# ESPORT: Electronic Sports Professionals Observations and Reflections on
Training

Andrzej Białecki*, Warsaw University of Technology  Peter Xenopoulos
Independent Researcher  Paweł Dobrowolski Institute of Psychology, Polish
Academy of Sciences  Robert Białecki Józef Piłsudski Warsaw University of
Physical Education  Jan Gajewski Józef Piłsudski Warsaw University of Physical
Education

###### Abstract

Esports and high performance human-computer interaction are on the forefront
of applying new hardware and software technologies in practice. Despite that,
there is a paucity of research on how semi-professional and professional
championship level players approach aspects of their preparation.

To address that, we have performed, transcribed, and analyzed interviews with
top-tournament players, coaches, and managers across multiple game titles. The
interviews range from competitive events occuring between 2015-2020. Initial
processing included transcription and manual verification. The pre-processed
interview data were then organized and structured into relevant categories,
touching on psychological, physical, and nutritional aspects of esports
preparation. Further, where applicable, interview responses where rated and
quantified via consensus judgement by a panel of experts.

The results indicate that physical training was most often mentioned as a
relevant or consistent activity, while nutrition was indicated as relatively
unimportant. Qualitative analysis also indicated that consistency and
resiliency were noted as the most key factors recommended for upcoming esports
competitors. It is also clear that many players put emphasis on balancing
their gameplay time and with activities. Lastly, we identified important areas
of inquiry towards a deeper understanding of the mental and physical demands
of professional esports players.

††* Corresponding author<EMAIL_ADDRESS>Institutional
contact<EMAIL_ADDRESS>
_Keywords_ esport $\cdot$ training $\cdot$ physical activity $\cdot$
psychology $\cdot$ nutrition

##  1 Introduction

Esports can be viewed as a subset of gaming that leverages simulated
environments to define the competition space. There are numerous efforts in
the research community to preciesely define its role in the sports landscape.
This includes efforts towards a more precise definition of esports [1, 2, 3].
The largest esports tournaments routinely attract millions of concurrent
viewers and award millions of dollars in prizes. Thus, esports is comparable
in interest with popular conventional sports and is a largely global
phenomenon, with tournaments held year-round on every continent [4, 5]. Such
strong growth has spawned not only a burgeoning esports industry, but also a
plethora of interdisciplinary research, detailing the intersection of esports
with law [6], health [7, 8, 9], and media studies [10, 11, 12]. In particular,
much esports-focused work fits well within the domain of human-computer
interaction, given the mechanism by which many esports function [13]. The
prominent use of hardware and software in esports means that research in this
area could be attributed to human-computer interaction (HCI) [14]. It is
common to see reports on technological advancements in the area of gaming
peripherals, some teams sell their own branded hardware yet their influence in
the design process is unknown.

There are no limits to use of customized pointing devices in most if not all
of esports, including adaptive hardware [15]. Players often tinker with their
equipment, personalizing it to fit their requirements for comfortable play. We
show such customized hardware on Figure 1. Ergonomy and ease of use of
hardware and software is a known area in esports. There are multiple ways to
position the mouse and keyboard, and different types of mouse grips that
players are used to. Other known issue in this space concerns the latency in
multiplayer competition, and potential software inconsistencies [16].

Figure 1: Examples of equipment customized by professional esports players
(Source Mikołaj “Elazer” Ogonowski). Notice and finger wear marks and taped
buttons.

Esports encompasses a large community, including players of all skill levels,
fans, and commentators "casters", and has provided intriguing directions for
HCI [17]. This includes cognitive and mental health in esports [18, 9, 19] and
visualization systems for esports [20, 21, 22, 23, 24, 25]. Additionally,
computer games offer unique opportunities for cognitive research on
neuroplasticity [26], and in their richness of stimuli can be compared to how
biofeedback facilitates skill acquisition [27]. Despite the large-scale
community and growing interest that esports provides, there has been little
work directed towards the long tail of the distribution of player skill -
namely, highly skilled and professional esports players. These players provide
a unique unit of study in that their skill often warrants distinct mental,
cognitive, and physical demands. At the same time, sports science has
repeatedly investigated the aforementioned characteristics for professionals
in other sports [28, 29, 30], yet this seems to be limited for the esports
domain despite its cognitive nature. Furthermore, many esports are remarkably
different from conventional sports, given their online nature and that they
often mandate a sedentary style of play, thus making it challenging to
extrapolate conclusions from conventional sports. Existing systematic reviews
and meta analyses point towards the need of further research in esports [31,
32]. This includes research on physical activity in esports [33]. In this
paper, we aim to bridge this gap by focusing on highly-skilled esports
players.

Despite growing academic interest in esports, esports curricula, and high
performance human-computer interaction, there seems to be a lack of
information regarding the needs of esports athletes from first hand sources.
Accordingly, we apply both qualitative and quantitative analysis of interviews
with esports professionals to investigate their approach in three major
categories of physical activity, psychological factors in esports, and
nutrition. Uniquely, we draw upon a curated dataset of a highly-skilled subset
of players representing the top end of esports players, many of which have
longstanding fanbases or storied careers. These interviews were gathered by
visiting major esports tournaments such as Intel Extreme Masters Katowice.

The goal of our work is to highlight the perspective of professional esports
staff on various aspects of the training process, including some of the top
players in the world in different games. We have formulated the following main
research questions to facilitate our approach towards our goal:

  * RQ 1:

What is the players’ attitude towards physical activity, nutrition, and
psychology?

  * RQ 2:

Do players have access to support staff that takes care of physical activity,
nutrition, and psychology?

  * RQ 3:

What is the perceived path to becoming an esports player?

