Beyond the Pain Management Clinic: The Role of AI-Integrated Remote Patient Monitoring in Chronic Disease Management - A Narrative Review.

IF 2.5 3区 医学 Q2 CLINICAL NEUROLOGY
Journal of Pain Research Pub Date : 2024-12-11 eCollection Date: 2024-01-01 DOI:10.2147/JPR.S494238
Prachi M Patel, Maja Green, Jennifer Tram, Eugene Wang, Melissa Zhu Murphy, Alaa Abd-Elsayed, Krishnan Chakravarthy
{"title":"Beyond the Pain Management Clinic: The Role of AI-Integrated Remote Patient Monitoring in Chronic Disease Management - A Narrative Review.","authors":"Prachi M Patel, Maja Green, Jennifer Tram, Eugene Wang, Melissa Zhu Murphy, Alaa Abd-Elsayed, Krishnan Chakravarthy","doi":"10.2147/JPR.S494238","DOIUrl":null,"url":null,"abstract":"<p><p>Remote Patient Monitoring (RPM) stands as a pivotal advancement in patient-centered care, offering substantial improvements in the diagnosis, management, and outcomes of chronic conditions. Through the utilization of advanced digital technologies, RPM facilitates the real-time collection and transmission of critical health data, enabling clinicians to make prompt, informed decisions that enhance patient safety and care, particularly within home environments. This narrative review synthesizes evidence from peer-reviewed studies to evaluate the transformative role of RPM, particularly its integration with Artificial Intelligence (AI), in managing chronic conditions such as heart failure, diabetes, and chronic pain. By highlighting advancements in disease-specific RPM applications, the review underscores RPM's versatility and its ability to empower patients through education, shared decision-making, and adherence to therapeutic regimens. The COVID-19 pandemic further emphasized the importance of RPM in ensuring healthcare continuity during systemic disruptions. The integration of AI with RPM has refined these capabilities, enabling personalized, real-time data collection and analysis. While chronic pain management serves as a focal area, the review also examines AI-enhanced RPM applications in cardiology and diabetes. AI-driven systems, such as the NXTSTIM EcoAI™, are highlighted for their potential to revolutionize treatment approaches through continuous monitoring, timely interventions, and improved patient outcomes. This progression from basic wearable devices to sophisticated, AI-driven systems underscores RPM's ability to redefine healthcare delivery, reduce system burdens, and enhance quality of life across multiple chronic conditions. Looking forward, AI-integrated RPM is expected to further refine disease management strategies by offering more personalized and effective treatments. The broader implications, including its applicability to cardiology, diabetes, and pain management, showcase RPM's capacity to deliver automated, data-driven care, thereby reducing healthcare burdens while enhancing patient outcomes and quality of life.</p>","PeriodicalId":16661,"journal":{"name":"Journal of Pain Research","volume":"17 ","pages":"4223-4237"},"PeriodicalIF":2.5000,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11646407/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Pain Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/JPR.S494238","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Remote Patient Monitoring (RPM) stands as a pivotal advancement in patient-centered care, offering substantial improvements in the diagnosis, management, and outcomes of chronic conditions. Through the utilization of advanced digital technologies, RPM facilitates the real-time collection and transmission of critical health data, enabling clinicians to make prompt, informed decisions that enhance patient safety and care, particularly within home environments. This narrative review synthesizes evidence from peer-reviewed studies to evaluate the transformative role of RPM, particularly its integration with Artificial Intelligence (AI), in managing chronic conditions such as heart failure, diabetes, and chronic pain. By highlighting advancements in disease-specific RPM applications, the review underscores RPM's versatility and its ability to empower patients through education, shared decision-making, and adherence to therapeutic regimens. The COVID-19 pandemic further emphasized the importance of RPM in ensuring healthcare continuity during systemic disruptions. The integration of AI with RPM has refined these capabilities, enabling personalized, real-time data collection and analysis. While chronic pain management serves as a focal area, the review also examines AI-enhanced RPM applications in cardiology and diabetes. AI-driven systems, such as the NXTSTIM EcoAI™, are highlighted for their potential to revolutionize treatment approaches through continuous monitoring, timely interventions, and improved patient outcomes. This progression from basic wearable devices to sophisticated, AI-driven systems underscores RPM's ability to redefine healthcare delivery, reduce system burdens, and enhance quality of life across multiple chronic conditions. Looking forward, AI-integrated RPM is expected to further refine disease management strategies by offering more personalized and effective treatments. The broader implications, including its applicability to cardiology, diabetes, and pain management, showcase RPM's capacity to deliver automated, data-driven care, thereby reducing healthcare burdens while enhancing patient outcomes and quality of life.

远程病人监护(RPM)是以病人为中心的医疗服务的一个重要进步,它大大改善了慢性病的诊断、管理和治疗效果。通过利用先进的数字技术,RPM 可促进关键健康数据的实时收集和传输,使临床医生能够做出迅速、明智的决定,从而提高患者的安全和护理水平,尤其是在家庭环境中。这篇叙述性综述综合了同行评审研究的证据,以评估 RPM 的变革性作用,特别是其与人工智能(AI)的整合,在管理心力衰竭、糖尿病和慢性疼痛等慢性疾病方面的作用。通过重点介绍针对特定疾病的 RPM 应用进展,该综述强调了 RPM 的多功能性及其通过教育、共同决策和坚持治疗方案增强患者能力的能力。COVID-19 大流行进一步强调了 RPM 在系统中断期间确保医疗保健连续性的重要性。人工智能与 RPM 的整合完善了这些功能,实现了个性化的实时数据收集和分析。虽然慢性疼痛管理是一个重点领域,但本综述还探讨了人工智能增强型 RPM 在心脏病学和糖尿病方面的应用。NXTSTIM EcoAI™ 等人工智能驱动的系统因其通过持续监测、及时干预和改善患者预后彻底改变治疗方法的潜力而备受瞩目。从基本的可穿戴设备发展到复杂的人工智能驱动系统,凸显了 RPM 重新定义医疗保健服务、减轻系统负担和提高多种慢性疾病患者生活质量的能力。展望未来,整合了人工智能的 RPM 预计将提供更加个性化和有效的治疗,从而进一步完善疾病管理策略。其更广泛的影响,包括其在心脏病学、糖尿病和疼痛管理方面的适用性,展示了 RPM 提供自动化、数据驱动型护理的能力,从而减轻医疗负担,同时提高患者的治疗效果和生活质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of Pain Research
Journal of Pain Research CLINICAL NEUROLOGY-
CiteScore
4.50
自引率
3.70%
发文量
411
审稿时长
16 weeks
期刊介绍: Journal of Pain Research is an international, peer-reviewed, open access journal that welcomes laboratory and clinical findings in the fields of pain research and the prevention and management of pain. Original research, reviews, symposium reports, hypothesis formation and commentaries are all considered for publication. Additionally, the journal now welcomes the submission of pain-policy-related editorials and commentaries, particularly in regard to ethical, regulatory, forensic, and other legal issues in pain medicine, and to the education of pain practitioners and researchers.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信