









































J Global Clinical Engineering Vol.4 Issue 3: 2022 16

Received January 31, 2022, accepted February 9, 2022, date of publication March 1, 2022

Overview of Trending Medical Technologies

By Jean Marie Vianney Nkurunziza, Jean Claude Udahemuka, Jean Baptiste Dusenge, Francine Umutesi 

Medical Technology Division, Rwanda Biomedical Center, Kigali, Rwanda

ABSTRACT

Healthy population is regarded as the most valuable asset of any country. Unfortunately, the health challenges that hinder man-
kind's wellbeing are enormously increasing. Examples include but are not limited to: the diversity of emerging diseases afflict-
ing the global population, the projected demographic growth of elderly people who need consistent monitoring, the deficiency 
in medical staff, the lower density of physicians, and the challenging geographical location of the population from healthcare 
providers. The mitigation of such health challenges calls for novel technologies to improve patient outcomes. In this article, 
seven emerging technologies, namely: Wearable Devices and Internet of Things, Artificial Intelligence, Blockchain Technology 
or Distributed Ledger Technology, Robotics Technology, Telehealth and Telemedicine, Big Data Technology and Nanomedicine 
have been highlighted. For each discussed technology, its historical background, development drivers, market status and trends, 
significance to healthcare, key player companies, and associated challenges have been presented. The information contained in 
this paper was collected from different journal articles, websites, reports, conference proceedings, and books. It was observed 
that though the technologies discussed in this article show growth at different rates, healthcare technology development and 
implementation are very promising in revolutionizing the health sector and improving the health of the population. Therefore, 
healthcare providers and countries are recommended to put in place Healthcare Technology Assessment Programs to help them 
collect data regarding the technology efficacy, relevance, safety, outcomes, and alternative technologies towards better planning 
for healthcare services improvement. 

Keywords – Wearable devices, Internet of Things, Blockchain, Telehealth and Telemedicine, Artificial Intelligence, Big Data, 
Nanomedicine, Market, Drivers, Challenges and Companies. 

Copyright © 2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY): Creative Commons - Attribu-
tion 4.0 International - CC BY 4.0. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) 
are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is 
permitted which does not comply with these terms.

INTRODUCTION

The triumph of modern medicine is axed to the emerging 
technological innovations, and there is no doubt that the 
medical expenditures and life expectancy are variables 
driven by technological progress.1-2 Medical technology 
uses scientific knowledge to improve healthcare by new 
and improved equipment to make work easier, pleasant, 
quick, and productive.3 The management and treatment 

of diseases have become largely dependent on innova-
tion and discoveries in newer drugs, surgical techniques, 
diagnostic and therapeutic equipment.3 Medical doctors 
themselves are becoming more reliant on technology to 
diagnose and carry out treatments.4 The scope of medi-
cal technology is vast; it covers consumables (bandage, 
syringes, hearing aids, wheelchairs, etc.), implants (hips 

http://www.globalce.org
http://globalce.org
http://globalce.org


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and knees, stents, pacemakers, etc.), medical equipment 
(imaging machinery, dialysis equipment, etc.), and in-vitro 
diagnosis.5 Technological innovations are appreciated by 
the general population because they enable a 4P-model 
for medicine (predictive, preventive, personalized, and 
participatory).6

The factors that reinforce the market for medical 
technology include advances in science and engineer-
ing, patent protection, increasing prevalence of chronic 
diseases, aging population, emerging pathogens, financial 
incentives of technology companies, mass media reports, 
public demand driven by direct-to-consumer advertis-
ing, consumer awareness and advocacy, rising prices of 
physician and hospital services, off-label use of drugs 
and devices, malpractice avoidance, strong and growing 
economies.7-8 The maintainability of high quality of life 
in the aging population is probably the most significant 
underlying global which requires requiring technological 
mindset.9 For example, Japan has the longest life expec-
tancy, and its aging population ratio is still increasing.

 This has called for rising expenditures, giving con-
cerns about the future inflation of health costs.10 In 2050, 
16% (1.5 billion) of the world’s population will be above 
65 years old.11 In China, 2.4 young people will have to 
support 7.9 old people in 2050.11 The physical nature, 
purpose, and stage of diffusion constitute the three ways 
to describe a healthcare technology.7 According to the 
stage of diffusion, medical technologies classification is 
presented in Table 1.

Today the actual figures for medical technologies are 
not available, but it is estimated that 500,000 different 
types of medical devices are in service.12 From 1960 to 
2007, health care expenditure in OECD countries increased, 
on average, from 3.8–9.0% of GDP.1 

In 2020 it was forecast that the global market for 
medical technology would achieve a volume of 490 billion 
euros.11 In 2025, global turnover for medical devices is 
estimated at approx. 615 billion dollars.11 

The main categories of healthcare technology include 
but are not limited to: drugs, biologics, devices/equip-
ment and supplies, medical and surgical procedures, 
public health program, support systems, organization, 
and managerial systems. However, not all technologies fall 
neatly into the category, and certain hybrid technologies 
combine drugs and devices.7 

In the past decade, the medical technology revenues 
have increased by 44.7% (USD 352.9 billion to USD 
510.9 billion for 2011 and 2021, respectively), and the 
forecast is to reach USD 594.5 billion in 2024.13 In 2022, 
the strongest medical technologies segments will be in 
cardiology, imaging diagnostics, orthopedics, and surgery. 
These technologies will account for 50% of the market.11 
Although there are giant companies in medical technol-
ogy, 95% of all medical technologies businesses are small 
and medium-sized companies (SME), with the majority 
having fewer than 50 employees.11 As of 2020, Medtronic 
Inc. was the leading medical technology company with a 
revenue of 30.12 billion USD. 

It was seconded by Johnson&Johnson with total revenue 
of 23 billion USD. In a survey conducted about medical 
technology in Belgium,5 106 companies participated, 
and the results are that 67.9% were active in medical 
devices-consumables, 15.1 % in In-vitro diagnosis, 12.7% 
in pharmaceutical products, 6.6% in para-pharmaceutical 
products, 43.4% in medical software, 40.6 % in implants 
and 45.3% in medical equipment and systems. Medical 
technologies are classified into preventive, screening, 
diagnosis, rehabilitation, palliation, and treatment types.7 

The technological acceptance and use expansion vary 
from society cultures. The Technology Acceptance Model 
developed by Davis, Theory of Planned Behavior, and 
Unified Theory of Acceptance and Use of Technology 2 
(UTAUT2) developed by Venkatesh showed that perceived 

TABLE 1. Classification of Medical Technologies According to 
the Stage of Diffusion7 

Medical 
Technology Class Explanation

Future in a conceptual stage, anticipated, or in the 
earliest stages of development 

Experimental undergoing bench or laboratory testing using 
animals or other models

Investigational undergoing initial clinical (i.e., in humans) 
evaluation for a particular condition or indication 

Established
considered by clinicians to be a standard 

approach to a particular condition or indication 
and diffused into general use 

Obsolete/
outmoded/ 
abandoned

Superseded by other technologies or 
demonstrated to be ineffective or harmful



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usefulness, perceived ease of use, price value, and habit 
are the key factors that determine the application and 
market expansion of a particular technology in a certain 
region.14,15 In addition to those factors, commercial-grade, 
durability, reliability, sustainability, technical support, 
disinfection, alarm management, network, and device 
security also advocate adopting a particular technology.16,17

LITERATURE REVIEW

  It is not easy to cover all details of the medical tech-
nologies available in a single paper due to their diversity. 
In this paper, the following trending technologies are 
looked at: Health Wearables and Internet of Things, Ar-
tificial Intelligence (AI), Blockchain Technology (BCT) or 
Distributed Ledger Technology (DLT), Robotics Technology, 
Nanomedical Technology, Telemedicine and Telehealth, 
Big Data

Health Wearables and Internet of Things

Environmental, psychological, behavioral, and physi-
ological domains that adversely impact the quality of 
life are recognized by the World Health Organization.19 
Wearables as medical technologies are becoming part of 
personal analytics, measuring physical status, recording 
physiological parameters, or informing schedules for 
medication.20 

The journey of wearables started with the invention 
of spectacles around the 13th century by English friar 
Roger Bacon.21 Growth in wearables was slow until the 
20th century, when in 1907, the first portable camera was 
put on the market. Since then, the pace of developing new 
devices never ceased to increase until 2014, when android 
wearables were commercialized. The whole evolution of 
wearable technology is picturesquely presented in the 
chronological sequence in Figure 1. 