##  2 Related Work

Similar to our attempt here, a few other works have employed interview-based
investigations. This includes research on coaching practices and issues; one
such study focused on two main categories in a qualitative manner, namely
general esports coaching information and challanges in League of Legends (LoL)
esports. The findings of this study emphasized different coaching
philosophies, ideas of trust, synergy, micro play, macro play, and other
psychological components that were perceived as key in a well-functioning team
environment [34].

On the other hand, it is not only coaches who create the team environment.
Some investigations focused on the player-perceived determinants of success,
mostly in the area of psychology through thematic analysis [35]. Furthermore,
other authors attempted to quantify the amount of physical activity, and in-
game training. They have found that press overexaggerated the training time to
be within 12 to 14 hours a day, while the players indicated on average 5.28
hours per day [36]. Other researchers performed 12 interviews with with 11
professional Overwatch esports players performing a themathic analysis on
game-sense and mechanics. They have concluded that important aspects are
knowledge of ally and enemy positioning, and timing [37]. Similar to our
approach there also exists an article on perceptions of effective training in
esports, although it focused on League of Legends practitioners. Authors split
interview gathered data into 3 themes: the state of training, training
experiences, and motivational change. Results indicated that the training
approaches and motivation can shift. Within the results, it was pointed out
that players often perceive their training practices as sub-optimal.
Additionally authors highlighted the emotional and physical toll on the
players. This is due to the extensive hours of gameplay in sedentary position
to improve ones ability (“grinding”) [38].

A Scoping Review on associations between esports participation and health
habits uncovered that most of the players 65%-88.7% indicated regular exercise
habits and indicated relative novelty of the esports research area [39].
Additionally, though different from our attempt, there exist interview based
investigations on how esports athletes perceive performance-enhancing
substances (doping) [40].

##  3 Material and Methods

###  3.1 Interview Collection

We collected interviews with esport athletes, coaches, and managers ranging
from semi-professional to professional. All of the interviews were collected
in a form of audio-visual recordings in English (22 interviews) or in Polish
(17 interviews), the total number of interviews split by the interviewee type
is availabile in Table 1. Collection of the interviews took place during
events such as  (1) ESL One Cologne 2015,  (2) ESL One Frankfurt 2015,  (3)
IEM Katowice 2016, 2017, 2018, 2019  (4) ESL Polish Championships 2017,  (5)
WGL EU Season 2 Qualifier 2017,  (6) MeetPoint 2018,  (7) ESL One Katowice
2019.

All of the interviews were published online or recorded for further broadcast
in cable television. Interviewees played, or were related to games such as
League of Legends (LoL), StarCraft 2 (SC2), Heroes of the Storm (HoTS),
Counter-Strike: Global Offensive (CS:GO), World of Tanks (WoT), Dota 2, and
the Business side of esports.

The interviews were originally recorded from 2015 up until 2020 and span
multiple game genres and esports titles. We used a total of 39 interviews. The
total number of questions asked per type of the interviewee is described in
Table 1.

Table 1: Interview count breakdown 2015–2020 type | interviews | total questions
---|---|---
player | 28 | 296
coach (in-game) | 2 | 20
coach (performance) | 1 | 11
manager | 7 | 63
commentator | 1 | 6
total | 39 | 396

###  3.2 Data Pre-Processing

The interviews were initially processed with OpenAI Whisper, which provides
automatic video to text transcription [41]. In the case of Polish recordings,
transcription was performed with the automatic translation feature. Next, all
transcriptions were manually verified by a bilingual native English speaker,
and split between questions and answers. Full interviews transcriptions are
available as a supplemental file.

###  3.3 Data Processing

Pre-processed interviews were placed in a spreadsheet format. Each of the
categories for questions and answers was coded as a column. Aside from the
main topics, interviewees also often provided additional information in a
free-form manner - an attempt was made to categorize these responses as well:
(1) physical activity,  (2) psychology,  (3) science,  (4) coaching,  (5) in-
game training,  (6) nutrition,  (7) sociology.

Next, four out of five authors as expert judges, separately grading the
extracted abstract questions to alleviate possible biases towards contextual
information. The judges were tasked with assigning a numerical value to each
of the coupled question-answer contexts. Possible values were binary (either 0
- No, 1 - Yes, and additionally 2 - No Information) or Likert scale (1 -
Strongly Disagree, 2 - Disagree, 3 - Neutral, 4 - Agree, 5 - Strongly Agree).
The interview environment made it possible for the interviewer to ask multiple
questions pertaining to the same topic. In the case when a similar question
was asked after the initial question-answer context, such questions were
judged separately and an average answer was calculated per interview.

###  3.4 Post-processing

After each of the referees provided their final graded sheet, further
processing and numerical analyses were performed. Corresponding to the
categories presented in Data Processing, coding of the analyzed inteview
questions is as follows: QA - physical activity, QP - psychology, QN -
nutrition, QT - in-game training. Note that not all of the categories could be
represented numerically for the quantitative analysis.

  * QA_0:

(likert) - Is physical activity important for players?

  * QA_1:

(binary) - Do you train physically?

  * QA_2:

(binary) - Do you work with a fitness coach?

  * QP_0:

(likert) - Is psychology important for players?

  * QP_1:

(binary) - Do you have a psychologist supporting you?

  * QN_0:

(likert) - Is nutrition important for players?

  * QN_1:

(binary) - Do you have a nutritionist supporting you?

  * QN_2:

(binary) - Do you have a meal plan?

  * QT_0:

(binary) - Do you make changes to your training before a tournament?

  * QT_1:

(estimated time in hours) - How much time do you spend training in-game before
a tournament?

  * QS_0:

(likert) - How do you rate the atmosphere of the current tournament?

##  4 Results

###  4.1 Quantitative Analysis

####  4.1.1 Physical Activity

Aggregated referee responses are visualized in Figure 2. Visual investigation
of the plots indicates that when asked about their approach towards physical
activity - 2(c), the majority of interviewees stated that they Agree or
Strongly Agree that it can positively influence their gameplay. Additionally,
most of the players - 2(a), indicated that they train physically. On the other
hand - 2(b), when asked about the external support from a professional fitness
coach, they typically indicated not having such support at the time.

