본문으로 이동
인공지능 · 임상 연구 · 의료 혁신

이 언어로 번역된 제목이 없어 원문을 표시합니다.

Predictive Analytics in Remote Patient Monitoring: Opportunities, Equity, and Clinical Safety

저자(들)

  • Changhong 저자

;

remote patient monitoring; artificial intelligence; patient safety; health equity; implementation; clinical evaluation

초록

Background: The adoption of remote patient monitoring in home-based care, chronic disease management, and hospital-at-home services creates opportunities to improve clinical services, but technical performance alone does not establish patient benefit. Objective: To critically examine applications, evidence, safety, equity, and implementation of remote patient monitoring. Approach: This narrative review develops an analytical synthesis of established clinical AI principles and reporting guidance; it does not report a systematic search, a new dataset, or an empirical trial. Findings: Key opportunities include early deterioration alerts, follow-up prioritization, and longitudinal risk estimation. Important limitations include missingness, device adherence, and changes in individual baselines, as well as alarm fatigue, measurement error, and delayed escalation. Responsible adoption requires shared escalation rules, patient consent, and clinician accountability, transparent reporting, and evaluation of timely intervention, avoidable admissions, patient burden, and false alarms. Conclusion: The clinical value of remote patient monitoring depends on fit with the care pathway, prospective evaluation, accountable human oversight, and sustained monitoring after deployment.

##submission.citations##

Inglis, S. C., Clark, R. A., Dierckx, R., Prieto-Merino, D., & Cleland, J. G. F. (2015). Structured telephone support or non-invasive telemonitoring for patients with heart failure. Cochrane Database of Systematic Reviews, 2015(10), CD007228. https://doi.org/10.1002/14651858.CD007228.pub3

Kvedar, J., Coye, M. J., & Everett, W. (2014). Connected health: A review of technologies and strategies to improve patient care with telemedicine and telehealth. Health Affairs, 33(2), 194–199. https://doi.org/10.1377/hlthaff.2013.0992

Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447–453. https://doi.org/10.1126/science.aax2342

Steinhubl, S. R., Muse, E. D., & Topol, E. J. (2015). The emerging field of mobile health. Science Translational Medicine, 7(283), 283rv3. https://doi.org/10.1126/scitranslmed.aaa3487

다운로드 통계

출판됨

2026-10-09