Annotated Bibliography

Abstract

Modern healthcare faces a range of challenges and opportunities, perhaps none more intriguing than the possibilities afforded the industry thanks to how advancements in technology transforming remote patient monitoring and chronic disease management. At this intersection of artificial intelligence (AI) and remote patient monitoring (RPM) the healthcare industry faces a unique chance to use technological advancements in healthcare to address critical challenges in patient care and management. This research was guided by the question: How does AI enhance RPM systems, and what are the implications for future healthcare delivery? The findings of this research reveal that AI can significantly improve RPM by enabling personalized patient monitoring, early detection of health deterioration, and efficient management of chronic diseases. These innovations, moreover, promise to reduce hospital readmissions and facilitate proactive healthcare. However, the integration of AI into RPM also presents challenges that need to be considered: these include data privacy concerns, the need for advanced algorithms capable of handling diverse health data, and the assurance of equitable access to these technologies. The thesis derived from this research posits that AI-enhanced RPM systems represent a transformative approach to healthcare, offering unprecedented opportunities for improving patient outcomes and operational efficiency. Yet, this potential is contingent upon addressing ethical, technological, and accessibility challenges. The implications of this research suggest a pathway for future exploration focusing on developing standardized frameworks for AI in RPM, enhancing data security measures, and ensuring these advancements are accessible across diverse patient populations. This research shows the need for having a cross-discipline approach that uses knowledge from technology, healthcare, and policy, to understand fully the benefits of AI-enhanced RPM in the modern healthcare ecosystem.

Annotated Bibliography

Chauhan, P., Bali, A., & Kaur, S. (2024). Breaking Barriers for Accessible Health Programs: The

Role of Telemedicine in a Global Healthcare Transformation. InTransformative Approaches to Patient Literacy and Healthcare Innovation(pp. 283-307). IGI Global. DOI:10.4018/979-8-3693-3661-8.ch014

This chapter explores telemedicine's impact on global healthcare, emphasizing how it improves access and delivery, especially in remote areas. It covers telemedicine's evolution, benefits like cost and time efficiency, and its vital role during the COVID-19 pandemic. The authors discuss various telemedicine methods, including asynchronous and synchronous consultations, and the importance of technology in patient care. They highlight the potential for telemedicine to address healthcare challenges but note existing barriers to its full implementation and standardization.

Strengths include a comprehensive overview of telemedicine's evolution and its applications during the COVID-19 pandemic, emphasizing cost and time efficiency. However, the chapter could have explored more on the practical challenges of telemedicine implementation, such as infrastructure requirements and the digital divide. Overall, it presents an optimistic view of telemedicine's potential to transform global healthcare, albeit with a need for addressing standardization and consolidation issues.

Farrokhi, M., Taheri, F., Moeini, A., Farrokhi, M., Alireza, M. Z. S., Farahmandsadr, M., ... &

Andevari, M. Y. (2024). Artificial Intelligence for Remote Patient Monitoring: Advancements, Applications, and Challenges.Kindle,4(1), 1-261. Retrieved from http://preferpub.org/index.php/kindle/article/view/Book33

This comprehensive work delves into the integration of Artificial Intelligence (AI) within the sphere of Remote Patient Monitoring (RPM),...

…integration into RPM, showcasing advancements like personalized health monitoring and behavior pattern analysis. However, a potential weakness might be its coverage of implementation challenges and trends, which could benefit from deeper analysis on practical barriers, ethical considerations, and data privacy concerns in deploying AI-driven RPM solutions.

Tak, A. (2024). Population Health Management: Leveraging it for Better Patient Outcomes.

International Journal of Health Sciences, 7(2), 53-67. https://orcid.org/0009-0005-8548-1636

This article examines the impact of integrating information technology (IT) into Population Health Management (PHM) frameworks. It explores how IT tools, including Electronic Health Records (EHRs), telehealth, and AI-driven analytics, can enhance patient care through proactive health interventions and a comprehensive understanding of health trends. The study employs a mixed-method approach, utilizing data analysis tools like Python's scikit-learn and pandas libraries, to evaluate the effectiveness of these technologies in real healthcare settings. Findings suggest that IT advancements significantly improve chronic disease management, preventive healthcare, and patient engagement, while also optimizing resource allocation and operational efficiency within healthcare systems. Tak's work provides valuable insights into the transformative role of IT in PHM, offering theoretical frameworks, policy implications, and practical guidelines for integrating technology-driven strategies effectively in healthcare.

The use of a mixed-method approach strengthens its findings. Still, it could have further explored the challenges and limitations of implementing these technologies, especially regarding data privacy and the digital divide. Overall, the article is a good resource for understanding the intersection of IT and health management, suggesting practical steps for integration while hinting at areas needing further research.