(a) Choice frequency for “Do you train physically?”.

(b) Choice frequency for “Do you work with a fitness coach?”.

(c) Choice frequency for “Is physical activity important for players?”.

Figure 2: Visualization for all coded questions related to physical activity.

####  4.1.2 Psychology

When asked about psychological aspects - Figure 3, the majority of the
interviewees agreed that it can be important for success in esports 3(b). On
the other hand, when asked if they have access to a professional psychological
support, most players responded negatively - 3(a).

(a) Choice frequency for “Do you have a psychologist supporting you?”.

(b) Choice frequency for “Is psychology important for players?”.

Figure 3: Visualization for all coded questions related to psychology.

####  4.1.3 Nutrition

While discussing nutrition and its possible influence on esports performance -
Figure 4, players indicated that they either Agree or Strongly Agree with the
premise of nutrition being important for their performance - 4(c). Despite
these statements, most of the players indicated that they do not follow any
meal plan and do not consult with a professional nutritionist, as can be seen
in 4(a) and 4(b)

(a) Choice frequency for “Do you have a nutritionist supporting you?”.

(b) Choice frequency for “Do you have a meal plan?”.

(c) Choice frequency for “Is nutrition important for players?”.

Figure 4: Visualization for all coded questions related to nutrition.

####  4.1.4 Response Comparison

To compare the perceived responses between different coded question
categories, we have conducted a Mann-Whitney U test for all of the likert
scale questions. The results of the test are presented in Table 2.

Table 2: Results of Mann-Whitney U test for likert scale coded questions. question | QA_0 | QP_0 | QN_0
---|---|---|---
u-stat | p value | u-stat | p-value | u-stat | p-value
QA_0 | – |  |  |  |
QP_0 | 379.0 | 0.207 | – |  |
QN_0 | 292.5 | 0.318 | 297.5 | 0.948 | –

Based on these results we conclude that all of the questions were answered
similarly indicating that esports professionals have positive attitude towards
the statement that either physical activity, psychology, or nutrition is
important to their performance.

####  4.1.5 In-Game Training

When asked about the in-game training characteristis, interviewees indicated
that they do change how they train when in preparation for a tournament -
Figure 5. Majority of the respondents indicated average training time between
7 and 9 hours being most prevalent.

(a) Choice frequency for “Do you make changes to your training before a
tournament?”.

(b) Choice frequency for “How much time do you spend training in-game before a
tournament?”.

Figure 5: Visualization for all coded questions related to psychology.

###  4.2 Tournament Atmosphere

When asked about the tournament atmosphere (n=18), i.e. “How do you rate the
atmosphere of the current tournament?”, the majority of the players indicated
that they strongly agree with the statement (n=8), others (n=6) stated that
they agree, and finally (n=4) provided neutral statements.

###  4.3 Qualitative Analysis

As discussed in subsection 3.4, not all questions could be represented
numerically, and yet key information was provided in their context.

####  4.3.1 Recommendations for Aspiring Players

When asked about what are their recommendations for the younger players that
would like to try and become professional, interviewee 16 stated:

> Like I said before, just practice, practice, practice, that’s all it really
> comes down to and just having a good mindset. Those are the two main things
> I’d definitely say, yeah.

In this statement the player underlined the idea of practice and having the
right mindset. Interviewee 17 stated:

> I’d say I was doing the basics. I was not doing more than I could have done.
> I was just working enough to graduate, not to do more. So I’d say it’s up to
> everyone, every each person to study as much as they want or so. Maybe some
> people are not going to school to play. I was doing that sometimes but
> that’s not what you should do obviously. It’s up to everyone to work as much
> as you want and then to try to play outside from the school hours.

Which emphasized that aspiring players should play as much as possible outside
of other responsibilities. This is in line with what interviewee 20 stated:

> You know what, it depends on who is at home (the environment). When parents
> are always going to put pressure on formal education, and they won’t let
> their son (child) fullfill themselves in e-gaming (gaming, esports), it will
> be a very difficult path, but you have to go through it and be persistent,
> persistent, persistent. Do not give up. After two or three years, if you
> want to become a professional player, sooner or later you can make it but it
> is very hard.

Which underlined the importance of environmental factors as well as being
persistent as key indicators that play a role in esports success. Similarly,
interviewee 29 stated:

> It’s just keep working, you should just finish school, you can play when you
> get home and with your team in the evening, it’s more like the social life
> you sacrifice because you have work, you have school, some things you just
> have to do if you don’t succeed and that’s just the fact and just keep
> trying and go forward but don’t go all in if you know what I mean …

Which additionally mentions not to sacrifice everything for the sake of an
esports career. On top of that, interviewee 31 stated:

> I feel like you have to really work hard. I think there’s a lot of people in
> the space that are really, really good at video games, but to get to a
> professional level, I think the biggest thing is stopping people is
> themselves, and you can be really good, but to become a professional is you
> need to be able to take criticisms, be able to send maybe your match demo to
> somebody and be like, hey, where did I mess up, and be willing to listen to
> that. You’re not like, oh, this guy’s an idiot, he doesn’t understand, or
> whatever, you have to be able to take criticisms from your peers, from the
> fans, from your teammates, and I think that’s kind of the difference between
> a professional and a really good player is how serious they’re willing to
> take themselves and how much time they’re willing to put into it. So in
> terms of tools, I think there is definitely tools out there that can help
> players grow, but in my personal opinion, your biggest enemy is yourself.

