# Analysis of Blockchain Integration in the e-Healthcare Ecosystem

Abdellah OUAGUID  ENSET, Hassan II University, Mohammedia, Morocco  Mohamed
HANINE  LTI Laboratory, National School of Applied Sciences, Chouaib Doukkali
University, El Jadida, Morocco  Zouhair CHIBA  L.I.S Labs, FSAC, Hassan II
University, Casablanca, Morocco  Noreddine ABGHOUR  L.I.S Labs, FSAC, Hassan
II University, Casablanca, Morocco  Hassan GHAZAL  Laboratory of Genomics,
Bioinformatics and Digital Health,
Mohammed VI University of Health Sciences, Casablanca, Morocco  Laboratory of
Genomics, Bioinformatics and Digital Health,
Mohammed VI Center for Research and Innovation, Rabat, Morocco  Royal
Institute of Sports, Salé, Morocco

###### Abstract

No one can dispute the disruptive impact of blockchain technology, which has
long been considered one of the major revolutions of contemporary times. Its
integration into the healthcare ecosystem has helped overcome numerous
difficulties and constraints faced by healthcare systems. This has been
notably demonstrated in the meticulous management of electronic health records
(EHR) and their access rights, as well as in its capabilities in terms of
security, scalability, flexibility, and interoperability with other systems.
This article undertakes the study and analysis of the most commonly adopted
approaches in healthcare data management systems using blockchain technology.
An evaluation is then conducted based on a set of observed common
characteristics, distinguishing one approach from the others. The results of
this analysis highlight the advantages and limitations of each approach, thus
facilitating the choice of the method best suited to the readers’ specific
case study. Furthermore, for effective implementation in the context of
e-health, we emphasize the existence of crucial challenges, such as the
incomplete representation of major stakeholders in the blockchain network, the
lack of regulatory flexibility to ensure legal interoperability by country,
and the insufficient integration of an official regulatory authority ensuring
compliance with ethical and legal standards. To address these challenges, it
is necessary to establish close collaboration between regulators, technology
developers, and healthcare stakeholders.

###### Index Terms:

Blockchain, Electronic Health Record (EHR), Healthcare system, Security,
Privacy

##  I Introduction

In the realm of e-health systems, particularly those managing sensitive data
such as patients’ Electronic Health Records (EHR), play a crucial role in the
security and evolution of the healthcare ecosystem[1]. Their continual
adaptation to emerging technologies (AI, IoT, blockchain, etc.) enables them
to leverage the benefits of these advancements while enhancing their level of
maturity.
However, the multitude of services comprising the healthcare ecosystem can
render the complete digitization of such a system complex, particularly in
terms of managing its interoperability with existing or third-party systems.
Figure 1 illustrates the organization of services within the healthcare
ecosystem, which can be classified into two types: clinical and non-clinical
services. Clinical services encompass all activities involving direct
interaction with the patient (such as diagnosis, therapy, and observation). In
contrast, non-clinical services refer to roles that do not directly involve
patient treatment but actively interact within the clinical environment, such
as medical research, information technology, and administrative assistance.
These diverse services generate data flows, both coherent and incoherent,
which fuel the operation of several systems, including EHR management systems,
supply chains, and scientific research.

Figure 1: Healthcare Ecosystem Overview

The significant transformation experienced in the healthcare sector,
particularly during the COVID-19 public health crisis, has attracted the
attention of malicious actors, leading to an increase of over 69% in the
volume of ransomware cyber-attacks targeting healthcare systems[2]. This
percentage represents the highest proportion compared to all other domains and
sectors in 2021. During the first quarter of 2023, industry-specific attack
ranking revealed a notable 22% increase in attacks on the healthcare sector
compared to the previous year, with a weekly average of 1,684 attacks (Table
I)[3]. This underscores the imperative to prioritize the security, integrity,
and confidentiality of patient data while digitizing an electronic healthcare
system to mitigate any form of attack (DDoS, data breaches, ransomware,
malware, phishing, etc.) that may compromise its proper functioning.

