ERS “CONNECT” Clinical Research Collaboration – moving multiple digital innovations towards connected respiratory care: addressing the over-arching challenges of whole systems implementation

van Boven, Job F.M.; Drummond, David; Chan, Amy H.Y.; Hew, Mark; Hui, Chi Yan; Adejumo, Ireti; Cano, Isaac; Hansen, Kjeld; Poberezhets, Vitalii; Costello, Richard W.; Pinnock, Hilary

doi:10.1183/13993003.01680-2023

Cited by 13 publications

(2 citation statements)

References 27 publications

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“…Digital technologies offer dual opportunities of monitoring in real-time (a) factors that increase the risk of an attack (eg, environmental triggers, individual history of attacks, poor adherence to preventer medication) to promote strategies to reduce risk and (b) objective measures that enable early detection of an imminent attack that can be captured by digital sensors 8 (eg, heart rate, [9][10][11] sleep quality 12 and peak expiratory flow 13 ), which can trigger an alert for immediate action to avert further deterioration. However, there has been no research to date that bring together the range of factors.…”

Section: How This Study Might Affect Research Practice and Or Policymentioning

confidence: 99%

DIGIPREDICT: physiological, behavioural and environmental predictors of asthma attacks—a prospective observational study using digital markers and artificial intelligence—study protocol

Chan,

Te Ao,

Baggott

et al. 2024

BMJ Open Resp Res

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IntroductionAsthma attacks are a leading cause of morbidity and mortality but are preventable in most if detected and treated promptly. However, the changes that occur physiologically and behaviourally in the days and weeks preceding an attack are not always recognised, highlighting a potential role for technology. The aim of this study ‘DIGIPREDICT’ is to identify early digital markers of asthma attacks using sensors embedded in smart devices including watches and inhalers, and leverage health and environmental datasets and artificial intelligence, to develop a risk prediction model to provide an early, personalised warning of asthma attacks.Methods and analysisA prospective sample of 300 people, 12 years or older, with a history of a moderate or severe asthma attack in the last 12 months will be recruited in New Zealand. Each participant will be given a smart watch (to assess physiological measures such as heart and respiratory rate), peak flow meter, smart inhaler (to assess adherence and inhalation) and a cough monitoring application to use regularly over 6 months with fortnightly questionnaires on asthma control and well-being. Data on sociodemographics, asthma control, lung function, dietary intake, medical history and technology acceptance will be collected at baseline and at 6 months. Asthma attacks will be measured by self-report and confirmed with clinical records. The collected data, along with environmental data on weather and air quality, will be analysed using machine learning to develop a risk prediction model for asthma attacks.Ethics and disseminationEthical approval has been obtained from the New Zealand Health and Disability Ethics Committee (2023 FULL 13541). Enrolment began in August 2023. Results will be presented at local, national and international meetings, including dissemination via community groups, and submission for publication to peer-reviewed journals.Trial registration numberAustralian New Zealand Clinical Trials Registry ACTRN12623000764639; Australian New Zealand Clinical Trials Registry.

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Section: How This Study Might Affect Research Practice and Or Policymentioning

confidence: 99%

DIGIPREDICT: physiological, behavioural and environmental predictors of asthma attacks—a prospective observational study using digital markers and artificial intelligence—study protocol

Chan,

Te Ao,

Baggott

et al. 2024

BMJ Open Resp Res

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“…Digital health is an ERS priority, as reflected by the launch of the ERS-funded Clinical Research Collaboration “CONNECT” (Moving multiple digital innovations towards connected respiratory care: addressing the over-arching challenges of whole systems implementation) [ 63 ]. Several advancements were presented, compared to previous ERS Congresses [ 1 , 64 – 67 ], on a great diversity of topics ( figure 3 ).…”

Section: Group 104: M-health/e-healthmentioning

confidence: 99%

ERS International Congress 2023: highlights from the Respiratory Clinical Care and Physiology Assembly

Gonsard,

Mekov,

Barron

et al. 2024

ERJ Open Res

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It is a challenge to keep abreast of all the clinical and scientific advances in the field of respiratory medicine. This article contains an overview of laboratory-based science, clinical trials and qualitative research that were presented during the 2023 European Respiratory Society International Congress within the sessions from the five groups of the Assembly 1 – Respiratory clinical care and physiology. Selected presentations are summarised from a wide range of topics: clinical problems, rehabilitation and chronic care, general practice and primary care, electronic/mobile health (e-health/m-health), clinical respiratory physiology, exercise and functional imaging.

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Digital Inhaler Implementation in Daily Asthma Management: Who, When, and How?

van Boven,

Kocks,

Dierick

2024

The Journal of Allergy and Clinical Immunology: In Practice

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ERS “CONNECT” Clinical Research Collaboration – moving multiple digital innovations towards connected respiratory care: addressing the over-arching challenges of whole systems implementation

Cited by 13 publications

References 27 publications

DIGIPREDICT: physiological, behavioural and environmental predictors of asthma attacks—a prospective observational study using digital markers and artificial intelligence—study protocol

DIGIPREDICT: physiological, behavioural and environmental predictors of asthma attacks—a prospective observational study using digital markers and artificial intelligence—study protocol

ERS International Congress 2023: highlights from the Respiratory Clinical Care and Physiology Assembly

Digital Inhaler Implementation in Daily Asthma Management: Who, When, and How?

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