E-prescription In Healthcare System Using Cloud

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 10 Issue: 12 |Dec 2023 www.irjet.net p-ISSN: 2395-0072
© 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 403
E-prescription In Healthcare System Using Cloud
Nameet Ahire, Sakshi Gawade, Vishal Ghosh, Nishita Gole
Rajiv Gandhi Institute Of Technology, Mumbai 400053
Prof. Bhushan M. Patil, Dept. of Computer Engineering, Rajiv Gandhi Institute Of Technology, Maharashtra, India
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Abstract - This research paper investigates the
implementation of a secure electronic prescription system in
healthcare using cloud technology. Data management in the
health care system is mandatory. The study focuses on
addressing data security and confidentiality issues in
electronic prescription processes. Through the integration
of cloud services, the proposed system aims to increase the
efficiency and availability of healthcare services while
ensuring robust protection of sensitive patient information.
The paper delves into the technical aspects of secure data
transfer, storage and access control and contributes
valuable insights into the evolving healthcare technology
landscape. The model proposed a system based on a web
application, through which the doctor has the ability to
prescribe to patients and other users, such as receptionists,
pharmacists and administrators, interact with the system
through their web accessibility. Overall, this work provides a
better solution to healthcare management. data and also
provide an easy way to interact with the system
Key Words: E-prescription, Healthcare System, Cloud,
Pharmacy, Chat-bot.
1. INTRODUCTION
The integration of digital technologies in healthcare is
crucial for increasing efficiency, availability, and safety.
Electronic prescribing systems are changing the way
doctors create and transmit prescriptions. This research
paper explores the convergence of e-prescribing systems
with cloud computing to address security issues and
improve healthcare service efficiency. The traditional
paper prescription model is being replaced by electronic
prescriptions, offering a more efficient and durable
process. However, this transition raises data security and
privacy concerns. The research aims to clarify how cloud
technology can be strategically used to strengthen the
security architecture of electronic prescription systems,
ensuring confidentiality, integrity, and availability of
patient data.
Cloud computing is a promising solution for healthcare
systems to enhance their electronic prescription
infrastructure. It improves availability, interoperability,
and protects patient data from cyber threats. This
research explores strategies and technologies for creating
a robust cloud-based framework for healthcare e-
prescribing. It also addresses regulatory environment and
compliance requirements related to e-prescribing
systems. As the healthcare industry digitizes,
understanding and mitigating risks associated with
electronic prescriptions is crucial. The research aims to
contribute insights for a safer and more resilient e-
prescribing ecosystem, strengthening trust among
healthcare professionals, patients, and stakeholders.
2. LITERATURE REVIEW
The introduction of electronic prescription (e-
prescription) systems in healthcare, facilitated by cloud
technology, has transformed medication management and
improved patient care. The traditional system of paper
prescriptions has given way to electronic prescribing,
which has simplified the process of drug administration.
Early studies on the development of electronic prescription
systems lay the groundwork for understanding the
challenges and opportunities associated with this
transition.
[1]The traditional way of prescribing, which relies on
handwritten or printed paper scripts, is characterized by
manual processes, limited availability, communication
problems, dependence on physical storage and security
issues. In contrast, an e-prescription using electronic
formats and digital systems offers a more efficient and
accurate alternative. With digital automation, instant
access to patient records, better communication between
healthcare providers and pharmacies, efficient record
keeping, improved security measures and seamless
integration with healthcare systems, electronic
prescription systems contribute to a safer, more efficient
and technologically advanced approach. to the
management of medicines in the healthcare sector.
[2]Machine learning (ML)-based electronic prescription
systems are revolutionizing medication management
through the use of advanced algorithms and data analytics.
Through ML, these systems analyze large datasets, learn
from patient history, treatment outcomes and drug
interactions, and assist healthcare providers in creating
highly personalized and optimized prescriptions. These
systems can dynamically adapt to evolving medical
knowledge and patient conditions, offer real-time decision
support, reduce the likelihood of prescribing errors, and
increase drug safety. ML-based e-prescribing not only
improves the accuracy of treatment plans, but also
contributes to a more active and individualized approach
to patient care, which represents a significant advance in
the field of health technology.

[3]Artificial intelligence-based e-prescribing systems
represent cutting-edge advances in healthcare technology
and seamlessly integrate artificial intelligence to improve
the prescribing process. These systems use sophisticated
algorithms and machine learning to analyze patient health
data, medical history and treatment outcomes, enabling
healthcare providers to create intelligent and personalized
prescriptions. AI algorithms can identify potential drug
interactions, predict patient responses to drugs, and tailor
recommendations based on evolving medical knowledge.