TABLE I: Global and Ransomware Attack Rates by Industry (Average Weekly) Industry | Global Attacks |  Ransomware Attacks∗
---|---|---
2022 Q1 |  2023 Q1 | # | %
Education/Research | 2180 | 2507 | 327 | +15 | 1 out of 26
Government/military | 1675 | 1725 | 50 | +3 | 1 out of 20
Healthcare | 1380 | 1684 | 304 | +22 | 1 out of 27
Communications | 1466 | 1598 | 132 | +9 | 1 out of 33
ISP/MSP | 1474 | 1312 | -162 | -11 | 1 out of 27
Finance/Banking | 1112 | 1212 | 100 | +9 | 1 out of 25
Utilities | 1013 | 1185 | 172 | +17 | 1 out of 32
Retail/Wholesale | 724 | 1079 | 355 | +49 | 1 out of 44
Insurance/Legal | 934 | 1055 | 121 | +13 | 1 out of 40
Leisure/Hospitality | 959 | 997 | 38 | +4 | 1 out of 51
Manufacturing | 982 | 992 | 10 | +1 | 1 out of 41
SI/VAR/Distributor | 917 | 963 | 46 | +5 | 1 out of 31
Consultant | 699 | 881 | 182 | +26 | 1 out of 33
Transportation | 769 | 784 | 15 | +2 | 1 out of 50
Software vendor | 803 | 763 | -40 | -5 | 1 out of 48
Hardware vendor | 398 | 525 | 127 | +32 | 1 out of 49
∗ X attacks out of every Y organizations.

Presently, the deployment of systems or applications requiring substantial
storage space and significant computing power has become accessible to all
entities, regardless of their size, owing to the growing and continuous
adoption of cloud service providers or SaaS partners vying to offer
competitively priced services with superior quality [4].
However, various limitations and challenges associated with the client-server
paradigm have emerged, particularly concerning the processing, storage, and
sharing of sensitive patient data. Furthermore, these systems pose risks
regarding the availability, trust, and integrity of stored data. The benefits
offered by innovative technology such as blockchain can address certain
requirements left unmet by traditional systems[5]. Its adoption and use in the
healthcare sector ensure system availability (eliminating any single point of
failure risk), guarantee patient data traceability, and facilitate their rapid
and secure sharing among system entities.
In this article, we highlight the common and distinctive features of the four
approaches through an in-depth study, comprehensive evaluation, and overall
comparison of the described approaches. The rest of the article is structured
as follows: section 2 presents the context of EHRs along with an introduction
to blockchain technology. Section 3 provides an overview of the integration of
EHRs into blockchain-based systems. Subsequently, we present the approaches
under study in section 4, followed by a detailed analysis and synthesis in
section 5. Finally, section 6 presents the article’s conclusion and future
research perspectives.

##  II Electronic Health Records (EHRs)

EHRs are collections of private and sensitive electronic information
concerning a patient’s health. Data can be gathered from treatments,
diagnoses, or analyses performed directly on the patient, with the
results/observations recorded by a healthcare professional (physician, nurse,
etc.) in a hospital system or automatically retrieved from wearable or
portable devices managed by the patients themselves. Secure sharing and access
to EHRs must be ensured for all authorized stakeholders (patients, hospitals,
laboratories, research centers, insurers, etc… ), while guaranteeing the
availability and reliability of stored and exchanged data, reflecting the
current health status of the patient as well as their medical history
(vaccinations, surgical interventions, etc…).
EHRs are sometimes confused with Electronic Medical Records (EMRs) [6]. As
depicted in Table II, the scope of the EMR is limited as it is not shareable
among the various entities within the healthcare ecosystem. This implies that
ultimately, the EMR only covers the scope of the creating entity (e.g., the
hospital) and is fuelled by data generated through its interventions and care.
In contrast, the EHR provides a comprehensive and detailed view of a patient’s
health information.

TABLE II: Differences Between Electronic Medical Records (EMR) and Electronic Health Records (EHR) in Healthcare Management | EMR | EHR
---|---|---
Healthcare Provider(s) | One | Multiple
Patient Record | Stored locally |  Shared between healthcare entities
Access for the Patient | View-only | Editable
Patient Record History |  Limited to a single provider’s office |  Accessible across various authorized provider’s offices
Real-time data Accessibility
Data Analysis |  |
Data Interoperability | No | Yes

##  III Blockchain Technology

###  III-A Definitions and concepts

Blockchain is an emerging secure technology based on a distributed
architecture, enabling the secure exchange and storage of data among
autonomous ’nodes’, without relying on a central or intermediary authority
[7]. These nodes, essential constituents of the blockchain network, engage in
the exchange, validation, and preservation of data in ’blocks’ that
consolidate multiple ’transactions’. This technology, whose composition is
illustrated in Figure 2, has brought about significant transformations in
various sectors, such as finance [8, 9], the Internet of Things (IoT) [10],
medical applications [11], supply chain logistics [12], computer security
analysis [13], access control systems [14], digital marketing [15], trust
management [16], E-learning [17] and artificial intelligence [18, 19]. Its
impact stems from its effective establishment of transparency and trust among
participants.