From a monetary perspective, the market of wearable 
devices is anticipated to grow exponentially at a rate of 
20% and is expected to reach 150 billion EUR by 2028, 
as presented in Figure 2.

FIGURE 1. Evolutional milestones in wearable devices.21

FIGURE 2. Wearable market growth forecast.21



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In the third quarter of 2021, the Chinese market shipped 
35.28 million units across the globe,22 and the market was 
dominated by Huawei.23 From a technological point of 
view, wearables are self-contained devices with embedded 
sensors worn by the user to detect, diagnose, monitor, and 
communicate the health and performance data of the user.24 
Wearable technologies include smartwatches, wristbands, 
hearing aids, electronic/optical tattoos, head-mounted 
displays, subcutaneous sensors, Smart belts, electronic 
footwear (Smart shoes and socks), and Smart textiles 
(Smart pants, Smart shirts).20,25 Generally, wearables 
devices are composed of five components: sensors, con-
nectivity, battery, interface, materials/algorithm.25 From 
the design and manufacturing consideration, wearable 
devices contains microprocessors, interface including data 
communication, different types of sensors: inertial mea-
surement units (gyroscopes, accelerometers, barometers, 
and magnetometers), optical sensors (complementary 
metal-oxide-semiconductor [CMOS]) sensors, spectropho-
tometers, cameras, temperature sensors, chemical probes, 
electrodes, microphones, shock detectors, strain gauges.20

These days, when the world is dealing with COVID-19, 
vital-sign wearable solutions were implemented in differ-
ent countries. Wearables can provide a key early-warning 
system about the likelihood of COVID-19 infection and 
its surveillance.26 For example, in Singapore, ViSi mobile 
developed by Sotera was used as a wearable device on 
patients in mild illness to monitor heart bit rate, respira-
tory rate, body temperature, and oxygen saturation.16

Wearable devices find different application in biomedi-
cal and clinical services, as shown in Figure 3.

Apart from measuring vital signs, aggregate data taken 
from wearables can also contribute to the research by 
detecting general patterns and trends within a popula-
tion, contributing to improved public health responses.26 
Wearables are positioned to different body parts depending 
on the parameter to be measured, as shown in Figure 4. 

Wearable devices come into 4 main classes25:
• Lifestyle and fitness devices. This includes fitness 

trackers, sport and activity trackers (e.g., Moov Now, 
Misfit Shine, Fitbit charge2).

• Diagnostics and monitoring devices. These non-
invasive devices provide valuable health information 
(e.g., DexcomG4, Quardio Core).

• Therapeutic devices. These devices monitor disease 
states, track activity, store data, and deliver feedback 
therapy (e.g., Quell, Minimed530GInsulin Pump).

Injury prevention and rehabilitation devices. This 
includes body motion monitoring devices, wearable sens-
ing garments, fall detection devices (e.g., Philips lifeline, 
sprouting baby monitor).

The International Electro-technical Committee Stan-
dardization Management Board Strategic Group10 distin-
guishes wearable technologies into near-body electronics, 
on-body electronics, in-body electronics, and electronic 
textiles.17,21 Wrist-worn and handheld wearables are the 
most widely adopted and market-filled niche covering FIGURE 3. Some biomedical applications of medical wearables.27

FIGURE 4. Wearables based on on-body location.26



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Smart rings, wrist bands, smartwatches, and gesture 
control devices.21

Unlike conventional testing in a clinical setting, which 
may occur a few (or less) times a year, wearables offer 
continuous access to real-time physiological data.28 In 
their use, wearable devices are applications of the Inter-
net of things, a concept used by devices for sending and 
receiving data via the Internet.18 Embedded intelligence 
connectivity offers a unique opportunity for condition 
monitoring, localization, identification, personal contextual 
notifications, information display, and virtual assistance.21

The wearables data processing cycle follows 6 stages, 
as presented in Figure 5.

The wearable market is growing faster in patients 
with specific conditions like epilepsy, chronic obstructive 
pulmonary disease, asthma, heart arrhythmia, chronic 
pain, and breast cancer.17 

Today, many wearable devices are commercially available, 
such as rings, headsets, sleep masks, wearable patches, 
arm straps, finger clips, chest straps, fitness bracelets, fit-
ness bands, and flex garments. Specific products include 
Google Glasses, GOW Pack, LUMOback, Metria Wearable 
Sensor Technology, nECG Platform, Peeko Monitor, PER-
Smobile, NuMetrex Heart Sensing Racer Tank, Re-Timer, 
SleepShirt, T. Jacket, 360 Kids Guardian, and Vega.15,24,29

Significant growth in purchased wearable devices has 
been recorded in North America, Western Europe, and the 
Asia Pacific region, while in the rest of the world, the mar-
ket growth is lower. Reports about the future of wearable 
technologies predict that the market volume will be 27.8 
billion dollars in 2022 and 93.19 billion dollars in 2027.18

Some of the challenges of wearable devices include the 
feeling of constant surveillance, inefficient data analytics, 
lack of appropriate data labeling, insufficient comput-
ing capabilities, inefficient switching among resources 
in hybrid networks, lack of modern energy harvesting 

FIGURE 5. Wearables data processing cycle.21

TABLE 2. Wearable Wireless Technologies, Operating Frequency, and Range.21 

Communication Technology Frequency Range Range

Short-range RFID 125–134 kHz, 13.56 MHz, 860–960 MHz Up to 100 m
NFC

BLE (IEEE 802.15.1)
13.56 MHz

2.4–2.48 GHz 
<0.2 m

Up to 100 m
Zigbee Zigbee (IEEE 802.15.4) 868–868.6 MHz, 902–928 MHz, 2.4–2.49 GHz Up to 100 m

Wi-Fi (IEEE 802.11a/b/g/n) 2.4–2.48 GHz, 
4.9–5.8 GHz 20-250 m

Wi-Fi 5 (IEEE 802.11ac) 4.9–5.8 GHz Up to 70 m
Wi-Fi 6 (IEEE 802.11ax) 1–6 GHz Up to 120 m

WiGig (IEEE 802.11ad/ay) 57–70 GHz 10–100 m
VLC (IEEE 802.15.7) 400–800 THz Up to 100 m
VLC (IEEE 802.15.7) LTE frequency bands Up to 15 km

Long-range LTE-M LTE frequency bands Up to 10 km
LoRa 867–869 MHz Up to 50 km
Sigfox 868–878.6 MHz Up to 50 km



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opportunities, low data resolution.21 The major market 
players in wearable medical technologies are: Apple, Fitbit, 
Jawbone, Misfit, Mykronoz, Samsung, Garmin Ltd, Xiaomi 
Technology Co. Ltd, Qualcomm Technologies, Inc; Adidas 
Group, Sony Corporation, Lifesense Group.18 The details 
on many body-worn devices are presented in Figure 6.