By automating and optimizing the prescribing workflow,
AI-based e-prescribing systems not only increase
efficiency, but also contribute to improved patient
outcomes, medication adherence and overall healthcare
quality through proactive decision support.
[4]Cloud technology has transformed healthcare by
offering a dynamic and scalable platform for data storage,
access and collaboration. In healthcare, cloud solutions
enable seamless sharing of patient records, diagnostic
images and medical information between healthcare
providers, improving care coordination and decision-
making. The cloud enables healthcare organizations to
efficiently manage and analyze vast amounts of data,
expand research capabilities, and support innovation in
personalized medicine. In addition, cloud solutions
increase the flexibility and availability of healthcare
services, allowing doctors to securely access patient
information from anywhere and supporting telemedicine
initiatives. Despite data security and privacy concerns, the
integration of cloud technology in healthcare continues to
play a key role in modernizing healthcare delivery,
promoting interoperability and ultimately improving
patient outcomes.
[5]Cloud e-prescription systems offer a number of
benefits, streamlining medication management by
providing immediate and secure access to patient records,
promoting effective communication between healthcare
providers and pharmacies, and increasing overall
interoperability. The scalability of cloud technology
enables seamless integration with electronic health
records, contributing to a more comprehensive healthcare
ecosystem. However, these benefits come with security and
privacy concerns. The potential risk of unauthorized access
to sensitive patient data raises data security concerns,
requiring robust encryption and authentication measures.
Privacy concerns also revolve around the transmission and
storage of electronic prescriptions, which require strict
adherence to regulatory standards to ensure patient
confidentiality. Achieving a balance between benefits and
addressing security and privacy concerns is critical to the
widespread adoption and success of cloud-based e-
prescribing systems in ensuring both efficiency and patient
data protection.
In conclusion, the integration of cloud technology into
electronic prescription systems has ushered in a new era of
efficiency and accessibility in healthcare.
3. METHODOLOGY
To create a cloud website, we need cloud services. We
use Amazon's AWS cloud service in our project. AWS is a
well-known cloud service provider in the cloud industry. It
provides some free services that are enough to run our
small project, but in the future we may use the AWS pay-
as-you-go service to make our website more efficient and
productive. We also need a chat-bot framework to provide
e-texts to website users. So let's start with Amazon's AWS
service.
[1] VPC - Amazon VPC, part of AWS, offers a
customizable and controlled virtual networking
environment in the cloud. Key elements include CIDR
Blocks for defining private IPv4 address ranges, subnets to
organize resources, and route tables to manage traffic flow.
Internet Gateways enable connectivity between VPC
resources and the internet. NAT Gateways/Instances allow
outbound traffic from private subnets. Security Groups
and Network ACLs control traffic, with the former
associated with instances and the latter with subnets.
VPC peering connects separate VPCs securely, and VPC
Endpoints provide private connections to AWS services.
VPN and Direct Connect establish secure links between
on-premises data centers and VPCs. Amazon VPC offers
flexibility in designing and configuring networks to meet
specific application and security needs.
[2] Elastic Compute Cloud - Amazon EC2 is a central
service provided by Amazon Web Services (AWS) that
enables users to rent virtual servers, known as instances,
in the cloud. These instances can be customized to host
applications, run software, or process data. EC2 offers a
variety of instance types to meet diverse computing needs,
ranging from general-purpose instances to specialized
instances optimized for specific tasks like computation,
memory, storage, or GPU-intensive workloads.
When you launch an EC2 instance, you can choose from
a selection of pre-configured Amazon Machine Images
(AMIs) or create your own custom AMIs. Each instance is
associated with a specific instance type, which determines
its computing power, memory, and storage capacity.
Key features of EC2 include the ability to scale instances
up or down based on demand, pay only for the compute
capacity you use, and choose from a global network of data
centers, with multiple availability zones within each
region to enhance reliability and fault tolerance. EC2
instances are often used in conjunction with other AWS
services to build scalable and resilient applications.

[3]Flow XO - Flow XO is a cloud-based automation
platform designed to streamline the development of chat-
bots and automation workflows. With its user-friendly
interface that requires little to no coding, the platform
facilitates the creation of chat-bots for various applications.
Additionally, Flow XO provides robust integration
capabilities, allowing businesses to connect with different
services seamlessly. The platform also incorporates
analytics tools, enabling users to gain insights into chat-
bot performance. Flow XO finds applications in optimizing
operations, delivering efficient customer support, and
automating repetitive tasks across a range of messaging
platforms.