Figure 2: Core components of the Blockchain technology

The uninterrupted operation of participating nodes (also referred to as
’miners’) ensures the availability, integrity, and reliability of the
exchanged and stored data in the ’chain’ by the involved entities, who reach a
’consensus’ on the integrity of these data through consensus algorithms. These
algorithms, extensively analyzed in various studies [20], highlight their
strengths and limitations. To ensure the stability of a blockchain-based
system, each participating node contributes to the system with its resources,
including financial stake [21] or material resources such as storage [22],
computing power [23], etc. The nodes strive to comply with regulations by
adhering to pre-established policies and conditions to maintain compliance and
avoid exclusion from the network [24].
Blockchain networks have the capability to host and execute autonomous
programs, commonly referred to as ’smart contracts’ [25], which are
automatically executed when predefined conditions and terms are met.

###  III-B Data structure

As illustrated in figure 3, the design of data stored in the Blockchain is
rooted in key principles, namely:

  * •

Transaction: This pertains to the operation of adding new data to the chain.
Before this is accomplished, the transaction must be exchanged among nodes
responsible for grouping them within blocks.

  * •

Block: It is a data structure that encapsulates one or more transactions.
Generated by system nodes, the block is then broadcast across the network for
verification and validation. During each mining round, network nodes record in
their local ledgers a single block designated by a consensus algorithm, which
is subsequently added to the chain after timestamping and the inclusion of the
hash in the valid block preceding it.

  * •

Chain: This encompasses all verified and validated blocks since the system’s
inception. Known for its high availability (hosted on all network nodes) and
resistance to any modification, whether legitimate or malicious, due to the
existing linkage between blocks through their hashes.

Figure 3: Data structure in Blockchain

###  III-C Classification of Blockchain

Blockchain technologies can be classified into three categories:

  * •

Public Blockchain (Permissionless): Members seeking to integrate into the
system by viewing, submitting, or validating transactions can access it
without restrictions on their identities or the total number of system
members. The security of this system is ensured by consensus algorithms such
as Proof of Work (PoW), although their significant consumption of time and
energy poses a challenge.

  * •

Private Blockchain (Permissioned): Suited for organizations desiring complete
control over their processes, data confidentiality, and the identification of
participants in their blockchain-based system. The exclusivity of the number
of participants allows the deployment of efficient, low-energy consumption
consensus algorithms, such as Raft and PBFT. Private blockchains are
particularly appealing to financial institutions due to their governance,
efficiency in management, and audit of deployed data and processes.

  * •

Consortium or Federated Blockchain: Systems based on this type of blockchain
promote resource sharing and collaboration in complementary or similar
domains. Access to information in this system can be granted to identifiable
participants, anonymous profiles, or both. while designating a limited number
of identifiable participants playing the role of validators. These validators
contribute to increasing system scalability and reducing transaction
validation latency.

##  IV Evolution of EHR Blockchain-based systems

The design of a confidential, secure, and synchronized sharing environment for
the different components of the healthcare ecosystem poses a significant
challenge for both government authorities and healthcare providers, whether
from a legal or technical perspective. The storage, management, and transfer
of sensitive EHR information must be handled transparently, providing patients
with full control over their own data, including how it is stored, with which
providers, and with whom they wish to share it[26]. This must be done in
accordance with regulations concerning the handling of sensitive data such as
HIPAA (Health Insurance Portability and Accountability Act), GDPR (General
Data Protection Regulation), PIPL (Personal Information Protection Law), PCI
DSS (Payment Card Industry Data Security Standard), and CCPA (California
Consumer Privacy Act).
In the literature, several EHR management systems have been proposed. For
example, Arshdeep and colleagues [27] suggested a cloud-based system that
provides secure access to integrated data while ensuring data interoperability
among different stakeholders to address the issue of the lack of standards in
health data exchanges. Other systems, such as the dynamic healthcare system
based on the Cloud Computing paradigm[28], have also emerged. This system
ensures the confidentiality of patient data in a reliable, scalable, and
secure environment, based on infrastructure tailored to e-health systems.
To overcome the limitations inherent in client-server architectures,
particularly in terms of availability (to avoid single points of failure
-SPOFs-) and the reliability of stored data (to prevent possible intentional
alteration caused by malicious or unintentional attacks, such as data
corruption following a bug or database crash), several works have adopted a
blockchain-based architecture. This simultaneously addresses the ethical and
legal requirements associated with the criticality of the healthcare domain
[29], as well as the technical limitations faced by traditional client-server
computerized systems. Alam et al.[30] proposed a blockchain-based system for
recording previously collected data from IoT devices. These data are
integrated for further processing by the various authorized actors within the
system. On the other hand, MedBloc (a Blockchain-Based Secure EHR System for
Sharing and Accessing Medical Data) [31] ensures the confidentiality and
interoperability of patient data, granting them access to their medical
history and the right to grant or revoke access to their EHR. The BCES
solution (a blockchain-based eHealth system for auditable EHRs manipulation in
cloud environments), proposed by Huang et al.[32], enables the verification of
the authenticity of EHR manipulations to ensure transparent, permanent, and
verifiable traceability by any internal or external auditing entity.
Blockchain technology has also been employed in intelligent healthcare supply
chain systems[33]. The proposed approach combines the benefits of the IoT with
those of the blockchain to ensure transparent traceability of medical supplies
and products, aiming to guarantee the authenticity of products and detect
those stemming from counterfeiting.