Artificial Intelligence (AI) 

AI is rapidly evolving in clinical practice in dealing 
with a significant amount of data provided by Smart 
wearables, Smartphones, and other monitoring systems 
in medical services.6 The concept of AI was first conceived 
in 1950 by Alan Turing in his book entitled Computers 
and Intelligence in what was called Turing test when he 
was trying to determine whether computers were capable 
of human intelligence. In 1956, John McCarthy described 
“Artificial Intelligence” as the science and engineering 
of making intelligent machines.30 The systematic evolu-
tion of AI is presented in Figure 8. Today, AI is defined as 
using computers and technology to simulate intelligent 
behavior and critical thinking comparable to a human be-
ing or the science and engineering of making intelligent 
machines.31-34

 The evolution of AI is presented in Figure 3. AI is not 
one type of machine or robot but a series of approaches, 
methods, and technologies that display intelligent behavior 
by analyzing their environments and taking actions—with 
some degree of autonomy—to achieve specific targets that 
can improve health services.35,36 Studies about AI have 

exponentially increased from 826 in 2012 to 12563 in 
2019.37 By 2019, there were 279,145 AI patent applica-
tions in the US, with the global market expected to reach 
190.61 billion dollars in 2025. AI can add about $15.7 
trillion to the world economy by 2030,38 with China lead-
ing the global market in 2030 with a share of 26.1%.39

These assertions are justified by the research article 
published by Chinese universities from 2015 to 2019, as 
seen in Figure 7.

With AI, patients will receive more rapid, accurate diag-
noses and reduced adverse events. The top applications of 
AI include robot-assisted surgery, virtual nursing assistant, 
administrative workflow assistance, fraud detection, dos-
age error reduction, clinical trial participant identifica-
tion, preliminary diagnosis, automated image diagnosis, 
cybersecurity, health research, and drug discovery and 
development.41 AI also finds application in diagnosis and 
case identification and prognosis and prediction.

The AI umbrella encompasses the following subfields30:
• Machine learning (ML): Machine learning involves 

training an algorithm to perform tasks by learning from 

FIGURE 6. Wearable devices worn on various body parts and the 
parameters they can monitor.27

FIGURE 7. Top 10 institutions with the most AI-related publications 
(2015-2019).40



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patterns in data rather than performing an explicitly 
programmed job.42 Machine learning algorithms can 
automatically learn and improve from experience 
without explicitly programming. The most common 
algorithms of ML are: supervised learning (used 
when we can precisely define the task we want the 
algorithm to learn based on data that we already 
have), unsupervised learning (It is like learning 
without a teacher. We have a group of patients with 
different sets of data, but we do not know their 
individual diagnoses. We build a model, then try to 
cluster patients based on similar attributes such as 
the symptoms they presented with, their lab markers 
or age and gender), Reinforcement Learning (this 
allows the algorithm to learn how to complete the 
tasks with a sequence of decisions by itself without 
being told how to do it).35,37

• Deep learning (DL): It is a subset of ML with simi-
lar functions but with different capabilities.37 This 
method of AI allows a machine to be fed with large 
quantities of raw data and to discover the representa-
tions necessary for detection or classification.43 DL 
uses chips called graphics processing units to rapidly 
perform required calculations, a single card of which 
can potentially process hundreds of millions of im-
ages a day.42 DL mammography is used for breast 
cancer detection, in computed tomography (CT) for 
column cancer diagnosis, in chest radiographs, for 
the detection of pulmonary nodules.41  

• Natural language processing: This branch of AI is 
concerned with the use of computational methods in 
understanding and interpreting human language.35,42 
Artificial Neural Networks (ANN) or Simulated 
Neural Networks (SNN): ANN are considered the 
heart of DL. ANN is technology based on a human 
neural network.44 Examples of ANN include hand-
writing recognition, speech-to-text transcription, 
weather prediction, and facial recognition.45 An SNN 
contains a node layer, one or more hidden layers, 
and an output layer. Each node, or artificial neuron, 
connects to another and has an associated weight 
and threshold. If the output of any individual node is 
above the specified threshold value, that node is acti-
vated, sending data to the next layer of the network.46 
ANN are used in economics, ecology, environment, 

biology. In medicine, the most widely used family 
is the multilayer perceptron (PMC) in therapeutic 
decisions to process data for anthropology.47

• Computer Vision (CV): CV allows the building of 
artificial systems capable of retrieving any informa-
tion from an image previously obtained. CV involves 
different stages, namely: image acquisition (image 
capture with a sensor and transformation of visual 
information into digital information), pre-processing 
(preparing the image for the next level handling), 
feature extraction (detection of some objects to be 
analyzed), segmentation (separation of images into 
cohesive regions), noise reduction and high-level 
processing.48 Today, there are many practical ap-
plications where AI was successfully useful.

The key challenges of AI are their computing power, 
trust deficit, data privacy and security, data scarcity,38 
ethical regulations, high resource and research cost, short-
age of transparency, poor governance and accountability, 
notability of data annotation.49

 Globally, the AI companies are NVIDIA Corporation, 
Amazon.com, Inc., Meta Platforms, Inc., DeepMind, OpenAI, 
Affectiva, DataRobot, Ubiquity6 CloudMinds.50,51 To ensure 
appropriate utilization of AI, companies need to embrace 
techniques that help them achieve fairness, security, and 
explainability.49 

TABLE 3. Examples of Success of Artificial Intelligence.37 

Company Application

Babylon Health
Software application for online consultation 

where the system gives medication based on the 
symptoms entered in the system

Sensely 
(developed Molly 

app)

A virtual nurse that was designed to have a 
smiling face coupled with a pleasant voice to 
assist patients with monitoring their health

Deep Genomics 
(developed 

Oncecompass 
Medecine app)

To match genetic mutations found in patients’ 
tumor samples with ongoing clinical trials 

worldwide

IBM Watson Software that provides evidence-based treatment 
options for oncologists

Atomwise Uses supercomputers to root out treatments from 
a database of molecular structures

http://Amazon.com


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TABLE 4. Applications of Artificial Intelligence in Diagnosis and Prediction.43  

Diagnosis and case identification
Prognosis and prediction

Function Clinical area Applications

Waveform analysis
Obstetrics Intrapartum monitoring

Cardiovascular risk prediction, 
Prediction of breast cancer 

survival. Prediction of outcomes 
in colorectal cancer, Predicting 

of survival in non-small cell 
lung cancer. Prediction of 

hospitalization due to heart 
disease. Prediction of sepsis in the 

intensive care unit, emergency 
department, and hospital floor 

Prediction of treatment outcome 
in social anxiety. Prediction of 
psychiatric readmission from 

discharge summaries

Neurology Remote monitoring of gait

Image processing

Pathology Detection of lymph node metastases in breast 
cancer

Dermatology
Identification of benign and malignant tumors, 

identification of fungal infection, classification of 
skin cancer

Ophthalmology Identification of diabetic retinopathy, grading of 
macular degeneration

Cardiology
Diagnosis of acute coronary syndrome, 

identification of heart failure status through 
remote patient monitoring

Radiology Mammography, diagnosis of pneumonia from 
chest x-ray

Electronic health 
records analysis

Identification of sepsis in the emergency department, Identification of breast 
cancer symptoms, Heart failure case identification, Identification of patient 

phenotype from analysis of intensive care unit data, identification of medical 
subdomains in clinical notes

