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European Journal of Applied Sciences – Vol. 11, No. 6
Publication Date: December 25, 2023
DOI:10.14738/aivp.116.15309
Olugboja, A. (2023). A Review on the Challenges of Artificial Intelligence in HealthCare Systems in Rural Areas. European Journal
of Applied Sciences, Vol - 11(6). 128-133.
Services for Science and Education – United Kingdom
A Review on the Challenges of Artificial Intelligence in HealthCare
Systems in Rural Areas
Adedeji Olugboja
Eswatini Medical Christian University
ABSTRACT
This paper examines the challenges of implementing AI technology in rural
healthcare systems. Despite the potential benefits of AI, rural healthcare systems
face significant obstacles, including limited access to technology, a lack of resources,
and a shortage of trained personnel. The essay argues that addressing these
challenges is critical to ensure that rural communities have access to high-quality
healthcare services. The solutions suggested include government funding,
education and training programs, and partnerships with technology companies. By
adopting these solutions, rural healthcare systems can harness the potential
benefits of AI technology and improve patient outcomes. This paper concludes by
suggesting directions for future research, including investigating additional
solutions for overcoming the challenges of AI implementation in rural healthcare
systems and exploring the long-term impact of AI technology on patient outcomes
in rural areas.
Keywords: Healthcare, Artificial Intelligence, Rural, Challenges, Technology
INTRODUCTION
AI, or artificial intelligence, is an emerging technology that has the potential to revolutionize
healthcare by improving diagnosis, treatment, and patient outcomes (Wright et al., 2021). AI
can analyze vast amounts of medical data and provide personalized recommendations for
patients, leading to more accurate diagnoses and better treatment plans. However, while AI has
been widely adopted in urban healthcare systems, its implementation in rural healthcare
systems faces unique challenges.
It is important to consider the challenges of AI implementation in rural healthcare systems
because these areas face a variety of unique obstacles, such as limited access to technology,
fewer resources, and a shortage of trained personnel (Bates et al., 2021). Addressing these
challenges is crucial to ensure that rural communities can benefit from the same advancements
in healthcare as urban areas.
In this paper, I will explore the challenges of implementing AI in rural healthcare systems and
examine the potential solutions that can help overcome these challenges. I will analyze case
studies of AI implementation in rural healthcare systems and discuss the successes and failures
of these implementations. Through this analysis, I will argue that while there are significant
challenges to implementing AI in rural healthcare systems, there are also viable solutions that
can help bridge the gap between rural and urban healthcare.
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Olugboja, A. (2023). A Review on the Challenges of Artificial Intelligence in HealthCare Systems in Rural Areas. European Journal of Applied Sciences,
Vol - 11(6). 128-133.
URL: http://dx.doi.org/10.14738/aivp.116.15309
OVERVIEW OF AI IN HEALTHCARE
AI, or artificial intelligence, is a technology that involves the development of intelligent
machines that can perform tasks that normally require human intelligence, such as learning,
reasoning, and problem-solving (Hannun et al., 2019). In healthcare, AI can be used in various
ways, such as analyzing patient data, diagnosing diseases, and developing treatment plans.
One of the benefits of using AI in healthcare systems is improved efficiency. AI can analyze vast
amounts of patient data in a short period of time, which can save healthcare professionals time
and improve their productivity. Additionally, AI can automate tasks that are time-consuming
or repetitive, such as administrative tasks, allowing healthcare professionals to focus on
providing care to patients (Topol, 2019).
Another benefit of using AI in healthcare systems is improved accuracy. AI can analyze patient
data with a level of precision that is difficult for humans to achieve, which can lead to more
accurate diagnoses and treatment plans. Additionally, AI can help healthcare professionals
identify patterns and trends in patient data that might be missed by human analysis, which can
improve the overall quality of care (Obermeyer et al., 2019).
AI can also improve patient outcomes by providing personalized treatment plans. By analyzing
patient data, AI can identify the most effective treatments for individual patients based on their
medical history, genetics, and other factors. This can lead to better health outcomes for patients
and a reduction in healthcare costs (Obermeyer et al., 2019).