Putting emphasis on the psychological and communication factors playing a role
in the success in esports. Furthermore, interviewee 39 stated:

> There is no secret if you’re good, you’re gonna get seen and and you need
> you know a bit of luck. Plus being very good. So It is just a matter of,
> Yeah, making things happen just show yourself as much as possible. And if
> you’re very good, you’re gonna get seen and you’re gonna climb up the ladder
> in a way and and yeah work hard

All of the interviewees providing recommendations for aspiring esports players
indicated hard work, persistence, or environmental factors coupled with luck
as key indicators for success in esports.

####  4.3.2 Tools and Esports Science

When asked about the availability of tools, and current state of educational
and scientifically applicable information, interviewee 12 stated:

> Difficult question. I’ve never looked for any advice (tutorials) on how to
> train in esport. I’ve watched some videos, as Piotr said, from Virtus.pro,
> how they prepare, how they train. Of course, it’s about the Counter-Strike
> team, but the influence of science… Personally I’ve not taken any scientific
> advice from articles, bachelor, or some master thesis on this topic.

And later provided more context with:

> Yes, for sure there are some statistics about how an average player from top
> teams spens their time in training. Maybe even on how they eat, or if they
> do something besides that. So surely some statistics could show that
> something out there works and helps in these preparations (training). But as
> I said, I’ve never looked for any statistics, I’ve never supported myself in
> this way, or looked for any advice.

At the same time indicating that the statistics are important in discovering
weaknesses in gameplay:

> Yes, we do. We take care of statistics, mainly percentage of wins of teams
> from different leagues, from different maps, and on different sides of the
> map. But I don’t think it changes… If we are weak in the map, we train it or
> we think that we don’t want to play this map and we always ban it. But
> specific preparation outside of the game and on a specific map, we don’t do
> that. There is no such thing that we have to focus more on the days when we
> play with these opponents. There isn’t anything like that.

On the other hand when a performacne coach (interviewee 15) of one of the
teams was asked about the availability of the tools, these were his
statements:

> I mean, mainly there are websites that collect the data and statistics,
> there are some software tools that are paid, and unfortunately they cost a
> lot. We try to use them. I think that there is no dedicated tool, you just
> got to know what you want to verify, what works and what doesn’t.
> Additionally, the tools for physical training are mostly available online.
> If it is tools for stretching, the balls for massaging the muscles? And in
> the game, well, it’s a computer. I do not see any other essential tools.

##  5 Limitations

It should be noted that the interviews were conducted in a short form, in a
fast paced tournament environment. Therefore, there was no way of coduncting a
full in-depth analysis with existing sociological methodologies. Moreover, as
mentioned in the Interview Collection section, the data was collected from
2016 through 2019 and in the everchanging esports landscape these represent
only a very limited sample of top tournament players, coaches, and managers.
Despite that, we think that our work offers a unique snapshot of the state of
top-level esports at the time of data gathering. Additionally, as opinions may
of course change over time, we cannot verify if the interviewees still hold
the same stance on the investigated topics.

##  6 Summary

Despite some of the players indicating that physical activity is not relevant
in esports, there are results that contradict such anecdotal experience.
Breaking prolonged sitting with a six minute walk has shown to improve the
executive functioning of players [42]. Further, the widespread consensus on
physical activity is that it is a positive stimulus for human cognitive
performance [43, 44]. Yet it is unclear what the optimal training load and
intensity are to facilitate positive effects on in-game performance. This
includes potential scheduling issues, as e.g. intense physical training just
prior to high levels of mental activity may even be detrimental to
performance.

Spitzer et al. [45] suggest a theoretical aproach for the possibility of
knowledge transfer by AI systems. Learning in new environments may include
acquiring "tacit" knowledge, which is hard to express by available language
but could be captured in data. On the other hand, as the esport research field
progresses this knowledge should be documented, verified, and applied to
future esport players and conventional sports.

###  6.1 Future Research

We recommend further research into the broad area of esports to answer the
following questions:  (1) What should be the load and intensity of physical
activity training to significantly boost the performance of esports players?
(2) How to structure esports training so that it can fit physical activity in
a non-invasive way?  (3) What should be the methodical structure of training
and practice in esports to maximize human performance?  (4) What are the
currently available training tools to manage training load and intensity?  (5)
Is it possible to use online and offline AI systems in esports training
effectively?

##  7 Conclusions

Given our results from the quantitative analyses, we have concluded that most
of the players and esports staff were aware of the potential positive effects
of physical activity, psychology, and nutrition (RQ 1). Additionally, a higher
percentage of interviewees indicated that they strongly agree with physical
activity being important, than for the nutrition or psychology. Despite the
high-profile of the interviewees, it is clear the they had limited access to
support staff to take care of these aspects for them (RQ 2). On the other
hand, 36% of the respondents indicated that they have access to a psychologist
which compared other questions: fitness coach - 20%, or a nutritionist - 13%.
Juxtaposing these claims with the 70% of interviewees stating that they train
physically, and only 18.2% following a meal plan we conclude that physical
activity and psychological aspects are of key importance to players.

Based on the players recommendations (RQ 3), we conclude that the best way for
the aspiring players to reach their goals in esports is to be persistent, hard
working, and not sacrifice other areas of life if possible. This points
towards a holistic view of esports represented by the top-level athletes.
Additionally, respondents indicated that they use statistical software to
track gameplay weaknesses, and look for various educational materials on how
to play better.

## Acknowledgements

We would like to acknowledge various contributions by the members of the
community, namely: Oliwia Kamińska, Konrad Daroch, Kacper Zyzak, and others
that helped in the interview collection process.

### Authors’ contributions

  * •

Conceptualization: Andrzej Białecki;

  * •

Supervision: Andrzej Białecki, Jan Gajewski;

  * •

Methodology: Andrzej Białecki, Paweł Dobrowolski;

  * •

Investigation: Andrzej Białecki, Peter Xenopoulos, Paweł Dobrowolski, Robert
Białecki, Jan Gajewski;

  * •

Writing - original draft: Andrzej Białecki, Peter Xenopoulos;

  * •

Writing - review and editing: Andrzej Białecki, Paweł Dobrowolski, Robert
Białecki;

  * •

Technical Oversight: Andrzej Białecki;

  * •

Experiments: Andrzej Białecki;

## Declarations

Authors declare no conflict of interest.

