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

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/ISRCTN1627560

Health Effects Associated With Electronic Cigarette Use: Automated Mining of Online Forums.

BACKGROUND:Our previous infodemiological study was performed by manually mining health-effect data associated with electronic cigarettes (ECs) from online forums. Manual mining is time consuming and limits the number of posts that can be retrieved. OBJECTIVE:Our goal in this study was to automatically extract and analyze a large number (>41,000) of online forum posts related to the health effects associated with EC use between 2008 and 2015. METHODS:Data were annotated with medical concepts from the Unified Medical Language System using a modified version of the MetaMap tool. Of over 1.4 million posts, 41,216 were used to analyze symptoms (undiagnosed conditions) and disorders (physician-diagnosed terminology) associated with EC use. For each post, sentiment (positive, negative, and neutral) was also assigned. RESULTS:Symptom and disorder data were categorized into 12 organ systems or anatomical regions. Most posts on symptoms and disorders contained negative sentiment, and affected systems were similar across all years. Health effects were reported most often in the neurological, mouth and throat, and respiratory systems. The most frequently reported symptoms and disorders were headache (n=939), coughing (n=852), malaise (n=468), asthma (n=916), dehydration (n=803), and pharyngitis (n=565). In addition, users often reported linked symptoms (eg, coughing and headache). CONCLUSIONS:Online forums are a valuable repository of data that can be used to identify positive and negative health effects associated with EC use. By automating extraction of online information, we obtained more data than in our prior study, identified new symptoms and disorders associated with EC use, determined which systems are most frequently adversely affected, identified specific symptoms and disorders most commonly reported, and tracked health effects over 7 years

Home-based Digital Health Technologies for Older Adults to Self-Manage Multiple Chronic Conditions: A Data-Informed Analysis of User Engagement from a Longitudinal Trial

BACKGROUND: Ageing populations are resulting in higher prevalence of people with multiple chronic conditions (multimorbidity). Digital health platforms have great potential to support self-management of multimorbidity, increasing a person's awareness of their health and well-being, supporting a better understanding of diseases and encouraging behaviour change. However, little research has explored the long-term engagement of older adults with such digital interventions. METHODS: The aim of this study is to analyse how 60 older adults with multimorbidity engaged with digital symptom and well-being monitoring through a digital health platform over a period of approximately 12 months. Data analysis focused on user retention, frequency of monitoring, intervals in monitoring and patterns of daily engagement. RESULTS: Our findings show that the overall engagement with the digital health platform was high, with more than 80% of participants using the technology devices for over 200 days. The submission frequency for symptom parameters (e.g. blood glucose (BG), blood pressure (BP), etc.) was between three and four times per week which was higher than that of self-report (2.24) and weight (2.84). Submissions of exercise (6.12) and sleep (5.67) were more frequent. The majority of interactions happened in the morning time. The most common time of submission for symptom parameters was 10 am, whereas 8 am was the most common time for weight measurements. CONCLUSIONS: The findings indicate the patterns of engagement of older adults with complex chronic diseases with digital home-based self-management systems

Personalized medication adherence management in asthma and COPD:a review of effective interventions and development of a practical adherence toolkit

BACKGROUND: Medication non-adherence management of patients with asthma/COPD remains challenging. Given the multitude of underlying causes, a personalized approach is required. The Test of Adherence to Inhalers (TAI) can identify reasons for non-adherence, but does not provide guidance on how to effectively act on results. OBJECTIVE: To develop a practical, evidence-based decision support toolkit for healthcare professionals managing adult patients with asthma and/or COPD, by matching TAI-identified adherence barriers to proven effective adherence enhancing interventions. METHODS: A literature review in PubMed and Embase was performed identifying interventions that enhanced medication adherence in adult patients with asthma and/or COPD. Randomised controlled trials (RCTs) published in English with full-texts available were included. Effective interventions were assessed by the Cochrane risk of bias tool, categorized, matched with specific TAI responses and developed into a practical TAI Toolkit. The Toolkit was assessed on content and usability (System Usability Scale, SUS) by a multidisciplinary group of healthcare professionals. RESULTS: Forty RCTs were included in the review. In total, seven effective interventions catergories were identified, informing the TAI Toolkit: reminders, educational interventions, motivational strategies, feedback on medication use, shared decision making, simplifying medication regimen and multiple component interventions. Healthcare professionals rated the TAI Toolkit with a mean SUS score of 71.4 (range: 57.5-80.0). CONCLUSION: Adherence can be improved using different interventions that the TAI Toolkit helps selecting. The TAI Toolkit was well received by healthcare professionals. Further research is required to test its validity, practicality and effectiveness in practice

