Authors :
Utulu, Emmanuel Chukwugozim
Volume/Issue :
Volume 10 - 2025, Issue 10 - October
Google Scholar :
https://tinyurl.com/24ta8hwh
Scribd :
https://tinyurl.com/mw5kfucw
DOI :
https://doi.org/10.38124/ijisrt/25oct356
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 30 to 40 days to display the article.
Abstract :
Background:
Rural healthcare service delivery in the United States remains a major issue due to a lack of adequate infrastructure,
qualified healthcare practitioners, and facilities. These deficiencies have reduced healthcare access and worsened rural-
urban health disparities. Artificial intelligence have been shown to contribute to healthcare service delivery and its
advancement globally, but its impact in service delivery for rural populations in the United State have been largely
underexplored. This paper addresses this gap by investigating the impact of artificial intelligence in improving healthcare
service delivery, accessibility to healthcare services, and health outcomes of individuals living in rural regions in the United
States.
Methods:
To retrieve relevant literature, JSTOR, Web of Science, Scopus, and PubMed/MEDLINE databases were searched for
relevant articles based on a predetermined inclusion and exclusion criteria. The CASP appraisal tool was used to assess the
quality of the included papers. Thematic analysis was employed to analyze the data extracted from these articles.
Findings:
The database search yielded an initial 57 articles. Following exclusion of duplicate articles and those which does not fit
into the search criteria, 8 articles were determined to meet the inclusion criteria, and subsequently included and subjected
to further analysis. After the included papers were critically analyzed and explored, four key themes were identified. These
themes includes: (i) Patient engagement and adherence to care services (ii) Diagnostic accuracy and timeliness, (iii)
Infrastructure limitations, and (iv) Closing the digital divide.
Conclusion:
This extensive investigation shows that AI has the potential to improve rural US healthcare access, diagnostic precision,
health outcomes, and patient participation. However, infrastructure gaps, algorithmic biases, and digital inequality
currently restrict its transformative potential. Equitable data inclusion, ethical AI design, and rural infrastructural
improvements are needed to overcome these systemic barriers to sustainable healthcare.
Keywords :
Artificial Intelligence, Rural Communities, Healthcare Service Delivery, Healthcare Improvement, Future Outlook, United State of America.
References :
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Background:
Rural healthcare service delivery in the United States remains a major issue due to a lack of adequate infrastructure,
qualified healthcare practitioners, and facilities. These deficiencies have reduced healthcare access and worsened rural-
urban health disparities. Artificial intelligence have been shown to contribute to healthcare service delivery and its
advancement globally, but its impact in service delivery for rural populations in the United State have been largely
underexplored. This paper addresses this gap by investigating the impact of artificial intelligence in improving healthcare
service delivery, accessibility to healthcare services, and health outcomes of individuals living in rural regions in the United
States.
Methods:
To retrieve relevant literature, JSTOR, Web of Science, Scopus, and PubMed/MEDLINE databases were searched for
relevant articles based on a predetermined inclusion and exclusion criteria. The CASP appraisal tool was used to assess the
quality of the included papers. Thematic analysis was employed to analyze the data extracted from these articles.
Findings:
The database search yielded an initial 57 articles. Following exclusion of duplicate articles and those which does not fit
into the search criteria, 8 articles were determined to meet the inclusion criteria, and subsequently included and subjected
to further analysis. After the included papers were critically analyzed and explored, four key themes were identified. These
themes includes: (i) Patient engagement and adherence to care services (ii) Diagnostic accuracy and timeliness, (iii)
Infrastructure limitations, and (iv) Closing the digital divide.
Conclusion:
This extensive investigation shows that AI has the potential to improve rural US healthcare access, diagnostic precision,
health outcomes, and patient participation. However, infrastructure gaps, algorithmic biases, and digital inequality
currently restrict its transformative potential. Equitable data inclusion, ethical AI design, and rural infrastructural
improvements are needed to overcome these systemic barriers to sustainable healthcare.
Keywords :
Artificial Intelligence, Rural Communities, Healthcare Service Delivery, Healthcare Improvement, Future Outlook, United State of America.