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Issue in Remote Assessment of Lung Disease and Impact on Physical and Mental Health (RALPMH): Protocol for Prospective Observational Study

Ranjan, Y; Althobiani, M; Jacob, J; Orini, M; Dobson, R; Porter, J; Hurst, J; (2021) Issue in Remote Assessment of Lung Disease and Impact on Physical and Mental Health (RALPMH): Protocol for Prospective Observational Study. JMIR Research Protocols 10.2196/28873. (In press). Green open access

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Abstract

Background: Chronic Lung disorders like COPD and IPF are characterised by exacerbations which are a significant problem: unpleasant for patients, and sometimes severe enough to cause hospital admission (and therefore NHS pressures) and death. Reducing the impact of exacerbations is very important. Moreover, due to the COVID-19 pandemic, the vulnerable populations with these disorders are at high risk and hence their routine care cannot be done properly. Remote monitoring offers a low cost and safe solution of gaining visibility into the health of people in their daily life. Thus, remote monitoring of patients in their daily lives using mobile and wearable devices could be useful especially in high vulnerability groups. A scenario we consider here is to monitor patients and detect disease exacerbation and progression and investigate the opportunity of detecting exacerbations in real-time with a future goal of real-time intervention. Objective: The primary objective is to assess the feasibility and acceptability of remote monitoring using wearable and mobile phones in patients with pulmonary diseases. The aims will be evaluated over these areas: Participant acceptability, drop-out rates and interpretation of data, Detection of clinically important events such as exacerbations and disease progression, Quantification of symptoms (physical and mental health), Impact of disease on mood and wellbeing/QoL and The trajectory-tracking of main outcome variables, symptom fluctuations and order. The secondary objective of this study is to provide power calculations for a larger longitudinal follow-up study. Methods: Participants will be recruited from 2 NHS sites in 3 different cohorts - COPD, IPF and Post hospitalised Covid. A total of 60 participants will be recruited, 20 in each cohort. Data collection will be done remotely using the RADAR-Base mHealth platform for different devices - Garmin wearable devices, smart spirometers, mobile app questionnaires, surveys and finger pulse oximeters. Passive data collected includes wearable derived continuous heart rate, SpO2, respiration rate, activity, and sleep. Active data collected includes disease-specific PROMs, mental health questionnaires and symptoms tracking to track disease trajectory in addition to speech sampling, spirometry and finger Pulse Oximetry. Analyses are intended to assess the feasibility of RADAR-Base for lung disorder remote monitoring (include quality of data, a cross-section of passive and active data, data completeness, the usability of the system, acceptability of the system). Where adequate data is collected, we will attempt to explore disease trajectory, patient stratification and identification of acute clinically interesting events such as exacerbations. A key part of this study is understanding the potential of real-time data collection, here we will simulate an intervention using the Exacerbation Rating Scale (ERS) to acquire responses at-time-of-event to assess the performance of a model for exacerbation identification from passive data collected. Results: RALPMH study provides a unique opportunity to assess the use of remote monitoring in the study of lung disorders. The study is set to be started in mid-May 2021. The data collection apparatus, questionnaires and wearable integrations have been set up and tested by clinical teams. While waiting for ethics approval, real-time detection models are currently being constructed. Conclusions: RALPMH will provide a reference infrastructure for the use of wearable data for monitoring lung diseases. Specifically information regarding the feasibility and acceptability of remote monitoring and the potential of real-time remote data collection and analysis in the context of chronic lung disorders. Moreover, it provides a unique standpoint to look into the specifics of novel coronavirus without burdensome interventions. It will help plan and inform decisions in any future studies that make use of remote monitoring in the area of Respiratory health. Clinical Trial: https://www.isrctn.com/ISRCTN16275601

Type: Article
Title: Issue in Remote Assessment of Lung Disease and Impact on Physical and Mental Health (RALPMH): Protocol for Prospective Observational Study
Open access status: An open access version is available from UCL Discovery
DOI: 10.2196/28873
Publisher version: http://dx.doi.org/10.2196/28873
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Respiratory Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine > MRC Unit for Lifelong Hlth and Ageing
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10129579
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