Flow XO employs a visual flow editor resembling a
decision tree to create chat-bots without coding. Triggers
initiate the conversation, leading to branches with
conditional logic for personalized responses. The platform
integrates external services, handles user inputs, and
allows for iterative design. Testing and analytics tools aid
in optimization, making it user-friendly for developing
dynamic and context-aware chat-bots.
3.1MODELLING
The system consists of several key entities, each of which
plays a different role in its functionality. The
administrator, or admin, assumes responsibility for
managing access to the pharmacy, securely uploading
databases to the cloud, and overseeing physician
inventory. With a focus on security, the admin serves as a
central figure in keeping the system running smoothly.
Doctors within the system use websites with cloud-based
security features to prescribe treatment to patients. They
also contribute valuable feedback to the system and
increase the overall quality and efficiency of healthcare
services provided through the platform.
Patients interact with the system primarily through
websites, where they can book appointments, order
medications, and share feedback about their experiences.
This direct engagement allows patients to effectively and
conveniently manage their health needs.
Pharmacists, another integral entity in the system,
contribute to the health database by securely adding
billing information. In addition, they play a key role in
generating patient bills and managing drug inventory,
ensuring accurate and efficient financial transactions and
inventory control within the pharmacy system. The
collaboration of these different entities creates a complex
and sophisticated health care ecosystem.
Fig 3.1: System Design
[1] First Layer - Essential Characteristics:
In the implementation phase, administrators use the on-
demand self-service to efficiently manage pharmacy access
and seamlessly upload databases, eliminating the need for
direct human interaction. This not only streamlines
processes, but also increases overall efficiency and
responsiveness and facilitates immediate provisioning of
resources.
The network-wide access model is implemented by
allowing users, including physicians, patients, and
pharmacists, to access the system through a variety of
devices using standard mechanisms. This approach
ensures cross-platform accessibility and promotes
flexibility and convenience in the user experience.
In the resource pooling model, the health care database is
shared among users, which promotes efficient use of
resources. This collaborative approach optimizes the use of
resources, leading to economies of scale and specialization,
ultimately benefiting the entire system.
A fast elasticity model is built into the system and allows it
to adapt to changing load by dynamically adjusting the cost
of computing resources based on usability. This
implementation provides flexibility and cost-effectiveness
by allowing the system to scale resources up or down as
needed, ensuring optimal performance and resource
utilization in response to changing demands.
[2] Second Layer - Service Models:
Infrastructure as a Service (IaaS) is implemented through
cloud infrastructure that provides the necessary support
for tasks such as database storage and management,
especially for administrators. A significant advantage of
IaaS lies in the provision of scalable and virtualized
computing resources, enabling flexible and efficient
resource allocation.

Platform as a Service (PaaS) is used when doctors
prescribe treatment to patients through a web-based
platform with cloud security. This implementation
simplifies the application development and deployment
process for clinicians, streamlines their workflow, and
increases overall efficiency. Software as a Service (SaaS) is
realized when patients interact with a cloud healthcare
website for appointments, orders and feedback. The
advantage of SaaS is evident in its delivery of software
applications over the Internet, which eliminates the need
for local installations and provides users with convenient
and affordable solutions.
Fig 3.2: Cloud Architecture
At the bottom layer, different deployment models are
explored. The Public Cloud model hosts the entire
electronic prescription system on a public cloud that is
accessible to authorized users from any location. This
approach ensures cost efficiency and scalability with
resources shared by multiple users. A private cloud
deployment involves an administrator managing the
healthcare database in the private cloud, prioritizing
security and offering better privacy and control over
sensitive user information. Hybrid cloud integration
combines both public and private clouds within the system.
This model optimizes workload placement and data
distribution based on specific requirements, while striking
a balance between availability and security.
Finally, the community cloud model is implemented so that
authorized users such as doctors, patients and pharmacists
collaborate on shared resources. This encourages resource
sharing and collaboration within a particular community
and caters to the unique needs and dynamics of that user
group.
Fig 3.3: Chat-bot Architecture
Incorporating an AI-based chat-bot is a key part of the
healthcare system and serves the essential function of
communicating with patients in real time. Designed to
work seamlessly, the chat-bot becomes especially
invaluable during emergency situations, providing
patients with quick and accurate responses, essential
instructions and immediate assistance. In addition to
emergency situations, the chat-bot extends its usefulness
by streamlining the process of purchasing medicines
online. Patients benefit from this technology by receiving
information about medicines, alternatives and guided
support throughout the purchase journey on the
pharmacy platform. In essence, an AI-powered chat-bot
not only increases communication efficiency, but also
plays a key role in facilitating and optimizing online drug
sourcing, thereby contributing to more responsive and
user-friendly healthcare.