##  V Healthcare System Management project on Blockchain

In this section, we present approaches that integrate blockchain technology
into their healthcare data management ecosystems, their architectures, and
their specificities compared to other existing approaches. The objective is
not limited to exploring the design and role of each entity but also to
conducting an evaluation based on a set of characteristics (distinctive or
common) observed in each approach. We will focus on analyzing four EHR
management approaches that have presented the necessary technical
specifications for the establishment of their architectures.

###  V-A IoT-based EHR system with Blockchain (BC)

Alam et al.[30] proposed a blockchain-based framework for IoT-EHR, where
patient health data was collected in real-time using IoT devices. The
framework also records environmental information, which is integrated with
patient data and prepared for future treatment.
The collected data are stored in a distributed manner, allowing various
stakeholders in healthcare provision to seamlessly, securely, and
transparently access, visualize, and exchange the patient’s EHR data to
prescribe appropriate treatments. As illustrated in Figure 4, the architecture
of the proposed approach consists of four layers:

  * •

IoT-based patient monitoring layer: The layer of patient sensors comprises a
diverse array of sensors aimed at capturing various patient-related data,
including but not limited to glucose levels, blood pressure, and body
temperature.

  * •

EHR layer: At this level, the sharing of specific health records is ensured
through collaboration among different healthcare entities and institutions
(healthcare organizations, hospitals, medical centers, etc.). The disparity in
EHR storage structure and its interoperability is not a challenge, as the data
are converted into a unified format via an interface before being communicated
to the blockchain layer.

  * •

User layer: Users interact with the system through a dedicated interface that
allows them to input or view records in a standardized format, regardless of
their initial storage type.

  * •

Blockchain (BC) layer: This layer implements several entities managing
authentication and verification of records, ensuring the execution of smart
contracts and consensus algorithms, guaranteeing the integrity and
immutability of local registers safeguarding patients’ EHRs, and more.

Figure 4: An overview of blockchain-based IoT-EHR framework

###  V-B MedBloc

"MedBloc"[31] refers to a secure EHR system based on a permissioned blockchain
developed by Jack Huang and his collaborators. The platform’s architecture
encompasses various entities within the healthcare ecosystem, including
patients (P), certification authorities, healthcare providers (HP),
authentication service providers, administrators, and others (Figure 5).
The design of MedBloc aims to improve data interoperability, privacy, and
security within the healthcare sector. This translates to transparent sharing
and facilitated access to health records for both patients and healthcare
providers. The system also allows patients to control access to their medical
history by granting or revoking consent to healthcare providers or other
authorized entities within the healthcare ecosystem. This approach facilitates
informed medical decision-making regarding treatments to be administered.
Digital identification and safeguarding of data encryption keys are ensured by
entities external to the traditional blockchain. The system utilizes smart
contracts to enforce access control rules, thereby preserving patients’
confidentiality and privacy.
The authors advocated for the use of nontraditional blockchain entities, such
as authentication servers and certification authorities. These entities
provide the means to issue digital identities and secure encryption keys used
to protect data on the blockchain. Finally, smart contracts are deployed to
ensure patient confidentiality via access control rules.