In summary, AI has several benefits for healthcare systems, including improved efficiency,
accuracy, and personalized treatment plans. By harnessing the power of AI, healthcare
professionals can provide better care to patients, improve patient outcomes, and reduce
healthcare costs.
CHALLENGES OF AI IMPLEMENTATION IN RURAL HEALTHCARE SYSTEMS
Despite the potential benefits of AI in healthcare, rural healthcare systems face several
challenges in implementing AI technologies. One of the primary challenges is limited access to
technology. Rural healthcare facilities may lack the necessary infrastructure to support AI
technologies, such as high-speed internet and advanced computer systems (Rogers et al., 2018).
This can make it difficult to access and analyze patient data, which is necessary for AI to function
effectively.
Another challenge is a lack of resources. Rural healthcare systems may have limited funding
and staffing resources, which can make it difficult to invest in and implement AI technologies.
Additionally, the cost of implementing AI can be high, which can be a barrier for rural healthcare
facilities with limited budgets (Gamble et al., 2020).
Finally, rural healthcare systems may face a shortage of trained personnel. AI requires
specialized knowledge and expertise to implement and maintain, which can be difficult to find
in rural areas (Rogers et al., 2018). Additionally, training healthcare professionals to use AI
technologies can be time-consuming and costly.
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These challenges have affected the implementation of AI in rural healthcare systems in several
ways. For example, a study by Gamble et al. (2020) found that rural healthcare facilities were
less likely to use AI technologies compared to urban facilities, in part due to limited resources
and funding. Similarly, a study by Rogers et al. (2018) found that rural healthcare systems faced
challenges in accessing and analyzing patient data, which made it difficult to implement AI
technologies that rely on such data.
In summary, rural healthcare systems face several challenges in implementing AI technologies,
including limited access to technology, lack of resources, and a shortage of trained personnel.
These challenges can make it difficult for rural healthcare facilities to invest in and implement
AI, which can impact the quality of care that they are able to provide to patients.
CASE STUDIES
While there are challenges to implementing AI in rural healthcare systems, there have been
some successful implementations. For example, telemedicine using AI has been implemented
in some rural areas to provide remote access to healthcare services. One study by Aoki et al.
(2019) found that using AI to interpret echocardiograms remotely allowed for more accurate
diagnosis of cardiac conditions in rural patients, which improved patient outcomes. However,
one challenge in implementing telemedicine using AI in rural areas is limited access to high- speed internet, which can affect the quality of video and audio during telemedicine
appointments (Gamble et al., 2020).
AI has also been used to improve patient outcomes through predictive analytics. For example,
one study by Wong et al. (2020) found that using machine learning to predict the risk of
readmission among rural patients with heart failure improved patient outcomes and reduced
healthcare costs. However, one challenge in implementing predictive analytics using AI in rural
areas is a lack of patient data, which can affect the accuracy of predictions (Gamble et al., 2020).
Another successful implementation of AI in rural healthcare is the use of virtual assistants to
improve patient engagement and education. For example, one study by Manchaiah et al. (2019)
found that using a virtual assistant to provide hearing healthcare education to rural patients
improved patient knowledge and satisfaction with healthcare services. However, one challenge
in implementing virtual assistants using AI in rural areas is a shortage of trained personnel who
can maintain and update the technology (Rogers et al., 2018). The success of these
implementations of AI in rural healthcare systems can be attributed to several factors. First,
these implementations were designed to address specific healthcare needs in rural areas, such
as limited access to specialized healthcare services or a shortage of healthcare professionals.
Second, these implementations were often tailored to the unique characteristics of rural
healthcare systems, such as limited resources and funding. Finally, these implementations often
involved collaboration between healthcare professionals, technology companies, and
community stakeholders to ensure that the technology was appropriate and effective for rural
patients (Gamble et al., 2020).
While there are challenges to implementing AI in rural healthcare systems, there have been
successful implementations of AI technologies in some rural areas. These implementations
have addressed specific healthcare needs in rural areas, tailored to the unique characteristics