FIGURE 8. Historical evolution of artificial Intelligence.30



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BCT or DLT

Patients and healthcare practitioners are faced with 
the challenge of accessing, managing, integrating, and 
sharing health records securely.52 In many countries data 
are recorded on legacy papers and numerous discon-
nected electronic systems. In the US, 90% of physicians 
use unconnected computerized systems. Patients must 
recount their history multiple times, which may be done 
incompletely. Medical errors are estimated to be the third 
leading cause of death for Americans. In 2015, 140 mil-
lion patient records were breached according to Protenus 
Breach Barometer Report.53 The WHO estimates that many 
countries in Africa and parts of Asia and Latin America 
have areas where more than 30% of the medicines on 
sale can be counterfeit.54

In 2018, the healthcare industry continued to be plagued 
by data breaches involving sensitive patient information. 
According to the Breach Barometer 2019 Report, more 
than 15 million patient records were breached in 2018. 
Such incidents allow blockchain vendors to launch new 
solutions.54

To alleviate the associated adverse effects, an intercon-
nected system is needed. In the UK, the NHS planned to 
interconnect all computerizing health network records by 
2018; however, this target was delayed first to 2020 and 
again to 2023.55 Nevertheless, during COVID-19, which 
is ravaging the globe, blockchain technology was used by 
two UK hospitals to keep tabs on the storage and supply 
of temperature-sensitive COVID-19 vaccines.56  

In March 2021, Moderna, a biotechnology and phar-
maceutical company based in the United States, signed a 
new agreement with IBM to use blockchain technology to 
manage its COVID-19 vaccines. Additionally, 3M Pharma-
ceuticals, another American pharmaceutical giant, uses 
blockchain technology to curb counterfeit pharmaceuti-
cals. Recently, it has started using blockchain technology 
to identify and stop counterfeit face masks.57

BCT, though initially designed for the financial market, 
its inherent characteristics make it suitable for the health 
sector, insurance, pharmacy, IoT, food science, industries, 
e-voting, tourism, energy, and legal contract.58-60 BCT 
helps streamline business processes by establishing 

trust, accountability, and transparency.58 In medical ap-
plications, the ideal blockchain model would be scalable 
with high security and data privacy. In finance, bitcoin 
and Ethereum are examples of cryptocurrencies that use 
blockchain technology.61 

In medical and clinical services, by using BCT, patients 
become the platform, owning and controlling access to 
their healthcare data. The data are stored in the private 
blockchain cloud, where they cannot be changed by 
anybody, including physicians and patients themselves 
internally and natively. 

Because data is stored on a decentralized network, 
there is no single institution that can be robbed or 
hacked to obtain a large number of patient records. Data 
is encrypted in the blockchain and can only be decrypted 
with the patient’s private key. Even if a malicious party 
infiltrates the network, there is no practical way to read 
patient data.62,63

In terms of patients’ full control of their health record 
history, there are three major aspects of privacy that need to 
be considered: (a) data ownership; (b) fine-grained access 
control; (c) data transparency, integrity, and auditability.53

In healthcare services, the key enablers of blockchain 
are the need for patient data security, desire to reduce 
medical errors and mistakes, breakthroughs in genomics, 
drug traceability and safety, government partnerships, 
removal of unscrupulous attacks, reduction of cost in 
medical transactions, and improved confidentiality in 
healthcare business operations.63

A blockchain is a ledger of transactions where an iden-
tical copy of the ledger is visible to all the members of a 
computer network. It is a digital healthcare system man-
agement from which authorized users, such as providers 
and patients, have access.62 BCT is a permanent record of 
online transactions distributed, shared, and maintained 
by multiple parties. 

The first blockchain was developed by Satoshi Naka-
moto in 2009. The technology brought breakthroughs 
until 2021 when Dubai hosts all government operations 
and record-keeping operations on blockchain as part of 
the Smart Dubai 2021 initiative.64



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The data-sharing practice is essential to enable clinical 
practitioners to transfer their patients' clinical data to the 
concerned authority for a quick follow-up.60 BCT differs 
from a personal ledger in the number of security checks, 
whereby a blockchain makes many security checks.61 
This technology is interpreted as blocks linked together 
to form a chain to offer patients and caregivers the abil-
ity to securely share the patient identity and healthcare 
information across platforms. 

Today, the market for blockchain technology is very 
promising because it is forecast to save $100 billion per 
year since 2025. The saving will be realized in a reduction 
in data-breaching related costs, operations costs, informa-
tion technology (IT) costs, counterfeit-related fraud, and 
insurance fraud.52  In healthcare, the blockchain market 
in healthcare was valued at USD 2.12 billion in 2020 and 
is expected to reach USD 3.49 billion by 2026 and USD 4.7 

billion in 2027 with a CAGR of 8.7% during the forecast 
period, 2021–2026, with North America as the fastest-
growing market.54 Regarding research, the number of 
scientific publications about blockchain technology shifted 
from 5 in 2016 to 64 in 2018. This was another indicator 
that this market was rapidly attracting researchers.65 In 
its structure, the components of blockchain technology 
are listed below.

• Blocks are the base of a blockchain and contain 
records linked lists, chains, genesis blocks, and con-
sensus protocol.66 Blocks contain records of the past 
transactions and have segments reserved to save the 
data for future transactions. A block on a blockchain 
network consists of hash codes, root hash of merkle 
tree, and nonce.61

• Chains are blocks inside a blockchain network that 
are connected to each other. Multiple blocks that are 
joined together form a chain of blocks. 

• Nodes contain the entire history of a blockchain 
network. Nodes are the devices that store these 
vast amounts of data. Computers, laptops, and big 
servers function as nodes. All the nodes in a block-
chain network are linked together. Nodes verify the 
signatures, double-check the answer of the hash 
code after authenticating the details, and add a new 
block to the blockchain network. Nodes can stay both 
online and offline.61

• Master nodes. Selective blockchain networks have 
master nodes which are are more capable than 
normal nodes.61

• Peer-to-peer networks (P2P) are networks designed 
for linking two nodes.

There are four types of blockchains:
• Public blockchains are permissionless blockchains 

that allow anyone to join. All nodes of the blockchain 
have equal rights to access the blockchain, create 
new blocks of data, and validate blocks of data.58,67 

• Private or managed blockchains are permissioned 
blockchains controlled by a single organization. In a 
private blockchain, the central authority determines 
who can be a node. The central authority also does 
not necessarily grant each node with equal rights to 
perform functions.67

FIGURE 9. Theoretical schematic of blockchain technology in 
healthcare.59



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• Consortium blockchains are permissioned block-
chains governed by a group of organizations, rather 
than one entity. However, setting up consortiums 
can be a fraught process as it requires cooperation 
between several organizations presenting logistical 
challenges and potential antitrust risks.67

• Hybrid blockchains are controlled by a single orga-
nization, but with a level of oversight performed by 
the public blockchain, which is required to perform 
specific transaction validations.67

Some key players in the blockchain market are IBM 
Corporation, Microsoft Corporation, Gem, Patientory Inc., 
Guardtime Federal, Isolve, and Factom57

Robotics Technology

Technological advancement has revolutionized how 
medical procedures take place, including surgical opera-
tions. Credits go not only to the development of actuators, 
sensors, control systems, and materials but also to the 
growth of imaging systems for medical applications such 
as higher resolutions and magnetic imaging.71 Apart from 
the industrial robot (a word originating from the Czech 
word “robota” meaning compulsory labor) first developed 

50 years ago, today’s medical and healthcare robots are 
used in tremendous clinical work.72, 73

According to the Robotic Institute of America, a robot 
is a machine in the form of a human being that performs 
the mechanical functions of a human being but lacks 
sensitivity. The first robot was developed by Leonardo 
Da Vinci in 1495, purposed at amusing royalty. It was 
followed the creation of the first operational robot by 
Joseph Marie Jacquard in 1801, in which an automated 
loom, controlled by punch cards, created a reproducible 
pattern woven into cloth.73 