Figure 5: An overview of MedBloc: A blockchain-based secure EHR system

###  V-C BCES system

In their study, Huang and colleagues[32] emphasize the importance of
preserving data confidentiality during the transmission of EHRs to authorized
medical institutions and practitioners. With this goal in mind, they developed
the BCES system, a blockchain-based healthcare solution focused on preserving
the integrity and availability of EHRs. This system addresses the significant
challenge of verifying the authenticity of EHR manipulations. Within the BCES
framework, every data modification is meticulously recorded as transactions on
the blockchain, ensuring permanent traceability.
The proposed architecture (Figure 6) not only ensures data security but also
simplifies sharing among care providers by storing metadata on the Blockchain
while maintaining large amounts of multimedia data within hospital systems.
Key components of BCES include the use of a Proof-Chain mechanism to securely
store manipulation logs on the blockchain, enabling transparent tracking of
any data alterations. Additionally, the authors introduced an innovative
attribute-based proxy re-encryption method for precise control over access to
medical data. This cryptographic approach reduces the risks of unauthorized
manipulation and ensures data integrity. The implemented encryption techniques
combine two methods, attribute-based encryption and proxy re-encryption,
strengthening the resilience of the online healthcare system against any
unauthorized data modifications, thereby preserving the accuracy of medical
diagnoses.
In summary, the work of Huang et al. enriches discussions on the applications
of blockchain technology in the healthcare domain. They address regulatory
challenges and introduce auditing systems tailored to lightweight entities.
Their proposal, the BCES system, a blockchain-based healthcare solution,
caters to the verification of EHR manipulations. Their innovative approach to
blockchain technology, Proof-Chain mechanisms, and attribute-based proxy re-
encryption contributes to establishing secure and verifiable EHR management.

Figure 6: The structure of Blockchain-based eHealth system-BCES

###  V-D NAIBHSC

Blockchain technology has demonstrated its significance in various domains,
particularly in pharmaceutical and healthcare supply chains. Nanda et al.[33]
introduced a novel approach, known as NAIBHSC, integrating IoT with blockchain
in the healthcare supply chain. Its objective is to ensure the tracking of
medical product logistics and address issues related to their security,
transparency of origin, and real cost, from their source to their final
delivery to the consumer. This approach combines the advantages of Blockchain
and IoT to create an intelligent healthcare supply chain management system,
ensuring easy detection of counterfeit products, which positively impacts the
confidentiality, visibility, and trust of various stakeholders in this
decentralized system of medical products.

Figure 7: Overview of the NAIBHSC Architecture

As presented in figure 7, the NAIBHSC architecture comprises the following
elements:

  * •

IoT Devices: These devices play a crucial role in medical logistics, utilizing
sensors to monitor environmental conditions and transmit data to the
blockchain network for verification. Before shipment, products are equipped
with QR codes and sensors for continuous tracking. Sensors regularly store
recorded data, which are later verified by smart contracts. Environmental
changes detected during shipment are immediately communicated to relevant
stakeholders.

  * •

Front End: It comprises diverse user interface devices, such as mobile
devices, computers, and others, through which users engage with the back end
using a REST API and JSON interface.

  * •

Back End: It is composed of several key components :

    * –

Ethereum Blockchain network: It provides open and user-friendly services,
verifying data recorded at the front end, with smart contracts operating
within an Ethereum Blockchain virtual machine to ensure data verification and
define operations for access control. Users interact with these smart
contracts via a REST API and JSON interface, enabling the identification and
authentication of user requests, as well as the management of data access
permissions.

    * –

HTTP Server: processes requests and exchanges information on the World Wide
Web (WWW), acting as an interface between the front end and back end, storing,
processing, and delivering web pages to clients.

Additionally, the authors have highlighted experimental results indicating
that the NAIBHSC approach reduces latency, improves response time, and
enhances the overall performance of the intelligent healthcare supply chain
management system. They have also mentioned the potential of blockchain to
revolutionize the structure, planning, management, and operations of the
supply chain.

##  VI Analysis and Synthesis

We conducted a systematic comparative analysis of the previously discussed
e-health projects based on blockchain. Focusing on their essential key
characteristics, we provide a comprehensive evaluation to highlight the
specific functionalities of each approach using a detailed summary table
(Table III).

TABLE III: A comparative analysis of studied approaches | BC-based IoT-EHR | MedBloc | BCES | NAIBHSC
---|---|---|---|---
EHR logs traceability/Manipulation traceability | no | no | yes | no
External Audit Entity | no | no | yes | no
Data anonymity | - | yes | - | -
Local register Encrypted | no | yes | - | -
Nodes represent all entities | no | no | no | no
Use Smart Contract | yes | yes | no | yes
Type of storage | on-chain | on-chain | off-chain | on-chain/off-chain
Official regulatory authority | no | Certification Authority | Auditor | no

Each of the approaches listed in Table III is evaluated based on several key
criteria:

  * •

Traceability of manipulations and EHR logs: BCES is the only approach to offer
this functionality, unlike the others that do not provide it.

