represents every
user. Whenever a user opens a Bitcoin wallet, an automatic
alphanumeric number is assigned to her to conceal his real
identity and to allow him to send and receive Bitcoins. Any-
one with the public key can know the history of transactions
in the blockchain, but not the identity of the person behind
it.20 Similarly, it ensures the identity of a patient not to be
directly exposed to the public from his EHRs [13], [89].
Smart contracts are another privacy mechanism that authors
20Anonymity vs. Pseudonymity In Crypto, https://www.gemini.com/
cryptopedia/anonymity-vs-pseudonymity-basic-differences,
Accessed 10 May 2021.
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FIGURE 7. Types of blockchain platforms/mechanisms used.
FIGURE 8. Types of consensus algorithm used in literature review.
used for safe EHR sharing in blockchain-based applications
[72], [102]. These are simple computer programs installed
on a blockchain that run when some preconditions are met.
Using predefined smart contracts, a patient can determine
who will access his EHRs and who will be restricted from
them. Audit trail is another significant privacy property for
blockchain-based EHR solutions. It provides information
about who, when, and from where users access EHRs. There-
fore, the privacy of patients’ records is maintained using
this property. Nevertheless, among the articles we analysed,
five papers [98], [103], [70], [80], [143] have not considered
privacy in their proposed solutions.
Security is the second most important property to con-
sider for EHR-based applications using blockchain. It has
three sub-categories: confidentiality, integrity, and availabil-
ity. Confidentiality means the EHR data will only be accessi-
ble by authorized users. It is highly significant for EHRs as
patients’ information with doctors and other medical prac-
titioners is highly sensitive, and exposing those can ham-
per the security and lead to data misuse or modification.
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In most blockchain-based solutions, confidentiality is main-
tained using cryptographic tools to ensure that data is not
readable by unauthorized users [99], [108], [135]. We found
that most popular encryption algorithms are Attribute-based
Encryption (ABE) [88], Proxy Re-Encryption (PRE) [87],
and symmetric encryption (e.g., AES) [11]. Integrity of EHR
data is all about accuracy, consistency, and completeness and
also refers to their safety. Data integrity can be broken due
to human errors, bugs, and hardware failure, leading to the
loss of critical health records and sensitive personal informa-
tion. Blockchain ensures the integrity of information found
in blocks using hash functions (e.g., SHA-256). Besides,
every node in the blockchain network has either a copy of
EHRs when they are stored on the blockchain [53], [143],
or a copy of the pointer to EHRs when stored externally
(e.g., cloud) [11], [71]. Availability means that EHRs are
available when and where the user needs them. If the data
is not known when the user wants it, there is no use in storing
it; moreover, the user may face tragic consequences such
as wrong medication or incomplete medical consultation.
As blockchain is a distributed ledger, there is a slight chance
of losing data or accessing it. However, Even though off-
chain data storage does not ensure data availability, it can
ensure that if the data is missing from the host database,
digital data forensic can be done using the data pointers.
Most blockchain-based applications for EHRs focused on
the system being fault-tolerant during any system failure
[65], [98]. All papers, except one [76], considered security
when proposing their blockchain-based solutions.
Storage scalability is a big concern for blockchain-based
solutions. A blockchain is a distributed ledger that increases
in size each time a block is created. The literature review
considers three main challenges: block creation time, block
size, and ample data storage. Block creation time corre-
sponds to the time needed to store either EHRs directly or
some auxiliary data linking EHRs stored externally from the
blockchain. It is crucial as EHRs data are generated contin-
uously across the world. If the time taken for storing these
data is long (e.g., When EHRs are developed every minute,
blocks creation time needs to be shorter than that), it will
cause problems for both patients and doctors. Similarly, block
size refers to the capacity limit of data in a block. This is
also important as EHR data vary in size. Various blockchain-
based solutions have been proposed with these issues in mind
but different results. For instance, Bitcoin takes around ten
minutes to create a new block, and the maximum block size
is 1 MB [1], whereas Ethereum takes about 10-20 seconds
to create a new block21 and the average block size is about
50-60 KB.22 Finally, big data storage refers to storing huge
EHR data generated all around the globe. It is mandatory to
analyze the capacity and the scalability of the data storage
options of a blockchain to handle these big data by storing
21Ethereum Average Block Time Chart, https://etherscan.io/chart/
blocktime, Accessed 15 May 2021.