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11institutetext: Walter Sisulu University, Buffalo City South Africa, 11email:
<EMAIL_ADDRESS>
# Blockchain in Healthcare: Implementing Hyperledger Fabric for Electronic
Health Records at Frere Provincial Hospital

Olukayode Ayodele Oki 11 0000-0002-6887-9782
Abayomi O. Agbeyangi 11 0000-0002-2504-2042
Aphelele Mgidi 11 0000-0002-1085-6465

###### Abstract

As healthcare systems worldwide continue to grapple with the challenges of
interoperability, data security, and accessibility, integrating emerging
technologies becomes imperative. This paper investigates the implementation of
blockchain technology, specifically Hyperledger Fabric, for Electronic Health
Records (EHR) management at Frere Hospital in the Eastern Cape province of
South Africa. The paper examines the benefits and challenges of integrating
blockchain into healthcare information systems. Hyperledger Fabric’s modular
architecture is harnessed to create a secure, transparent, and decentralized
platform for storing, managing, and sharing EHRs among stakeholders. The study
used a mixed-methods approach, integrating case studies and data collection
methods through observation and informal questions, with the specific goal of
understanding current record management methods and challenges. This method
offers practical insights and validates the approach. The result demonstrates
the role of blockchain in transforming healthcare, framed within a rigorous
exploration and analysis. The findings of this study have broader implications
for healthcare institutions seeking advanced solutions to address the
persistent challenges in electronic health record management. Ultimately, the
research underscores the transformative potential of blockchain technology in
healthcare settings, fostering trust, security, and efficiency in the
management of sensitive patient data.

###### Keywords:

Blockchain E-Health Hyperledger Fabric Electronic Health Records.

##  1 Introduction

Blockchain technology has expanded beyond its original connection with
financial technology and is now making its way into different areas, such as
healthcare [1, 2]. Blockchain is recognised for its ability to disrupt banking
institutions and its close association with cryptocurrencies. It is now being
seen as a promising way to improve data security, transparency, and
interoperability in healthcare environments [3]. Initially, cryptocurrencies
like Bitcoin relied on blockchain as their foundational technology. It
functions as a decentralised and unchangeable system of record-keeping. By
utilising cryptographic techniques, it ensures transparency, security, and
tamper-resistance when storing transactions or data records across a dispersed
network of nodes. According to Tseng and Shang [4], it removes the necessity
for intermediaries seen in conventional centralised databases, enabling direct
transactions between peers while preserving the integrity of data.

Managing electronic health records (EHR) in the traditional healthcare system
encounters notable hurdles such as data security risks, interoperability
problems, and administrative inefficiencies. The problems impact patient
privacy, impede smooth information sharing between healthcare professionals,
and lead to inefficiencies in healthcare service delivery. Despite attempts to
tackle these issues with technical progress, current solutions have not fully
achieved widespread and lasting enhancements in EHR management. Hyperledger
Fabric [5], an open-source blockchain platform designed for enterprise use,
shows great potential for transforming multiple industries, such as
healthcare. Its distinctive attributes make it especially suitable for
tackling the issues found in conventional healthcare information management
systems [6]. By providing unique benefits compared to other blockchain
frameworks and conventional data management methods, it is suitable in
healthcare settings. For example, Hyperledger Fabric’s permissioned blockchain
network allows for greater control over who can access and contribute to the
stored data, ensuring privacy and security. By harnessing the power of this
innovative technology, healthcare facilities can enhance the quality of care
they provide while reducing costs and increasing patient trust.

The motivation for the study is due to the benefits of this technological
innovation as well as its security, technical aspects, and operational
feasibility at healthcare facilities. The current increase in specialised
healthcare services and patient movement emphasises the crucial need to
provide healthcare facilities with thorough patient medical histories. Sharing
clinical data securely across several healthcare facilities is a complex task
that demands a careful equilibrium between confidentiality, data integrity,
and patient privacy.

The main contribution of the paper is to explore the transformative potential
of implementing a blockchain-based Electronic Health Record (EHR) system.
aiming to revolutionise healthcare data management and improve patient care
outcomes. Other specific contributions of the paper include:

  * •

examining the viability, advantages, and obstacles of implementing a
blockchain-based EHR system

  * •

the implementation of the blockchain-based EHR system.

The Frere Hospital, where the study is conducted as a case study, is a
provincial and public hospital, and it plays a vital role as the primary
medical facility catering to the healthcare needs of East London and the
broader Eastern Cape region in South Africa. It focuses on providing essential
medical services to underprivileged communities, ensuring access to quality
healthcare for all. By introducing a blockchain-based solution, the study
seeks to demonstrate the potential benefits of blockchain technology in
improving data security, integrity, and accessibility in healthcare settings.
While the system is initially an ongoing research project, its ultimate goal
is to showcase its feasibility and effectiveness in real-world healthcare
environments and potentially pave the way for adoption.

The remaining part of the paper is structured as follows: Section 2 discusses
the literature review; Section 3 explains the methods; the discussion on the
implementation is in Section 4; and Section 5 concludes the paper.