  * •

External Audit Entity: BC-based IoT-EHR, Medbloc, and NAIBHSC do not include
an external audit entity. In contrast, BCES ensures that manipulations can be
audited by an external entity.

  * •

Data Anonymity: Medbloc supports data anonymity, whereas the other approaches
do not specify whether they support this feature or not.

  * •

Encrypted Local Register: BC-based IoT-EHR stores data encrypted in a local
register, whereas for the other approaches, this feature is either not
specified or not considered.

  * •

Representation of all System Entities: no approach includes all entities of
its system as a node in the established blockchain network.

  * •

Use of Smart Contracts: Among the proposed systems, only BCES does not employ
smart contracts. It is noteworthy that while the described approaches
intentionally avoid specifying the programming language for smart contracts,
only NAIBHSC explicitly mentions the use of the Solidity language. The authors
of these approaches focused on detailing smart contract logic and algorithms
without restricting them to a particular language, thereby allowing
flexibility in implementation.

  * •

Storage Type: BC-based IoT-EHR and Medbloc store data on-chain. The BCES
stores data off-chain. However, the storage type adopted by NAIBHSC is hybrid,
storing data both on-chain and off-chain.

  * •

Official Regulatory Authority as an Entity: BC-based IoT-EHR and NAIBHSC do
not include an official regulatory authority as an entity. In contrast,
MedBloc specifies the presence of an authority issuing certificates considered
identifiers for the participants of the blockchain network, although the
official nature of this regulatory entity is not specified. The same
observation applies to BCES, which foresees the existence of an auditor
allowing the detection of any malicious behavior without specifying the
official regulatory authority.

After highlighting the significant differences between the four approaches, we
note that for each proposed approach, external actors play primary or
secondary roles in the system’s operation, without being represented as a node
in the blockchain network. Despite the fact that blockchain technology relies
on data verification through consensus and shared trust, all system entities
(or at least the main entities) cannot participate, as a node, in data
validation and therefore contribute to the good governance of the entire
ecosystem. This increased dependence on external entities could limit the
potential benefits offered by blockchain in a crucial field such as e-health.
However, this choice may be motivated by various reasons and challenges that
any future approach must consider in the context of e-health. The priority
given to a high level of security and confidentiality of electronic patient
data, as well as the simplification of the structure and functioning of the
blockchain with existing systems, whether internal or external, may have
influenced this decision, as highlighted by the Digital Development Agency
(ADD) in its proposal [26] to use the Blockchain as a secure digital safe for
medical data while preserving the current system of each actor involved in
patient care, along with its architecture. It is also essential to ensure
strong interoperability regarding the technology used and the structure of the
exchanged data.
Furthermore, the absence of integration of an official regulatory authority
within the framework of the studied approaches raises questions. It is worth
emphasizing that the integration of an official regulatory authority does not
necessarily imply a central authority with absolute power and control. In
contrast, a regulatory authority aimed at ensuring adherence to ethical and
legal standards could be deployed as an entity represented by at least one
node in the network. This authority would have access to various data enabling
it to monitor any fraud related to the breach of patient data or falsification
of medical records for the purpose of gaining advantage with insurers. This
integration also aims to detect any inconsistencies or unlawful collusion
among different actors, such as clinics and insurers. Among the practices to
be monitored are the unjustified changes in medical service fees, the
generation of fictitious invoices, and insurance reimbursements showing
inappropriate amounts or frequency. The issue of confidentiality does not
arise, as this regulatory authority, potentially governmental or
institutional, will have the legal right to access the various information
stored in the blockchain. This will be regulated by law or by the explicit
consent of the patients themselves.
The issue of data interoperability among diverse healthcare platforms and
systems is compounded by significant challenges in regulatory flexibility,
given the health regulations and jurisdictions associated with the storage,
processing, and transfer of sensitive patient data, which vary from one
country to another. This situation requires adaptation to the different
national regulations of each country as well as international standards.