In medicine, robotic systems were first introduced in 
the mid-80s, and today they make an impact in various 
medical disciplines, including general surgery, research, 
therapy, rehabilitation, neurosurgery, orthopedic surgery,74 

and medical transport (for example, TUG Robot able to 
carry around more than 400 kilograms of medication).75 

As per 2017, 20% of the world population experience 
difficulties with physical, cognitive, or sensory function-
ing mental and behavioral health, which can be solved 
with robotics technology application.76 The very first 
mechanical robot to be used in surgery was the Puma 
560 in 1985 for the precise positioning of the cannula 
for brain biopsies.77

Statistics show that 1in every 25 patients will contract 
hospital-acquired infection (HAIs) in the USA, and 1 in 9 
will die.75 That is why next-generation smart hospitals 
have robotics that can help reduce infections, viruses, 
and bacteria.78 For example, Xenex Robot allows for fast 
and effective systematic disinfection of any space within a 
healthcare facility by destroying deadly microorganisms 
causing HAIs using special ultraviolet (UV) disinfection 
methodology.75 Data from the USA show that surgery 
costs annually are estimated to be $170 billion, with an 
estimated $41 billion US spent on readmission due to 
complications. In Europe. over half (52%) of all surger-
ies were due to unexpected complications. Consequently, 
robotics can lower the readmission rate by up to 50%, 
resulting in a saving of $10 billion annually.79 The global 
landscape of robotics application in healthcare and well-
being are presented in Table 7.

TABLE 5. Challenges of Blockchain Technology59,62,60 

Technology Blockchain software is still in its infancy, 
continually being developed and refined 

Integration Must initially be co-existent with current 
technologies, must be integrated overtime 

Cost Adoption of new technologies will incur 
initial greater costs to institutions 

Regulation
Government institutions have yet to settle 

regulatory concerns over blockchain 
technology

Culture
Adoption of the technology will require 

significant buy-in from the global 
community 

Energy
Maintaining the blockchain requires a 

network of nodes, and resulting substantial 
computing power 

Privacy
Emerging cyber security concerns must be 
addressed before individuals will entrust 

data to a public blockchain



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FIGURE 10. Blockchain structure in hospital applications.68

FIGURE 11. Properties of blockchain technology.69



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In their general design and construction, medical robots 
consist of a Central Processing Unit (the robot's brain for 
coordinating all its activities) and Sensors (acting as the 
powerhouse of the robot feedback mechanism). These 
include light sensors, sound sensors, temperature sensors, 
contact sensors, proximity sensors, distance sensors, pres-
sure sensors, positioning sensors, etc.). Also included are 
Actuators (the robot's hydraulic, pneumatic, or electric 
muscles), End-Effectors (the tools that perform the actual 
work and interact with the environment or a workpiece), 
the Power Supply (energy required for robot operation), 
and the Program (for providing the logic that drives the 
robot behaviors and activities).81

Robotics applications in medicine involve different 
stakeholders, including primary stakeholders (direct 

robot user, clinicians, and caregivers), secondary stake-
holders (robot makers, environmental service workers, 
health administrators), and tertiary stakeholders (policy 
makers, insurers, advocacy groups).76 Among robotics 
applications, surgical robots have a high revenue growth 
market segment, are highly competitive with established 
players, well-defined market entry routes, and a good 
product innovation pipeline.80 

In 2020, the leading global company in medical ro-
botics was Intuitive Surgical, with a market cap of $121 
billion,  6335 robots in service,78 with more than 1.2 mil-
lion procedures performed globally, and with a growth 
of 18% per year.80 

TABLE 6. Blockchain Potentials for Healthcare and Life Science52,59,70 

Category Potential use Key Benefits

Patients

Patient empowerment. Patients can keep track 
of their medical background. Patients can check 
their latest medical prescriptions, Patients can 
share their data securely across their providers

Increases patient trust. Improves patient access to trusted 
data. Facilitates better collaboration, Increases transparency. 
Improves and personalizes the patient experience. Increases 

efficiency and reduces operations costs, Enables patient access 
to their health records anywhere in the world. Enables patient 

access to their latest prescriptions

Regulation and 
compliance

Compliance tracking, Smart contract-based 
check

Establishes a trusted audit trail verifiable in real-time. 
Establishes a platform to enforce privacy regulations 

automatically. Enables monitoring of who has shared data and 
with whom, without revealing the data itself

Inter-company 
processes

Transfer of funds. Medical devices supply chain. 
Temperature-controlled supply chains, Services

Facilitates automated payments through smart contracts. 
Increases speed for payments. Provides full transparency of 

assets across the supply chain to the patient. Enables certified 
& private messaging between medical devices and service 

providers. Brings all transactions into a single platform

Administration and 
back offices Revenue management

Improves efficiencies in tracking and tracing areas where 
leakage occurs. Reduces admin costs, Increases reliability and 

auditability. Speeds up financial transactions process

Pharmaceuticals Verifies drug provenance. Creates an industry-
wide, single source of aggregate information

Tracks and traces pharmaceuticals, Proof of authenticity for 
anti-counterfeiting techniques. Helps prevent the transport 

and sale of counterfeit products. Makes it is possible to detect 
the full spectrum of complications related to pharmaceutical 

treatment

Research and 
development Securing clinical trials

Prevents theft of intellectual property. Enables users to 
authenticate any document and ensuring proof of the existence. 

Enables access to a huge anonymous and authenticated 
database of patients



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Other companies in service include Boston Dynam-
ics, Stryker, Accuracy, Vicarious Surgical, Medtronic, GE 
Healthcare, Myomo, Stereotaxis, Ottava77,78 Neocis.Inc, 
Medtronics, Brainlab, Smith & Nephew plc, Corindus 
Vascular Robotics, Inc., Riverfield Co., Ltd, Auris Health, 
Inc., etc.80

Between 2015-2020, China emerged as a leader for 
next-generation surgical robotic systems’ innovations 
with 237 (36.5%) patents published in this area from 
2015 to 2020 (Figure 12).80

TABLE 7. Medical Robotics Market Potential Assessment Summary80 

Healthcare robotics Technology 
Readiness level

Breadth of 
application Current adoption Growth potential

Medical robots

Surgical
Robots

Diagnostics
Robots

Healthcare Service 
robots

Medication delivery and 
dispensing

Cleaning and disinfecting

Telepresence and remote 
monitoring

Autonomous vehicles

Care robots

Personal assistant/
Companion robots

Assistive robots

FIGURE 12. Medical robotics patent filings from 2015 to 2020.80



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The global medical robot market is expected to reach 
USD 12.7 billion by 2025 from an estimated USD 5.9 
billion in 2020 at a CAGR of 16.5% during the forecast 
period. On the other hand,82 medical robotics market 
is forecast to account for $43.22 billion in 2028 with a 
compound annual growth rate of 22.3% from 2021 to 
2022 (Figure 13).82

The key drivers of medical robotics market evolution 
include demand for minimally invasive procedures for 
diagnosis, improved precision in diagnosis and treatment, 
technological advancement in AI, management of surge 
capacity during peak demand, and improvement of the 
overall efficiency of logistics. Also, there is a desire to 
increase the automation of pharmacy operations, large 
population living with chronical illnesses, hospitals’ will 
to maintain hygiene protocols and standards, especially as 
it directly impacts hospital accreditation, reduces manual 
labor, improves efficiency and cost savings for cleaning 
and disinfection. Increasing prevalence of stroke, multiple 
sclerosis, Parkinson's disease, cerebral palsy, Rise of the 
elderly population, and shortage of caregivers.80 

Nowadays, since 2019 when the whole world experi-
enced the COVID-19 outbreak, robotics has been finding 
applications in undertaking human-like activities.83 In 