22Ethereum Average Block Size Chart, https://etherscan.io/chart/
blocksize, Accessed 15 May 2021.
a large set of dummy data23 before deploying. Failing to do
so will not be fruitful for patients worldwide. Authors such
as [100], [108], decided to put the EHRs in external databases,
such as local or cloud databases, in order to cope with the
limited storage of blockchains. However, when storing data
outside the blockchain network, it is crucial to consider
the security of the storage options (e.g., encryption, access
control). For storage scalability, several authors [105], [108]
proposed solutions that are costly but easy data access.
Accessibility is another important property related to the
EHR data access policies in the blockchain. We found three
major sub-properties to ensure the proper accessibility of
EHRs: access control, authorization, and platform indepen-
dence. Access control verifies EHR access rights. It has two
aspects: patients accessing their own EHRs [37] and other
users accessing those same EHRs [12], [98]. The former case
is pretty simple as the patients should have all the rights
to access their own EHRs, but the latter requires careful
investigation. Often, a third party who requests access to the
owner of EHRs, follows a public-key encryption process [98].
For instance, ABE [88] allows third parties to get access
rights from some attributes such as ‘‘doctor’’ and ‘‘hospi-
tal.’’ Authorization is the process where a patient or hospital
authorizes someone to get access to his EHRs. It is sometimes
(depending on the country’s legislation) illegal to access
someone’s EHRs without his consent [37], as this may then
expose the data to malicious users. Furthermore, platform
independence is the property of a blockchain-based solution
that makes sure it runs on all platforms for smartphones and
computers, such as Android, Windows, and MAC. Failing to
do so will create accessibility problems not only for patients
but also for physicians. All papers except five, [98], [123],
[129]–[132] considered accessibility carefully when design-
ing their blockchain-based solutions.
Finally, cost analysis is a significant feature to offer
in blockchain-based EHRs solutions. Costs are involved in
adding a block to the blockchain, rewarding miners, and
uploading and maintaining a database when EHRs are stored
externally. Data storage cost is higher when directly stored in
blockchains [85], so authors [100], [108] came with off-chain
data storage. However, even if EHRs are stored in external
databases, it is pretty expensive to store huge amounts of EHR
data generated every day worldwide.24 Data Maintenance in
local or cloud databases involves a huge cost such as work-
force, computing resources, and resources for data sharing.
This is a significant issue when making EHR management
using blockchain. Finally, miners’ rewards are the expense
for people who mine a block before accepting and uploading
it to the blockchain. Miners are there to ensure that they will
upload only the eligible and authentic data to the blockchain.
If we consider a large-scale blockchain-based solution for
234 ways to create random dummy files.. https://www.digitalcitizen.life/3-
ways-create-random-dummy-files-windows-given-size/, Accessed 12 May
2021.
24Why new off-chain storage is required for blockchains, https://www.
ibm.com/downloads/cas/RXOVXAPM, Accessed 23 May 2021.
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EHRs, these costs (e.g., transaction fees, miners’ reward, and
database maintenance) are significant to consider. However,
only 24 papers [56], [59], [68], [71], [75], [77], [81], [84],
[86], [87], [91], [99], [108], [110], [112], [115], [117], [118],
[124], [126], [127], [130], [131], [137] discussed or analyzed
the cost induced by their solutions using blockchain. The
remaining 75 papers did not focus on the cost issue.
IV. FUTURE RESEARCH DIRECTION
This section discusses about directions for designer of
blockchain applications to handle EHRs.
A. ARTIFICIAL INTELLIGENCE
When blockchain systems are integrated with Artificial Intel-
ligence (AI) in different real-world healthcare solutions, they
will become more efficient and stable [146]. Machine learn-
ing (ML) and deep learning (DL) are two main domains of
AI which are helping to automate real-world applications.