##  VII Conclusion

The structural and architectural choice of any future e-health system based on
blockchain depends on the specific design and objectives of the system. Each
requirement may present unique demands in terms of regulatory compliance,
security, interoperability, confidentiality, and performance, thereby
influencing the implementation and management of the entities within the
system.
In this article, we specifically examined certain blockchain-based approaches,
representing common and individual characteristics related to the context of
e-health, including the health supply chain, IoT, and other related areas.
The results of our analysis have highlighted the strengths and weaknesses of
each approach, emphasizing the importance of various key functionalities in
the context of EHR management and the integration of Blockchain technology in
this management. However, we have underscored the existence of crucial
challenges for effective implementation, necessitating close collaboration
among regulators, healthcare stakeholders, and technology developers. These
challenges notably include the inadequate representation of key entities in
the blockchain network, facilitated by the increasing dependence on external
systems, which can compromise effective governance, confidentiality, and data
security for patients. We have also emphasized that the appropriate
integration of an official regulatory authority is essential to ensure
compliance with ethical and legal standards while preserving the decentralized
nature of the blockchain. Regulatory flexibility must also be considered to
ensure compliance with the jurisdiction of each country using these systems,
as well as to guarantee the compliance and interoperability of this system and
its data on a global scale.

## References

  * [1] R. Cerchione, P. Centobelli, E. Riccio, S. Abbate, and E. Oropallo, “Blockchain’s coming to hospital to digitalize healthcare services: Designing a distributed electronic health record ecosystem,” _Technovation_ , vol. 120, p. 102480, 2023.
  * [2] Thomson Reuters, “Ransomware attacks against healthcare organizations nearly doubled in 2021, report says,” https://www.thomsonreuters.com/en-us/posts/investigation-fraud-and-risk/ransomware-attacks-against-healthcare, 2022, visited 2023-10-25.
  * [3] Check Point Research, “Global cyberattacks continue to rise with africa and apac suffering most,” https://blog.checkpoint.com/research/global-cyberattacks-continue-to-rise/, 2023, visited 2023-10-25.
  * [4] V. Rai, K. Bagoria, K. Mehta, V. M. Sood, K. Gupta, L. Sharma, and M. Chauhan, “Cloud computing in healthcare industries: Opportunities and challenges,” _Recent Innovations in Computing: Proceedings of ICRIC 2021, Volume 2_ , pp. 695–707, 2022.
  * [5] M. Madejczyk, T. Trejderowski, and B. Trejderowska, “Protection of personal data using blockchain,” _Zeszyty Naukowe Wyższej Szkoły Technicznej w Katowicach_ , vol. 14, 2022.
  * [6] J. L. Habib, “Ehrs, meaningful use, and a model emr,” 2010.
  * [7] U. Padmavathi and N. Rajagopalan, “Concept of blockchain technology and its emergence,” in _Research Anthology on Convergence of Blockchain, Internet of Things, and Security_. IGI global, 2023, pp. 21–36.
  * [8] Y.-S. Ren, C.-Q. Ma, X.-Q. Chen, Y.-T. Lei, and Y.-R. Wang, “Sustainable finance and blockchain: A systematic review and research agenda,” _Research in International Business and Finance_ , p. 101871, 2023.
  * [9] M. Zouina and B. Outtai, “Towards a distributed token based payment system using blockchain technology,” in _2019 International Conference on Advanced Communication Technologies and Networking (CommNet)_. IEEE, 2019, pp. 1–10.
  * [10] A. Yazdinejad, A. Dehghantanha, R. M. Parizi, G. Srivastava, and H. Karimipour, “Secure intelligent fuzzy blockchain framework: Effective threat detection in iot networks,” _Computers in Industry_ , vol. 144, p. 103801, 2023.
  * [11] G. Al-Sumaidaee, R. Alkhudary, Z. Zilic, and A. Swidan, “Performance analysis of a private blockchain network built on hyperledger fabric for healthcare,” _Information Processing & Management_, vol. 60, no. 2, p. 103160, 2023.
  * [12] Y. Hao, P. Helo, N. Tsoniotis, and R. Toshev, “Blockchain-based supply chain system in automotive industry forsmall-and medium-sized manufacturing,” in _Blockchain Driven Supply Chains and Enterprise Information Systems_. Springer, 2023, pp. 151–171.