##  2 Literature review

###  2.1 Background

Blockchain has emerged as a very significant and rapidly evolving subject on a
global scale, especially in the context of financial technologies, since the
start of the 21st century. This technology, in conjunction with distributed
database technologies, plays a crucial role in facilitating advancements in
distributed transaction and ledger systems, hence creating fresh possibilities
for digital platforms and services [14, 13]. According to Bhutta et al. [15],
the blockchain environment consists of a decentralised system that uses
cryptography to record and store an unchangeable, reliable, and sequential log
of transactions amongst interconnected participants. Similar to a distributed
ledger, the parties involved maintain, update, and validate this system. This
approach eliminates the necessity of a central authority to authenticate
transactions, as all members of the network collectively verify and safeguard
the information [16]. The extensive implementation of blockchain technology
across multiple sectors, such as finance[17], supply chain management[14],
healthcare[2], and voting systems[18], is mostly due to its high level of
transparency and security. The potential uses of blockchain technology are
extensive, with certain experts forecasting that it has the ability to
fundamentally transform the methods by which we engage in commerce and
transfer assets in the coming years.

The healthcare management sector is constantly changing as new technical
advancements provide fresh ways to tackle long-standing challenges. Blockchain
technology’s implementation in healthcare represents a fundamental shift in
the management of electronic health records (EHRs) and patient data [3].
Although traditional EHR systems have been effective in converting medical
records into digital format and improving administrative efficiency, they
frequently encounter challenges with the accuracy and security of data, as
well as the capacity to seamlessly exchange information with other systems.
Menachemi and Collum (2011) opined that EHR systems face some challenges,
including high upfront costs, ongoing maintenance expenses, workflow
disruptions leading to temporary productivity losses, and potential privacy
concerns among patients. Specifically, blockchain provides a secure and
verifiable record of patient data exchanges, which helps address these
difficulties. It enhances data security and confidentiality by decentralising
data storage and employing cryptographic techniques to prevent unauthorised
access, data breaches, and manipulation.

Furthermore, the distributed architecture of blockchain allows for effortless
compatibility between different healthcare systems and participants,
facilitating the safe transfer of patient information between different
organizations. Interoperability is especially vital in healthcare settings, as
patient care frequently requires cooperation across many clinicians and
institutions. The lack of interoperability, as stated by Iroju et al. [20],
poses significant challenges in healthcare systems, where health practitioners
may face difficulties in obtaining complete patient information, leading to
repeated tests and procedures. Healthcare organisations may optimise data
sharing processes, boost care coordination, and improve patient outcomes by
utilising blockchain technology. Also, blockchain technology has the potential
to empower patients by giving them more authority over their health data,
enabling consent management, and promoting transparency in healthcare
transactions [21].

Although blockchain has great promise, its implementation in the healthcare
industry is not without obstacles. According to Sharma and Joshi [22], low
awareness of legal issues and inadequate support from high-level management
are the most influential driving barriers, based on their study on blockchain
adoption in the Indian healthcare industry. However, the investigation of
blockchain technology in healthcare gives a promising chance to tackle the
intricacies of EHR management, boost data security and interoperability, and
eventually improve the provision of healthcare services to patients.

###  2.2 Related Work

In healthcare, studies have been conducted on the impact and feasibility of
blockchain to enhance healthcare service delivery [6, 7, 8, 9, 10, 11, 21,
22]. Several of these studies have shown promising results, particularly in
enhancing patient data security and improving interoperability among different
healthcare providers. It was stated by Pandey and Litoriya [7] that blockchain
provides a secure and transparent system for integrated healthcare services,
ensuring corruption-free and efficient implementation of nationwide health
insurance programs. Furthermore, research has also highlighted the potential
of blockchain technology in reducing medical errors [9, 8] and improving
overall patient care quality. Overall, the existing literature emphasises the
importance of analysing and designing blockchain-based EHR systems to
revolutionise healthcare delivery. An important feature of blockchain
technology in healthcare, specifically using Hyperledger Fabric, is its
capacity to guarantee the integrity and confidentiality of data [10]. This, in
turn, improves patient privacy and security. In the study by Sutradhar et al.
[6], the paper presents a specialised framework for managing identity and
access in the healthcare industry using blockchain technology. By utilising
Hyperledger Fabric and OAuth 2.0, it was shown that the framework guarantees
improved security and scalability while also providing transparency,
immutability, and fraud prevention.

Another interesting approach was by Antwi et al. [10]; the study examines the
practicality of using private blockchain technologies, notably Hyperledger
Fabric, to address different requirements and scenarios in the healthcare
industry. Empirical assessments in the study reveal the significant advantages
of the approach, such as heightened security, adherence to regulations,
interoperability, adaptability, and scalability, hence demonstrating their
potential to efficiently tackle crucial issues in healthcare data management.
The study by Stamatellis et al. [11] also looked at the changes that have
happened in healthcare from using paper-based systems to electronic health
records (EHRs) and the problems that have come with them, mainly looking at
cybersecurity risks like malware and ransomware. It specifically focuses on
notable events like the WannaCry ransomware cryptoworm and the Medjack
cyberattack. The research highlights the susceptibility of conventional EHR
databases to typical methods of attack and emphasises the necessity for a
scalable, unchangeable, transparent, and secure solution to tackle these
difficulties. The results of the experimental evaluation provide evidence of
the advantages of the method in improving security, compliance, compatibility,
flexibility, and scalability. This offers a potential alternative for managing
decentralised medical data, as also implied in this research.

Similarly, an effort by Al-Sumaidaee et al. [12] addresses the difficulties in
the healthcare sector caused by inadequate interoperability and fragmented
communication systems, which have negative effects on patients, resources, and
costs. The paper suggests implementing blockchain technology, specifically
Hyperledger Fabric, to enhance the exchange of information among various
healthcare organisations by introducing a trust element. It emphasises the
substantial influence of factors such as workforce size and transactions per
second (TPS) on network latency and overall throughput. The studies emphasise
the potential of blockchain technology, specifically Hyperledger Fabric, in
strengthening healthcare service delivery, improving patient data security,
minimising medical errors, and transforming healthcare practices. Although
recent studies show encouraging outcomes, there are still unresolved concerns
that need to be tackled. Some of the challenges include scalability,
regulatory compliance, interoperability, and the requirement for additional
empirical validation in real-world healthcare environments. This study
conducted empirical assessments and real-world implementations to provide
practical insights and validation for the solutions, considering these issues.
It is aimed at enhancing patient outcomes and healthcare service delivery by
raising awareness and acceptance of blockchain technology in the healthcare
sector.