J. Silvaa , N. Hipolito b,c , P. Machadob , S. Florab , J. Cruza,b, *

Acknowledgements: This work is part of a project funded by FEDER - Fundo Europeu de Desenvolvimento Regional by COMPETE 2020 Programa Operacional Competitividade e Internacionalização (POCI) and national funds by Fundação ao para a Ciência e a Tecnologia (FCT), entitled ^ “OnTRACK project - Time to Rethink Activity Knowledge: a personalized mHealth coaching platform to tackle physical inactivity in COPD” (POCI-01-0145-FEDER-028446, PTDC/SAU-SER/28446/2017). SF and NH are being financially supported by PhD fellowships DFA/BD/6954/2020 and 2021.05188.BD, respectively, funded by FCT/MCTES, FSE, Por_Centro and UE. PM acknowledges the support provided by the FCT with the PhD fellowship. The authors acknowledge the financial support provided by FCT to their research unit Center for Innovative Care and Health Technology (UIDB/05704/2020).Pulmonology is the official journal of the Portuguese Society of Pulmonology (Sociedade Portuguesa de Pneumologia/SPP). The journal publishes 6 issues per year, mainly about respiratory system diseases in adults and clinical research. All articles published open access will be immediately and permanently free for everyone to read, download, copy and distribute.Introduction: Low physical activity (PA) levels have a negative impact on the health status of patients with Chronic Obstructive Pulmonary Disease (COPD). Smartphone applications (apps) focused on PA promotion may mitigate this problem; however, their effectiveness depends on patient adherence, which can be influenced by the technological features of the apps. This systematic review identified the technological features of smartphone apps aiming to promote PA in patients with COPD. Methods: A literature search was performed in the databases ACM Digital Library, IEEE Xplore, PubMed, Scopus and Web of Science. Papers including the description of a smartphone app for PA promotion in patients with COPD were included. Two researchers independently selected studies and scored the apps features based on a previously developed framework (38 possible features). Results: Twenty-three studies were included and 19 apps identified, with an average of 10 technological features implemented. Eight apps could be connected to wearables to collect data. The categories ‘Measuring and monitoring’ and ‘Support and Feedback’ were present in all apps. Overall, the most implemented features were ‘progress in visual format’ (n=13), ‘advice on PA’ (n=14) and ‘data in visual format’ (n=10). Only three apps included social features, and two included a web-based version of the app. Conclusions: The existing smartphone apps include a relatively small number of features to promote PA, which are mostly related to monitoring and providing feedback. Further research is warranted to explore the relationship between the presence/absence of specific features and the impact of interventions on patients’ PA levels.info:eu-repo/semantics/publishedVersio

Development and implementation of a remote monitoring and coaching intervention delivered using digital health technology for people with a history of cancer.

There is a need to improve care practices to optimally enhance physical health and health- related quality of life in people with a history of cancer. Intensive treatment of cancer can impact patients both acutely and chronically as long-term or late effects well after treatment completion. As a result, both patients with cancer and cancer survivors need additional support Supportive cancer care, including survivorship and rehabilitation services focuses on developing strategies to support survivors’ well-being and recovery during and after cancer treatment. However, despite the evidence-based benefits of these services, many barriers still exist that may restrict patients with cancer from participation and engagement. One possible solution to these challenges is the use of digital health technologies. The aim of this research was to explore current gaps in knowledge regarding digital health enabled supportive cancer care and design and develop a digital health enabled intervention, specifically tailored to the needs of people with a cancer diagnosis. The experience culminated in the implementation of a 10-week prospective cohort trial, focused on the feasibility and acceptability of a patient-provider tracking and exercise coaching portal. As evidenced by the research studies presented within this thesis, findings suggest that patient-centric supportive care can be provided to cancer patients using a digital health enabled approach. Further, remote monitoring and individual exercise coaching can feasibly be offered to patient populations who may not be able to conveniently access support services, or who choose to access these services remotely. Several recommendations for future research and future directions were provided to further this area of research

Complex Care Management Program Overview

This report includes brief updates on various forms of complex care management including: Aetna - Medicare Advantage Embedded Case Management ProgramBrigham and Women's Hospital - Care Management ProgramIndependent Health - Care PartnersIntermountain Healthcare and Oregon Health and Science University - Care Management PlusJohns Hopkins University - Hospital at HomeMount Sinai Medical Center -- New York - Mount Sinai Visiting Doctors Program/ Chelsea-Village House Calls ProgramsPartners in Care Foundation - HomeMeds ProgramPrinceton HealthCare System - Partnerships for PIECEQuality Improvement for Complex Chronic Conditions - CarePartner ProgramSenior Services - Project Enhance/EnhanceWellnessSenior Whole Health - Complex Care Management ProgramSumma Health/Ohio Department of Aging - PASSPORT Medicaid Waiver ProgramSutter Health - Sutter Care Coordination ProgramUniversity of Washington School of Medicine - TEAMcar