AI as a Service (AIaaS) is effectively implemented by
integrating an AI-based chat-bot into the system through
platforms like Flow XO. This integration enables real-time
communication between the AI chat-bot and patients,
leading to a number of benefits. One significant benefit is
improved patient engagement, as a chat-bot facilitates
seamless and immediate interaction with users. During
emergency situations, an AI chat-bot serves as an essential
communication tool that enables patients to receive quick
responses and appropriate instructions, thereby
improving the overall responsiveness of the healthcare
system.
In addition, AIaaS optimizes the process of purchasing
medicines online by providing valuable assistance to
patients through a chat-bot. This includes offering
information about medicines, suggesting alternatives and
guiding users through the purchase process on the
pharmacy platform. By streamlining these interactions,
the AI chat-bot contributes to a more efficient and user-
friendly experience for patients who wish to purchase
medicines online. In short, implementing AI as a service
with an AI-based chat-bot significantly improves patient
interactions, emergency communication, and the overall
process of online drug purchases within the healthcare
system.

Fig 3.4: System Flow
The patient interaction flow within the healthcare system
follows a structured scenario where patients engage with
the AI chat-bot in case of emergency. The chat-bot will
quickly assess the situation, offer immediate guidance to
the patient and, if necessary, immediately alert the
relevant healthcare professionals. This streamlined
process ensures that patients receive prompt and
appropriate help at critical moments, increasing the
overall responsiveness of the healthcare system.
On the contrary, the online drug purchase flow is activated
when the patient intends to buy the drug online. In this
scenario, a chat-bot proves useful by helping the patient
with detailed information about available drugs, their
prices and guiding them through the purchasing process.
Once the patient makes a choice, the chat-bot seamlessly
integrates this information into the prescription and sends
it to the pharmacy. This integrated approach not only
simplifies the process of purchasing medicines online, but
also ensures that the prescription is effectively
communicated to the pharmacy, contributing to a
seamless and user-friendly experience for patients.
The overarching benefit of integrating a chat-bot into a
system is twofold. First, Faster Response ensures that
patients receive immediate and accurate assistance during
emergencies, facilitating timely action. Second, the
Efficient Medicine Purchase feature allows patients to
navigate the online drug purchase process effortlessly
under the guidance of a chat-bot, streamlining the entire
process and improving the user experience within the
healthcare system.
4. CONCLUSIONS
This study focuses on the development of an online
platform that revolutionizes patient-physician interaction
by enabling seamless connectivity regardless of
geographic limitations. The platform makes it easy for
patients to connect with doctors from anywhere and gives
them the convenience of getting medical advice and
prescriptions at their doorstep. This not only improves the
availability of health services, but also enables individuals
to seek medical help at any time and breaks down barriers
to timely access to health care.
A core aspect of this study is the incorporation of cloud
computing to enhance system performance, especially in
terms of security. The use of cloud computing
infrastructure ensures a robust and secure environment
for storing and managing sensitive health data. The use of
cloud solutions not only increases the scalability and
efficiency of the platform, but also significantly contributes
to the protection of patient information and strengthens
trust in the online healthcare ecosystem. The integration
of cloud computing represents a strategic step to optimize
system performance, ensure data integrity, and address
key security issues in providing healthcare services
through an online platform.
5. FUTURE WORK
Looking ahead, the future development of this project
includes the implementation of a product tracking system
designed to increase transparency in the drug supply
process. By incorporating this system, users will be able to
track the status and location of their medications and
provide real-time insight into the delivery route. This not
only ensures a more reliable and responsible
pharmaceutical supply chain, but also gives patients
confidence in the timely delivery of prescribed medicines.
In addition, improvements to the invoicing process within
the platform are planned to streamline and optimize
financial transactions related to healthcare services. The
use of modern and advanced blockchain methods is part of
this improvement strategy, which provides a secure and
decentralized framework that ensures the integrity and
transparency of financial transactions within the
healthcare platform.
The project further envisages expanding its scope to
include comprehensive data on the Blood Bank for
emergency purposes. This addition serves as a critical
feature that improves the usability of the platform in
emergency healthcare situations. By integrating blood
bank data, the system aims to provide quick and accessible
information for healthcare professionals and patients who
need blood-related medical procedures. This strategic
expansion is in line with the broader goal of creating a

more holistic and versatile healthcare platform that not
only addresses routine medical needs but also addresses
emergency scenarios and contributes to a more robust and
comprehensive healthcare infrastructure.
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