##  3 Methods

The study uses a mixed-methods approach, starting with requirement gathering,
to investigate the adoption of blockchain technology, specifically the
Hyperledger Fabric, for the management of electronic health records (EHR) at
Frere Provincial Hospital. The implementation was divide into separate
components, each of which fulfils a specific role in the system’s
functionality. The main constituents consist of the Hyperledger Fabric network
and distributed ledger, smart contracts, the application Software Development
Kit (SDK), and the application frontend.

###  3.1 Requirement Gathering

The research collected data as part of the requirement gathering for the
system implementation. The goal was to gather patient insights while also
observing the operational dynamics at Frere Provincial Hospital. A structured
questionnaire was designed as a form of standardised format for data
collection. To encourage open and honest feedback, the respondents were
assured of the anonymity of their responses. It was distributed to a sample
group of patients, encompassing a diverse demographic. This was to investigate
concerns related to the current non-digital storage of medical records and
assess the perceived impact of administrative processes on the overall service
delivery experience.

For the on-site operational observations, physical observation was conducted
in the hospital environment, paying attention to document handling, data
retrieval, and administrative workflows. This was followed by an informal
interview with the hospital staff to gather qualitative insights into the
challenges faced in data management. Prior informed consent was obtained from
participants in adherence to ethical considerations without collecting
personally identifiable information.

Figure 1 provides a visual representation of the requirement-gathering
analysis, based on responses from a random sample of 10 patients. Subfigure
1(a) shows the frequency of patient visits to the hospital, with 70% of
respondents visiting regularly (more than five times), indicating a high
reliance on the hospital’s services. Subfigure 1(b) illustrates the awareness
of electronic health records (EHR) among patients, revealing that 60% of
respondents are not aware of EHRs, suggesting a significant gap in patient
knowledge about digital health record systems. Subfigure 1(c) depicts the
experience of patients with EHRs; 70% of respondents have no prior experience
with EHRs, highlighting the lack of exposure and potential challenges in
transitioning from a non-digital to a digital record-keeping system. Finally,
subfigure 1(d) reveals that 60% of respondents are dissatisfied with the
current manual record-keeping system, pointing to a critical need for
improvement in the hospital’s data management processes. This data underscores
the necessity for implementing a blockchain-based EHR system to enhance
efficiency, security, and patient satisfaction.

Figure 1: Insights on Electronic Health Record System: (a) Frequency of
hospital visits among patients (b) Awareness of Electronic Health Records
(EHR) (c) Experience with using EHR systems (d) Current record keeping
satisfaction.

###  3.2 The Hyperledger Fabric Components

The Hyperledger Fabric’s components are crucial and provide the technical
foundation for understanding the application of the proposed blockchain
technology implementation for electronic health records (EHR).

The modular architecture of the Hyperledger Fabric, as described in Figure 2,
is specifically designed to offer a flexible and scalable framework for
blockchain solutions, forming the backbones of the entire application,
managing the ledger, and facilitating interactions between various
participants. The smart contracts are crafted using JavaScript, a versatile
and widely used programming language. These contracts define the transactional
logic and rules governing the interactions between different entities within
the Hyperledger Fabric network. The front end of the application used Angular,
a popular web application framework. Angular111https://angular.io/ provides a
robust and dynamic user interface, enabling a user-friendly experience. It
serves as the interface through which users (patients, doctors, and
administrators) interact with the system. The test network adaptation entails
transforming organizations within the network to represent distinct hospitals.
This modification entails adjusting Docker files, configuration files, and
corresponding certificates. Specifically, alterations are made to organization
names in the “configtx.yaml” file, and adjustments are applied to the
certificate authorities in the docker-compose file. Afterwards, the files that
reference these configurations are updated. Once this custom network is set up
and a designated channel is established, as shown in the architecture, the
necessary certificates are made for the organisation and peers that are
involved. Also, as illustrated in Figure 2, the Hyperledger Fabric
architecture comprises two main organisations: Org1 (hospitals or clinics) and
Org2 (patients). Each organisation has peers—Peer0 for doctors and Peer1 for
patients—connected via Channel 1, which ensures secure, transparent, and
verifiable data exchanges. Both peers maintain a ledger (L1) that records all
transactions. The Client SDK facilitates application interactions with the
blockchain network, while the Membership Service Provider (MSP) handles
identity management, ensuring authorised access. The Certificate Authority
(CA) issues digital certificates for identity validation, enhancing the
system’s security. This architecture supports secure, efficient data sharing,
giving patients control over their health records, and enabling healthcare
providers to update patient information as needed.

Figure 2: Overview of the Hyperledger Fabric Architecture

###  3.3 Smart contract implementation and role-based access control

In line with the application’s modularity, all components are pluggable. The
backend code and smart contracts utilise ExpressJS as a server to deliver REST
APIs. Communication between the frontend and backend is facilitated through
REST calls, incorporating JSON web tokens for authentication. he fabric
framework supports two databases - LevelDB and CouchDB. The CouchDB database
was chosen due to its enhanced flexibility, especially in handling images and
supporting indexes, and features vital for the healthcare context. Given that
all patient data resides within the CouchDB, obviating the need for a separate
Electronic Health Record (EHR) store, CouchDB aligns perfectly with the
system’s requirements. In this architecture, CouchDB is leveraged to store the
world state. This design choice eliminates the need to query the entire
transaction log for each transaction request, streamlining system efficiency.
By providing quicker access to relevant information without traversing the
entire transaction history, CouchDB optimises the overall performance of the
system.