Rwanda, robots were deployed to minimize contact time 
with confirmed cases and reduce the risk of contamination 
of health professionals in COVID-19 treatment centers. 
The 5 human-size robots are programmed to perform 
temperature screening, take vitals readings, deliver video 
messages, detect people not wearing masks, and then 
instruct them to wear masks properly. One robot called 
Urumuli deployed at Kigali International Airport had the 
capacity of screening 50 to 150 people per minute and 
reporting abnormalities to officers on duty.84 

Later, on 9 February 2021, in partnership with the 
United Nations Development Programme, the govern-
ment deployed another set of three THOR UVC robots to 
Nyarugenge District Hospital to strengthen the national 
response to COVID-19 pandemic.85 Robots were also used 
to store patients’ data during diagnosis and treatment, 
reduce the workload of healthcare providers, ease the di-
agnosis procedures, and assist the physicians and students 
in learning more about the new disease in a short time.86

In South Korea, a self-driving robot with cameras 
and an LED screen was used to greet clients at the coun-
try’s biggest mobile operator, check their temperatures, 
dispense hand sanitizers, and disinfect the floor. Other 
robots were used to disinfect 33 square meters in 10min 
using ultraviolet radiation. In addition, they could detect 
people's gatherings, advise them to disperse, and wear face 
masks.87 In China, Wuhan City, where the pandemic was 
first detected, constructed a fully robot-staffed hospital 
where patients entering were screened by connected 
5G thermometers to alert staff for feverish. In addition, 
Patients wore smart bracelets and rings that synced with 
Cloud Minds’ AI platform so their vital signs, including 
temperature, heart rate, and blood oxygen levels, could be 
monitored. Doctors and nurses also wore the devices to 
catch any early signs of infection.88 Regarding the future 
of medical robotics, up to 2013, Nanorobotics was still 
the largely hypothetical technology of creating machines 
or robots at or close to the scale of a nanometer.73

Though the growth of the medical robotics industry is 
promising, it is humped by the following challenges: high 
establishment cost, fewer trained professionals to adminis-
ter the tests, technical complexities leading to operational 
issues, the high running cost for disadvantaged people.80

FIGURE 13. Market growth for medical robotics.82



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Nanomedical Technology

It is a technology for diagnosing, treating, and preventing 
disease and traumatic injury, relieving pain, preserving 
and improving human health using molecular tools and 
molecular knowledge of the human body.89 Nanotechnol-
ogy classically refers to the matter in a size range of 1–100 
nm but can be extended to include materials below 1 μm 
in size.90 Nanomedicine is also defined as the application 
of nanobiotechnologies to medicine.91,92

Though the concept of nanotechnology dates to 1959, 
the optimistic expectation of nanoparticles and nanoscale 
tools to improve the diagnosis and pharmacological 
treatment of several diseases was first established in 
1990.93 The basis of this new science derives from the 
development of an array of ultramicroscopic devices 
and the studies of cellular, molecular, and finally atom-
sized structures in biology, chemistry, and physics in the 
20th century. Nanotechnology is not in itself a single 
emerging scientific discipline, but rather a meeting of 
different traditional sciences linking physics, chemistry, 
biology, medicine, electronics, and IT.94 Nanotechnology 
in medicine was recently focused on because there is a 
diversity of diseases originating from the alteration in 
biologic processes at the molecular level like mutated 
genes, misfolded proteins, and infections caused by viruses 
or bacteria (Figure 14).95 The three main subsections of 
nanomedicine are: nanobiotechnology, nanotechnology, 
and nanobiomimetics.96

Currently, in medicine, nanotechnology is used in 
antibacterial treatment, wound treatment, cardiovascu-
lar diseases, ophthalmology, cancer-fighting, cell repair, 
imaging, probing of DNA structure, tissue engineering, 
tumor detection, separation and purification of biologi-
cal molecules and cells, MRI contrast enhancement and 
phagokinetic studies, company directory and to deliver 
drugs, heat, light or other substances to specific types of 
cells (such as cancer cells).91,97 Its use in diagnostics is 
at the development stage. The use of nanoparticles will 
reduce damage to healthy cells in the body and contribute 
to the early detection of diseases.91 The global Nanomedi-
cine market size is projected to reach USD 232 million by 
2026, from USD 150 million in 2019, at a CAGR of 6.4% 
during 2021-2026.98

The nanomedicine market segmentation by type includes: 
• Quantum dots (QD): QD are semiconductor nano-

crystals that have a reactive core (made of cadmium 
selenide CdSe, cadmium telluride [CdTe], indium 
phosphide [InP], or zinc selenide [ZnSe]), for control-
ling their optical properties. QD are used in medical 
real-time tissue imaging,99 biological probes, for 
live cells labelling,100 drug delivery vehicles, in vivo 
imaging, therapeutic delivery,101 blood cancer assay, 
and cancer detection and treatment, in vivo animal 
targeting, tracking different particles, forecasting of 
disease stage.102

• Nanoparticles: A considerable fraction of the solid 
matter on earth can be found in the size range of 
colloids and nanoparticles, and in the last 2 decades, 
scientists have shown that colloids and nanoparticles 
are present everywhere in the environment.103 NPs 
are categorized into three types: natural nanopar-
ticles, incidental nanoparticles, and engineered 
nanoparticles (Figure 15).104 

From a chemical point of view, nanoparticles are classi-
fied into inorganic and organic types. Inorganic nanopar-
ticles are used as antimicrobial agent against bacteria, 
fungi, parasites, and viruses.104 Organic nanoparticles 
prepared from various materials, including polymers 
and lipids, have found exciting therapeutic delivery and 
imaging applications.105

FIGURE 14. Relationship of nanobiotechnology to nanomedicine 
and other biotechnologies.91



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The choice of material impacts various properties, 
including drug encapsulation, immunogenicity, and target-
ing. At the same time, the design of nanoparticles, such as 
size, shape, flexibility, and compartmentalization, will also 
impact nanoparticle performance. These two attributes 
(choice of material and nanoparticle design) collectively 
determine the therapeutic outcome (Figure 16).105

Other applications of nanoparticles within medicine 
include tissue engineering, bio-micromechanical systems 
(bioMEMS), biosensors, anticancer drugs, microfluidics, 
and diagnostics.106 

• Nanoshells: The discovery of nanoshells was made 
by Professor Naomi J. Halas and her team at Rice 
University in 2003.107 These are a special class of 
nanomaterials that consist of concentric particles.108 
A nanoshell is a type of nanoparticle with a dielectric 
(e.g., silica) core and a thin metal coating (usually 
gold).109

Nanoparticles find a place in medicine because of their 
safety, biocompatibility, stability, bioavailability, optically 
tunable, and photo-luminescent ability as well as high ability 
to attach to many therapeutic materials. Nanoshells (and 
especially gold nanoshells) show promise application in 
biomedical imaging, target therapy, gene delivery, tissue 
welding, drug delivery systems, therapeutic applications in 
general, and cancer imaging and treatment (Figure 17).110

Gold nanoshells exhibit unique optical properties 
because their interaction with the electromagnetic field 
is greatly intensified by a phenomenon known as local-
ized surface plasmon resonance. They are designed to 
absorb radiation at various frequencies absorb certain 
types of radiation. Once the nanoshells are attached to 
the cancerous cells, only laser light is needed to treat 
cancer. Near-infrared (NIR) light passes through the body 

FIGURE 15. Types of nanoparticles.104

FIGURE 16. Design parameters for nanoparticles.105

FIGURE 17. Use of nanoshells for cancer treatment (Source: National 
Cancer Institute).



