Evaluating a Remote Monitoring Program for Respiratory Diseases: Prospective Observational Study.

Autor:	Althobiani MA; Respiratory Medicine, University College London, London, United Kingdom.; Interstitial Lung Disease Service, University College London Hospital, London, United Kingdom.; Department of Respiratory Therapy, Faculty of Medical Rehabilitation Sciences, King Abdulaziz University, Jeddah, Saudi Arabia., Ranjan Y; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom., Jacob J; Respiratory Medicine, University College London, London, United Kingdom.; Satsuma Lab, Centre for Medical Image Computing, University College London, London, United Kingdom., Orini M; Institute of Cardiovascular Science, University College London, London, United Kingdom., Dobson RJB; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.; National Institute for Health and Care Research, Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, United Kingdom.; Institute of Health Informatics, University College London, London, United Kingdom.; National Institute for Health and Care Research, Biomedical Research Centre at University College London Hospitals, National Institute for Health Foundation Trust, London, United Kingdom., Porter JC; Respiratory Medicine, University College London, London, United Kingdom.; Interstitial Lung Disease Service, University College London Hospital, London, United Kingdom., Hurst JR; Respiratory Medicine, University College London, London, United Kingdom., Folarin AA; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.; National Institute for Health and Care Research, Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, United Kingdom.; Institute of Health Informatics, University College London, London, United Kingdom.; National Institute for Health and Care Research, Biomedical Research Centre at University College London Hospitals, National Institute for Health Foundation Trust, London, United Kingdom.
Jazyk:	angličtina
Zdroj:	JMIR formative research [JMIR Form Res] 2023 Nov 24; Vol. 7, pp. e51507. Date of Electronic Publication: 2023 Nov 24.
DOI:	10.2196/51507
Abstrakt:	Background: Patients with chronic respiratory diseases and those in the postdischarge period following hospitalization because of COVID-19 are particularly vulnerable, and little is known about the changes in their symptoms and physiological parameters. Continuous remote monitoring of physiological parameters and symptom changes offers the potential for timely intervention, improved patient outcomes, and reduced health care costs. Objective: This study investigated whether a real-time multimodal program using commercially available wearable technology, home-based Bluetooth-enabled spirometers, finger pulse oximeters, and smartphone apps is feasible and acceptable for patients with chronic respiratory diseases, as well as the value of low-burden, long-term passive data collection. Methods: In a 3-arm prospective observational cohort feasibility study, we recruited 60 patients from the Royal Free Hospital and University College Hospital. These patients had been diagnosed with interstitial lung disease, chronic obstructive pulmonary disease, or post-COVID-19 condition (n=20 per group) and were followed for 180 days. This study used a comprehensive remote monitoring system designed to provide real-time and relevant data for both patients and clinicians. Data were collected using REDCap (Research Electronic Data Capture; Vanderbilt University) periodic surveys, Remote Assessment of Disease and Relapses-base active app questionnaires, wearables, finger pulse oximeters, smartphone apps, and Bluetooth home-based spirometry. The feasibility of remote monitoring was measured through adherence to the protocol, engagement during the follow-up period, retention rate, acceptability, and data integrity. Results: Lowest-burden passive data collection methods, via wearables, demonstrated superior adherence, engagement, and retention compared with active data collection methods, with an average wearable use of 18.66 (SD 4.69) hours daily (77.8% of the day), 123.91 (SD 33.73) hours weekly (72.6% of the week), and 463.82 (SD 156.70) hours monthly (64.4% of the month). Highest-burden spirometry tasks and high-burden active app tasks had the lowest adherence, engagement, and retention, followed by low-burden questionnaires. Spirometry and active questionnaires had the lowest retention at 0.5 survival probability, indicating that they were the most burdensome. Adherence to and quality of home spirometry were analyzed; of the 7200 sessions requested, 4248 (59%) were performed. Of these, 90.3% (3836/4248) were of acceptable quality according to American Thoracic Society grading. Inclusion of protocol holidays improved retention measures. The technologies used were generally well received. Conclusions: Our findings provide evidence supporting the feasibility and acceptability of remote monitoring for capturing both subjective and objective data from various sources for respiratory diseases. The high engagement level observed with passively collected data suggests the potential of wearables for long-term, user-friendly remote monitoring in respiratory disease management. The unique piloting of certain features such as protocol holidays, alert notifications for missing data, and flexible support from the study team provides a reference for future studies in this field. International Registered Report Identifier (irrid): RR2-10.2196/28873. (©Malik A Althobiani, Yatharth Ranjan, Joseph Jacob, Michele Orini, Richard James Butler Dobson, Joanna C Porter, John R Hurst, Amos A Folarin. Originally published in JMIR Formative Research (https://formative.jmir.org), 24.11.2023.)
Databáze:	MEDLINE
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