In the application, all the executable business logic is encapsulated within
smart contracts. This implies that any operations involving the creation,
retrieval, update, or deletion of records in the distributed ledger are
orchestrated through smart contracts. Each functionality required by the
system to interact with the Hyperledger Fabric (HLF) network is encapsulated
within a separate function for clarity and ease of maintenance.

As depicted in Figure 3, there are three primary smart contracts packaged into
a single chaincode, each catering to specific roles (Admin, Patient, Doctor):

  * •

AdminContract: Invoked by the administrator, this contract endows the admin
with the capability to create and delete patient records by adding or removing
patient objects from the ledger. The admin can also retrieve information on
all patients across the network.

  * •

PatientContract: Designed for patient interactions with the ledger, this
contract encapsulates logic tailored for the patient’s role. Specifically, the
patient can update and view personal details and passwords through the methods
defined in the contract. Additionally, the patient contract includes methods
to grant and revoke access from a doctor.

  * •

DoctorContract: Tailored for doctor interactions, this contract provides
methods enabling doctors to update and read patients’ medical details.

Figure 3: Relationships and Dependencies between the Contract Classes

The main reason for the three smart contracts is to ensure that each role has
appropriate access to data on the ledger. Only the PatientContract has the
right to update personal details, grant or revoke access, and update the
password. Similarly, the doctor’s methods are inaccessible to the patient or
admin. While the readPatient method is common for all roles, the data
retrieved by the contracts varies based on the role (i.e., the admin has
access to patient names, the doctor has access to medical records, and the
patient has access to the entire patient objects). This is to ensure a
granular and role-specific access control mechanism within the system on the
Hyperledger Fabric. The breakdown of the key components of the hyperledger
fabric in Algorithm 1 (Figure 4) illustrates the steps involve in setting up
the network, deploying smart contracts, and performing transactions.

Algorithm 1 Setting Up Hyperledger Fabric Network and Smart Contracts

1:Initialization

2:Define Org1 (Hospital/Clinic) and Org2 (Patients)

3:Create Peer0 for Org1 and Peer1 for Org2

4:Establish Channel 1 for communication between peers

5:Configure Membership Service Provider (MSP) for identity management

6:Setup Certificate Authority (CA) for digital certificates issuance

7:Smart Contracts Development

8:Develop AdminContract, PatientContract, and DoctorContract using JavaScript

9:Package contracts into chaincode

10:Network Deployment

11:Deploy chaincode onto the Hyperledger Fabric network

12:Initialize CouchDB for world state storage

13:Transactions Management

14:AdminContract

15:Create and delete patient records

16:Retrieve information on all patients

17:PatientContract

18:Update and view personal details and passwords

19:Grant and revoke access to doctors

20:DoctorContract

21:Update and read patients’ medical details

22:Access Control

23:Ensure role-specific access to data on the ledger

24:Implement granular access control for Admin, Patient, and Doctor roles

Figure 4: Algorithm for Setting Up Hyperledger Fabric Network and Smart
Contracts

##  4 Discussion

The implementation of the blockchain-based Electronic Health Records (EHR)
management system at Frere Provincial Hospital yielded promising results
across various test cases involving three sets of users: administrators,
doctors, and patients. Through rigorous testing, the system demonstrated its
efficacy in enhancing data security, streamlining administrative processes,
and improving patient care delivery. Figure 5 shows a sample deployment of a
local test fabric network, the installation and instantiation of a healthcare
chaincode, and the visualisation of the transaction history using the
Hyperledger Explorer.

Figure 5: The Fabric Network Deployment

The testing was conducted in separate phases, specifically focusing on
assessing the specific features designed for administrators, doctors, and
patients. Every stage yielded valuable observations regarding the system’s
performance, usability, and impact on healthcare service delivery. Figure 6
shows the complete Hyperledger Explorer integration.

Figure 6: The Hyperledger Explorer Integration

Overall, our findings from comparing traditional record systems, analysing
data from requirements gathering, and implementing the blockchain-based
electronic health records (EHR) systems reveal the following:

  * •

Hyperledger Fabric’s decentralised structure eliminates vulnerabilities
associated with centralised traditional database systems.

  * •

The automatic correction mechanisms of Hyperledger Fabric enhance its
effectiveness in mitigating manipulation risks. This provides reassurance
regarding the integrity and authenticity of healthcare data, addressing
concerns prevalent in traditional database systems.

  * •

Hyperledger Fabric’s ledgers ensure data permanence, contrasting with the
mutable nature of traditional databases. This highlights the significance of
data integrity and permanence in healthcare settings, where accurate and
reliable records are paramount.

##  5 Conclusion

The study examines the implementation of Hyperledger Fabric, a type of
blockchain technology, for managing electronic health records at Frere
Provincial Hospital. The study demonstrated the pragmatic application and
advantages of blockchain technology in healthcare information systems. The
study offers insightful information about how blockchain technology can
revolutionise healthcare information systems by enhancing EHR management
efficiency, security, and privacy. Although our study highlights the potential
use of blockchain technology in the management of electronic health records,
it is important to acknowledge our research’s limitations. As part of our
ongoing exploration of this technology, the study is a preliminary
investigation into the practical deployment and advantages of blockchain
technology in healthcare settings. The findings, derived from a single case
study, may not comprehensively encompass the intricacies and complexities of
wider healthcare settings. In light of our practical implementation of the
system, additional investigation and experimentation are necessary to
thoroughly examine the complete functionalities and prospective uses of
blockchain technology in healthcare settings. Specifically, challenges persist
within the Hyperledger Fabric necessitating ongoing development, such as
transaction history retrieval issues and performance concerns, which
underscore the need for continued refinement.

### Acknowledgments

The authors extend sincere gratitude to Frere Provincial Hospital for their
collaboration and support during the implementation of the blockchain-based
Electronic Health Records (EHR) system. The opinions expressed in this study
are solely those of the research team.

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