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and reaches the gold nanoshell. The tuned gold nanoshell 
receives the NIR light and converts the light energy into 
heat, killing the cancer cells.107

• Nanotubes: Nanotubes, usually made in carbon 
(CNTs), consist of carbon atoms arranged in a series 
of condensed benzene rings rolled up into a tubular 
structure.111 Carbon nanotubes (CNTs) are cylin-
drical molecules that consist of rolled-up sheets of 
single-layer carbon atoms (graphene). They can be 
single-walled (SWCNT) with a diameter of less than 1 
nanometer (nm) or multi-walled (MWCNT), consist-
ing of several concentrically interlinked nanotubes, 
with diameters reaching more than 100 nm. Their 
length can reach several micrometers or even mil-
limeters (Figure 18).112

Their impressive structural, mechanical, and electronic 
properties are due to their small size and mass, incred-
ible mechanical strength, and high electrical and thermal 
conductivity. In medicine, nanotubes are used in pharma-
ceuticals, drug delivery systems, gene delivery and therapy, 
tissue engineering, bio-imaging, biosensor applications, 
lab-on-chip devices, photo-thermal therapy, diagnostics, 
and high-performance composites for implants.113,114

Although there are advantages of nanotubes (like 
biocompatibility, rigidity, mimicking of natural tissue 
nanofibers, stimulating the adhesion and proliferation 
of cells and ability to form strong 3-D architectures, 
high surface area, high photo-stability and absence of 
quenching, special optical, mechanical, and electronic 

properties),114 concerns related to their toxicity, biosafety, 
and biodegradation still remain.113 Examples of nano-
technology equipment in medicine include atom probes, 
atomic absorption spectrometer, profilometers, raman 
microscopes, calorimeters, cryogenic probe stations, 
scratch testers, flow chemistry reactors, graphene, surface 
analyzers, Spectroscopic ellipsometer, wafer bonders, 
x-ray detectors, x-ray diffractometer, etc.106

The challenges faced by nanotechnology include high 
manufacturing costs, technical challenges, raised skepti-
cal opinions within the scientific community about the 
clinical relevance of nanomedicine.93 The competitive 
landscape of the industry has also been examined along 
with the profiles of the key players who include Abbott 
Laboratories, Arrowhead Pharmaceuticals Inc., General 
Electric Company, Luminex Corporation, Merck & Co. Inc., 
Nanobiotix, Novartis AG, Pfizer Inc., Sanofi SA, Starpharma 
Holdings Limited.115

Telemedicine and Telehealth

The provision of primary healthcare has been challeng-
ing during the recent and current periods of COVID-19 due 
to overcrowding of medical services seekers to different 
health facilities.116 It is evident to many that COVID-19 
accelerated the adoption of Telemedicine globally.117 
Telemedicine uses electronic communications and in-
formation technologies to provide clinical services when 
participants are at different locations.118,119 Some writers 
prefer to use the term “telehealth” interchangeably with 
“telemedicine,” but Telehealth is broader because it also 
considers even non-clinical services. Telehealth refers to 
‘the use of telecommunications and IT to provide access to 
health assessment, diagnosis, intervention, consultation, 
supervision and information across distance.120

Telemedicine is traced back many centuries, starting 
from ancient hieroglyphs and scrolls to share informa-
tion about health-related events such as outbreaks or 
epidemics. This was followed by using smoke signals to 
warn nearby cities of sickness.120 In contemporary times, 
Telemedicine through telephone and video technology 
has been used since the 1960s in the military and space 
sectors.121 Apart from military services, Telehealth was 
first used in 1972 when Murphy and Bird conducted 500 

FIGURE 18. Conceptual diagrams of single-walled carbon nanotubes 
(a) and multiple-walled carbon nanotubes (b).111



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patient consultations via interactive television.122 Today, 
Telemedicine is applied in radiology, dermatology, surgical 
peer monitoring, medication management, mental health, 
diagnosis, patient monitoring, etc.123

The drivers of Telemedicine include: enhancement of 
care coordination, patients and doctors are fascinated 
by the services offered by Telemedicine, society, and 
healthcare tendency to digital life (in OECD countries, 
nearly 65% of people aged 65 to 84 years are estimated 
to have more than one chronic condition, a prevalence 
that reaches 89% for those aged 85 and over), bridging 
of the rural gap, continuous innovation in the consumer 
technology market, projected shortages in the health pro-
fessional workforce, growth of consumerism in health care 
cost-effectiveness, quick access to medical services,123,124 
improved quality, medication management, changes in 
care models.125,126

The services offered by Telemedicine include special-
ist referral services (assisting a general practitioner in 
rendering a Diagnosis), direct patient care (sharing audio, 
video, and medical data between a patient and a health 
professional for use in generating a diagnosis, treatment 
plan, prescription or advice), remote patient monitoring 
(devices to remotely collect and send data to a monitor-
ing station for interpretation), medical education and 
mentoring, consumer medical and health information, 
patient support service (reminders to take medication, 
supervision, scheduling of appointments and similar ap-
plications which are not implicitly medical).118

There are four key elements needed for a successful 
telemedicine program.
1. Collaboration tools are devices that help patients 

to connect with healthcare service providers. They 
include smartphones, laptops, tablets, etc.127

2. Medical peripherals are the diagnostic tools used in 
Telemedicine, such as otoscopes, ultrasound machines, 
or digital stethoscopes.127

3. Workflow represents adequate software to manage 
the complete process of connecting patients to medi-
cal professionals and to integrate Telemedicine with 
their existing IT resources.127

4. Cloud-based services: Cloud computing delivers dif-
ferent services through the Internet. These resources 
include tools and applications like data storage, 
servers, databases, networking, and software. When 
using cloud computing, the user is not required to 
be in a specific place to access it, allowing the user 
to work remotely.128 In Telemedicine, cloud-based 
services help user-friendly access to medical records 
for both clinicians and patients from anywhere they 
can access the Internet.129 

When the world experienced COVID-19 pandemic, 
social distancing measures were put in place to fight its 
sustainability. Moreover, the rapid global spread of CO-
VID-19 has increased the volume of data generated from 
various sources.130 The cloud technology had a major 
role in fighting the epidemic; it became a salvation for 
governments and organizations in numerous fields of 
life, education, health, industry, communication, remote 
surveillance, and more information (Figure 19).131

FIGURE 19. Use of Telemedicine by doctors and patient benefits.123



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Generally, the lines of action of the telehealth program 
are based on three components, as presented in Figure 20.

From 2010 to 2017 the world experience growth in 
the use of Telemedicine, with three diseases dominating 
the growth rate. Those are diabetes, congestive heart 
failure (CHF), and chronic obstructive pulmonary disease 
(Figure 21).

Since 2018, the quarterly investment in Telehealth has 
experienced peaks and bottoms, but when WHO officially 
declared COVID-19 as a pandemic on 13 March 2020, 
the investment in Telehealth has drastically increased 
compared to previous years, as presented in Figure 22.