ML could be a potential technology in combination with
blockchain to handle EHRs in the near future. Despite the
challenges like storing, sharing, and training critical EHR
data for designing practical applications, interest is growing
among researchers to develop ML, and blockchain-based
EHR applications [147], [148]. IBM has recently announced
plans to deploy intelligent blockchain, where some AI agent
performs various tasks like legislation, improved records,
suspicious activities and make suggestions for updating smart
contracts in a large network.25 AI is used to develop a
next-generation blockchain in the MATRIX project [149],
which facilitates the automated generation of intelligent con-
tacts, improves the protection against malicious threats, and
enables highly scalable operations.
Using various ML algorithms, one can find fraudulent
EHRs data, and only valid EHRs will be stored in the
blockchain. Using DL, previous damaged medical records
can be recovered and stored in blockchain for knowledge
improvement (e.g., for drug analysis and prediction) [150].
Deep Learning as-a-Service (DaaS) is also used on stored
EHRs to precisely predict future diseases based on cur-
rent diagnosis reports of patients [151]. Finally, ML algo-
rithms can be used to prevent major attacks in blockchain
networks [152]. There are some existing projects where
AI and blockchain are combined. For instance, Singulari-
tyNET [153], which focuses on creating networking with
AI and blockchain for the robot brain, and DeepBrain
Chain,26 which focuses on creating a platform to develop
AI algorithms. Besides, some ML and DL based works
related to health are underway, such as Gamalon project,27
TraneAI [154], Neureal [155], etc.
25AI & Intelligent Automation, https://www.tractica.com/artificial-
intelligence/four-examples-o-fblockchain-artificial-intelligence-
deployments/, Accessed 25 May 2021.
26Artificial Intelligence Computing Platform Driven By BlockChain-
DeepBrain Chain, https://cryptorating.eu/whitepapers/DeepBrain-Chain/
DeepBrainChainWhitepaper.pdf, Accessed 26 May 2021.
27ABOUT GAMALON, https://gamalon.com/company/,Accessed 26
May 2021.
B. EDGE COMPUTING
Sharing large amounts of EHRs among various health care
organizations is challenging because of network loads and
data size. Recent solutions for EHR management, in par-
ticular, have poor scalability, high computational cost, and
extended response times. Edge computing could be a solution
for the issues mentioned above. It can process a large amount
of data from diverse locations, as edge computing consists
of a group of servers/computers for its operations [156].
Gai et al. [157] suggest edge computing to expand cloud
services to the network’s edge, providing processing capacity
and enhancing device Quality of Operation.
Edge Computing has the advantage of big data storing,
long networking, and high computing power, and it supports
the scalability for distributed applications in a secure and
controlled manner. Even though edge computing has several
flaws such as security, vulnerability to various attacks during
message transmission, and integrity, blockchain-based solu-
tions face numerous problems such as storage, scalability,
constraints of block size, and block creation time that can
be solved using edge computing. Similar mechanisms for
decentralized technologies can enhance privacy, security, and
automatic resource handling [158]. Combining both can have
several merits. Firstly, we can build distributed controls at
various edge nodes using blockchain. The mining process
of blockchain confirms data accuracy, consistency, and reli-
ability. Secondly, user privacy can even become higher as
users control the data using cryptographic keys. Finally, edge
computing involves resource sharing among other nodes,
which can be achieved securely using smart contracts on
blockchain [159].
C. IoMT
Internet of Medical Things (IoMT) is a series of medi-
cal equipment and software that use online computing net-
works to link to various healthcare providers. The basis of
IoMT is the Machine-to-Machine (M2M) communication
among wireless medical devices. Through the IoMT, medical
care providers & authorities can get the real-time health
update of patients from remote locations through wearable
devices.
However, besides the advantages of IoMT, there are sev-
eral downsides to it, as IoMT devices are vulnerable to
security threats. During the pandemic situation of Covid-19,
not only the demand for innovative medical devices has
increased enormously, but the cyber threats related to them
also increased significantly [160].
Blockchain can be considered a savior for the threats
related to IoMT devices. The decentralized key manage-
ment, inseparability, and integrity properties of blockchain
can ensure secure communications among smart Medical
devices.
V. LIMITATIONS
The SLR solely focused on applying blockchain for EHR
management and did not include any other potential
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blockchain applications related to other healthcare sectors
(e.g., supply chain management for medicine) or any other
fields (e.g., transaction handling). The review was strictly
limited to articles that only addressed EHR and blockchain
ideas.
