REVIEW article
Front. Immunol.
Sec. Autoimmune and Autoinflammatory Disorders : Autoimmune Disorders
This article is part of the Research TopicBig data research, precision medicine and real‑world evidence in autoimmune and rheumatic diseasesView all articles
Remote Patient Monitoring in Autoimmune related Interstitial Lung Diseases: A Narrative Review
Provisionally accepted
Maryam Almoagal1,2
Malik A Althobiani3,4*- 1Respiratory Therapy Department, College of Applied Medical Sciences, King Saud Bin Abdulaziz University for Health Sciences,, Al Ahsa, Saudi Arabia
- 2Respiratory Medicine, Division of Medicine, University College London, London, United Kingdom
- 3Department of Respiratory Therapy, College of Medical Rehabilitation Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
- 4Respiratory Therapy Unit, King Abdulaziz University Hospital, Jeddah, Saudi Arabia
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Autoimmune related interstitial lung disease can worsen between clinic visits, and episodic assessment may miss clinically important change. Digital health extends observation into daily life through home spirometry, wearable sensors, application based patient reported outcomes, and therapist supported telerehabilitation. This Review synthesises recent evidence on feasibility and adherence, data quality and agreement with clinic assessments, patient experience and safety, and service integration for remote monitoring in autoimmune related interstitial lung disease. Device derived signals and patient generated health data show useful agreement with clinic measures when interpreted across repeated time points, and remote monitoring data can reveal actionable trends and support rehabilitation and self management. Important limitations remain, including variability and artefacts, missing data, uneven interoperability, workload implications for services, and inequities in digital access. We outline a practical workflow for adoption that includes enrolment, training, quality checks, alert thresholds, and escalation to the multidisciplinary team, with attention to privacy, cost, and record integration. Remote monitoring can complement standard care by increasing observation frequency and patient support. Priorities for the field are to define clinically meaningful digital endpoints, evaluate effects on outcomes and use of resources, and develop strategies that sustain long term engagement.
Keywords: Interstitial lung disease (ILD), Autoimmune rheumatic diseases, Remote monitor, wearables, artificial intelligence - AI, machine learning
Received: 08 Jun 2025; Accepted: 20 Nov 2025.
Copyright: © 2025 Almoagal and Althobiani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Malik A Althobiani, malthobiani@kau.edu.sa
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.