Generally, the global telemedicine market was valued 
at $50 billion in 2019, with forecast potential growth to 
increase to $460 billion by 2030.135

There are three types of Telemedicine:
• Store and forward telemedicine or asynchronous 

Telemedicine. In this type of Telemedicine, patient 
information such as medical images or bio-signals 
can be sent to the specialist as needed when it has 
been acquired from the patient.136 It is regarded as 
the acquisition and storing of clinical information 
such as lab reports, data, images, sound, and videos 
that are then forwarded to (or retrieved by) another 
site for clinical evaluation.122

• Real-time video or synchronous Telemedicine. 
In this type of Telemedicine, consultations use video 
conferencing to connect the patient with the physi-
cian. Patients from their homes can use smartphones, 
tablets, or computers to interact with physicians. This 
method enables the physician to conduct a medical 
consultation as they would in person.122

• Remote monitoring telemedicine. This uses a 
range of technological devices to remotely monitor 
a patient's health and clinical signs. This is exten-
sively used in the management of chronic diseases 
such as cardiovascular disease, diabetes mellitus, 
and asthma.136

The key challenges hindering the growth of Tele-
medicine are system development costs, digital literacy, 
Digital Technology Acceptance, less accurate diagnosis for 
specific images transmitted with Telemedicine concern-
ing the original images, aspects linked to security and 
confidentiality in the doctor-patient relationship through 

FIGURE 20. General lines of action of telehealth.132

FIGURE 21. World Telehealth Patients (thousand) per disease.133

FIGURE 22. Quarterly global telehealth funding (2018-2021) in $M.134 



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appropriate interfaces, and system implementation by 
the involvement of different parties.132,137

Although Telemedicine has many challenges to overcome, 
there are also opportunities to sustain its development. 
They include gap service coverage (for example, in the 
USA, teleradiology predominates other services), urgent 
service coverage (a case of a mobile telemedicine system 
for consulting acute stroke even remotely by employing 
a wireless LAN or a mobile phone network), and video-
enabled multisite group chart rounds (model of medical 
education liked to clinical care).138,139

Big Data

The healthcare landscape is saturated with a large, 
diversified amount of data. Big Data in healthcare is over-
whelming because of its volume and the diversity of data 
types, and the speed at which it must be managed.140 Those 
data could be an enabling resource for deriving insights 
for improving care delivery and reducing waste.141 Over 
more than a decade, as in other industries, the medical 
industry has experienced rapid digitization due to an 
increase in electronic medical records (EMR).142 

Driven by mandatory requirements and the potential 
to improve the quality of healthcare delivery and obtain 
the best healthcare services meanwhile reducing the costs, 
requires a significant diversified quantity of electronic 
health records to help in clinical decision support, disease 
surveillance, and population health management.140,143

Big Data should be collected and used to ensure agree-
ments between patients, healthcare service providers, and 
policy and research. Today, there is no common definition 
to explain what Big Data is. However, some researchers 
tried to formulate the meaning of Big Data. According to 
McKinsey the term “Big Data” refers to “datasets whose 
size is beyond the ability of typical database software 
tools to capture, store, manage, and analyze.”144 Big data 
is unmanageable using traditional software. We need 
technically advanced applications and software to employ 
fast and cost-efficient high-end computational power to 
utilize it properly. The term Big Data is described by the 
following characteristics: value, volume, velocity, variety, 
veracity, and variability, denoted as the 6 “Vs”.143

According to some studies have shown that 93% of 
healthcare organizations have experienced a data breach 
because personal data is extremely valuable and profitable 
on the black markets, and this pushed organizations to 
start using data analytics to help them prevent security 
threats by identifying changes in network traffic, or any 
other behavior that reflects a cyber-attack.146

Big Data help to identify individual and community 
trends and develop better treatment plans or predict 
at-risk patients, forecast patient admissions trends and 
schedule the correct number of staff, drive innovation, 
compare chronic disease and population growth in 
neighborhoods, streamline insurance claims processes, 
easy detection of fraud and inventory tracking.147 The 
global health data in 2013 only was estimated to be 153 
Exabytes, with forecast potential growth to 2,314 Exabytes 
in 2020 alone.135

Big Data analytics are divided into four categories:
• Descriptive analytics. This consists in decrying the 

current situation and reporting on it.
• Diagnostic analytics aim to explain why certain 

events occurred and what factors triggered them.
• Predictive analytics. This reflects the ability to 

predict future events; it also helps identify trends 
and determine probabilities of uncertain outcomes.

• Prescriptive analytics. This proposes suitable ac-
tions leading to optimal decision-making.148

The global Big Data analytics in healthcare market size 
was valued at $16.87 billion in 2017 and is projected to 
reach $67.82 billion by 2025, growing at a CAGR of 19.1% 
from 2018 to 2025.149 

The nine stages that make analyzed data useful are 
shown in Figure 23. Big Data come from clinical practices 
and research, patient-generated data, medical claims, 
electronic healthcare records, social media, patient sum-
maries, genomic and pharmaceutical data, clinical trials, 
Telemedicine, mobile apps, sensors, and information on 
wellbeing, behavior, and socio-economic indicators.142,144  
Big Data are used in medical services to gain advantages 
as shown in Figure 24, and Big Data architecture for 
healthcare is presented in Figure 25.



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The Big Data analysis ensures that the health facility 
manager sees a big picture of the hospital, the attendance, 
its nature, the costs incurred, etc., which will help run it 
smoothly. An example of a dynamic dashboard for patient 
care is shown in Figure 26.146 The challenges facing Big 
Data technology are: segmentation of data in healthcare 
providers (clinical data, financial data, administrative 
data, patient data are not linked and shared), protection 
of patient’s privacy,151 data capturing, cleaning and stor-
age, stewarding and querying.152,153

There are several challenges in adopting Big Data 
technology: data in many health care providers are often 
segmented or siloed, complicated use Big Data is compli-
cated, long system response time.151,154 The key players 

in healthcare data analytics include IBM, Cerner, Health 
catalyst, McKesson, Oracle.155

CONCLUSION

In conclusion, driven by needed increases in medical 
productivity, the growing prevalence of chronicling dis-
eases, the increasing aging population, and the increasing 
emphasis by healthcare agencies towards early diagnosis 
and treatment, many countries and healthcare providers 
are struggling to scale-up technology level to provide 
adequate services to patients. In addition, physicians 
themselves believe in introducing new technologies to 
help them prevent, diagnose, treat, monitor, and care for 
patients. 

Technology advancement has proven effective in 
providing access to information, facilitating remote care, 
improving efficiency by connecting the patients with 
physicians, cost-effective and time-saving solutions. 
Medical technologies encompass data centers, medical 
devices, software, drugs, IT services, public clouds, cyber-
security, communication services, surgical procedures, 
and Internet of things.

The medical technology market is growing fast in Asia, 
with different and bulky products available on almost all 
global markets. As a result, the global market for medical 
devices only is projected to grow from USD 455.34 billion 
in 2021 to USD 657.98 billion in 2028.

The key challenges humping the development of medical 
technology are biomedical complexity, standardization, 

FIGURE 23. The nine stages of the Big Data analytics lifecycle.150

FIGURE 24. Application areas of Big Data technology in medicine.146



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FIGURE 25. Big Data architecture for health system.148

FIGURE 25. Big Data architecture for health system.148



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cybersecurity and data privacy, higher starting costs, and 
regulatory and environmental consideration.

The revolution of healthcare technology applications 
in medical services requires knowledge and skills in as-
sessment, planning, procurement, inventory management, 
installation, and maintenance. Therefore, healthcare pro-
viders need to be watchful about Healthcare Technology 
Assessment (HTA) to ensure evidence about safety, effec-
tiveness, relevance, technology outcomes, and alternative 
technologies when running a particular technology. HTA 
is a multidisciplinary process that summarizes informa-
tion about the medical, social, economic, and ethical 
issues related to using health technology systematically, 
transparent, unbiased, and robustly. 

According to World Health Organization, only 70 coun-
tries worldwide have a National Agency or committee that 
provides HTA reports to the Ministry of Health, among 
which only 3 countries come from Africa (Benin, Mali and 
South Africa). Governments are therefore encouraged to 
adopt HTA programs because they provide information to 
support decisions about priorities in healthcare. Further-
more, HTA involves different parties, including patients' 
experience, caregivers, policymakers, physicians, HTA 
agencies, clinical engineering industry representatives, 
payers, pharma groups, and finance managers. 

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