We identified several limitations of blockchain-based EHR
solutions. Limitations include common standard, scalability
in terms of storage, block creation time, data storage, user
adaptation, and storing and maintaining EHR data costs. Most
of the solutions are still in either a theoretical or prototype
state. Blockchain technology is still in a developing state that
lacks user-friendliness and has limitations regarding EHR
privacy and security of EHR data. No solutions have been
found to either delete fraud EHR data from the blockchain or
for dead patients.
Besides, no acceptable solutions were found for the sce-
nario where a patient is in a coma, unconscious, or illit-
erate, and his EHRs need to be accessed by the doctors
or physician. One possibility is that the patient has an ID
card with a unique identification number, and the doctor can
read the EHRs using it. Finally, aggregation of technolo-
gies like ML, AI, and Edge Computing may help overcome
problems like scalability, fraud EHRs detection, and many
more.
VI. CONCLUSION
This study answers the question of the current state of the art
in blockchain-based EHR management research and future
directions. We showed the distribution of blockchain types
and platforms adopted by the reviewed articles. The potential
benefits of blockchain to manage EHRs have met stakehold-
ers’ expectations in the healthcare sectors, while we also
found that several challenges require further research. For
instance, cross-border sharing of EHR data may be ham-
pered by varying and often conflicting legislation. Besides,
the privacy policies also vary based on the specific gov-
ernment regulation. Hence, further investigation on regula-
tion, standardization, and cross-border accessibility of EHRs
is crucial.
However, After thorough scrutiny of selected articles,
we concluded that the most prominent blockchain platform
for EHR management is Ethereum (private) and Hyperledger
Fabric because these two platforms meet almost all the
requirements. We also found that handling big EHR data on
a large scale with blockchain has limitations such as limited
storage capacity, computation cost, and communication cost.
However, there are potential solutions to overcome these
limitations, such as artificial intelligence, IoMT, and edge
computing.
The study may serve as a reference for future research
in this field. The accumulation of all related papers,
their contributions, and limitations will help the poten-
tial researchers to design a new architecture or model.
Moreover, future research directions to combine blockchain
could help propose more exciting solutions for the existing
problems.
DECLARATION OF COMPETING INTEREST
The authors declare that they have no known competing
financial interests or personal relationships that could have
influenced the work reported in this paper.
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ABDULLAH AL MAMUN is currently a Ph.D.
Researcher with the Victoria University of
Wellington, New Zealand. He is also working
towards designing a proactive honeypot based on
artificial intelligence and blockchain-based elec-
tronic health records management. His research
interests include honeypots, machine learning,
cybersecurity, information security, data privacy,
and blockchain.
SAMI AZAM (Member, IEEE) is currently a
Leading Researcher and a Senior Lecturer with
the College of Engineering, IT and Environment,
Charles Darwin University, Australia. He has num-
ber of publications in peer-reviewed journals and
international conference proceedings. His research
interests include computer vision, data privacy and
security, signal processing, artificial intelligence,
and biomedical engineering.
CLEMENTINE GRITTI received the M.Sc. degree
in computer science from Grenoble Alpes Univer-
sity, France, in 2012, and the Ph.D. degree in com-
puter science from the University of Wollongong,
Australia, in 2016. She is currently a Lecturer
at the Computer Science and Software Engineer-
ing Department, University of Canterbury. Prior
to joining the University of Canterbury last year,
she worked at the Norwegian University of Sci-
ence and Technology, Norway, and at the Graduate
School and the Research Center in Digital Sciences Eurecom, France. She
previously worked on several research projects dealing with information
security and privacy for electronic health and electronic voting. Her current
research interests include design and evaluation of public-key cryptographic
protocols for security and privacy in various environments, such as cloud
computing, the Internet of Things, and blockchain. She has been a Program
Chair Member for security conferences, such as the Australasian Confer-
ence on Information Security and Privacy and International Conference
on Cryptology in India. She has been a Reviewer for various journals,
such as IEEE ACCESS, the IEEE INTERNET OF THINGS, and Computers and
Security (Elsevier).
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