  * [13] A. Ouaguid, F. Fathi, M. Zouina, M. Ouzzif, and N. Abghour, “Androscanreg 2.0: Enhancement of android applications analysis in a flexible blockchain environment,” _International Journal of Software Innovation (IJSI)_ , vol. 10, no. 1, pp. 1–28, 2022.
  * [14] M. A. Amallah, N. Abghour, K. Moussaid, A. El Omri, and M. Rida, “Review on blockchain and access control systems,” in _Advances on Smart and Soft Computing: Proceedings of ICACIn 2021_. Springer, 2021, pp. 235–246.
  * [15] M. Abirou and N. Abghour, “A review of blockchain and the benefits for digital marketing-related applications of blockchain integration,” _Advances on Smart and Soft Computing: Proceedings of ICACIn 2021_ , pp. 355–365, 2022.
  * [16] B. Bellaj, A. Ouaddah, E. Bertin, N. Crespi, A. Mezrioui, and K. Bellaj, “Btrust: A new blockchain-based trust management protocol for resource sharing,” _Journal of Network and Systems Management_ , vol. 30, no. 4, p. 64, 2022.
  * [17] M. Bidry, A. Ouaguid, and M. Hanine, “Enhancing e-learning with blockchain: Characteristics, projects, and emerging trends,” _Future Internet_ , vol. 15, no. 9, p. 293, 2023.
  * [18] J. You, “Curvetime: A blockchain framework for artificial intelligence computation,” _Software Impacts_ , vol. 13, p. 100314, 2022.
  * [19] N. El Akrami, M. Hanine, E. S. Flores, D. G. Aray, and I. Ashraf, “Unleashing the potential of blockchain and machine learning: Insights and emerging trends from bibliometric analysis,” _IEEE Access_ , 2023.
  * [20] H. Xiong, M. Chen, C. Wu, Y. Zhao, and W. Yi, “Research on progress of blockchain consensus algorithm: A review on recent progress of blockchain consensus algorithms,” _Future Internet_ , vol. 14, no. 2, p. 47, 2022.
  * [21] S. King and S. Nadal, “Ppcoin: Peer-to-peer crypto-currency with proof-of-stake,” _self-published paper, August_ , vol. 19, p. 1, 2012.
  * [22] S. Dziembowski, S. Faust, V. Kolmogorov, and K. Pietrzak, “Proofs of space,” in _Annual Cryptology Conference_. Springer, 2015, pp. 585–605.
  * [23] S. Nakamoto, “Bitcoin: A peer-to-peer electronic cash system,” _Decentralized business review_ , 2008.
  * [24] A. Ouaguid, N. Abghour, and M. Ouzzif, “Node security metric: Proof of conformity blockchain consensus protocol,” in _International Conference on Advanced Intelligent Systems for Sustainable Development_. Springer, 2020, pp. 665–682.
  * [25] V. Buterin _et al._ , “A next-generation smart contract and decentralized application platform,” _white paper_ , vol. 3, no. 37, pp. 2–1, 2014.
  * [26] D. Anass, E. A. Hicham, Y. Azeddine, C. Saad, and A. Smail, “White paper on e-health in morocco: Realities, challenges and development levers,” _white paper_ , 2022.
  * [27] A. Bahga and V. K. Madisetti, “A cloud-based approach for interoperable electronic health records (ehrs),” _IEEE Journal of Biomedical and Health Informatics_ , vol. 17, no. 5, pp. 894–906, 2013.
  * [28] S. S. Vellela, B. V. Reddy, K. K. Chaitanya, and M. V. Rao, “An integrated approach to improve e-healthcare system using dynamic cloud computing platform,” in _2023 5th International Conference on Smart Systems and Inventive Technology (ICSSIT)_. IEEE, 2023, pp. 776–782.
  * [29] A. S. Makinde, A. O. Agbeyangi, and S. Omaji, “Integration of blockchain into medical data security: Key features, use cases, technical challenges, and future directions,” in _Contemporary Applications of Data Fusion for Advanced Healthcare Informatics_. IGI Global, 2023, pp. 137–165.
  * [30] S. Alam, S. Bhatia, M. Shuaib, M. M. Khubrani, F. Alfayez, A. A. Malibari, and S. Ahmad, “An overview of blockchain and iot integration for secure and reliable health records monitoring,” _Sustainability_ , vol. 15, no. 7, p. 5660, 2023.
  * [31] J. Huang, Y. W. Qi, M. R. Asghar, A. Meads, and Y.-C. Tu, “Medbloc: A blockchain-based secure ehr system for sharing and accessing medical data,” in _2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)_. IEEE, 2019, pp. 594–601.
  * [32] H. Huang, X. Sun, F. Xiao, P. Zhu, and W. Wang, “Blockchain-based ehealth system for auditable ehrs manipulation in cloud environments,” _Journal of Parallel and Distributed Computing_ , vol. 148, pp. 46–57, 2021.
  * [33] S. K. Nanda, S. K. Panda, and M. Dash, “Medical supply chain integrated with blockchain and iot to track the logistics of medical products,” _Multimedia Tools and Applications_ , pp. 1–23, 2023.