Remote-Management of COPD: Evaluating the Implementation of Digital Innovation to Enable Routine Care (RECEIVER): the protocol for a feasibility and service adoption observational cohort study

Taylor, Ashleigh; Lowe, David J; McDowell, G; Lua, Stephanie; Burns, Shane; McGinness, P; Carlin, C. M.

doi:10.1136/bmjresp-2021-000905

Cited by 7 publications

(24 citation statements)

References 23 publications

(18 reference statements)

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“…Comanaged digital tools are now being studied, which use wearable data and patient-reported outcome measures to help clinical teams identify and respond to change [ 66 ].…”

Section: Resultsmentioning

confidence: 99%

User Requirements for Comanaged Digital Health and Care: Review

Chute¹,

French²,

Raman³

et al. 2022

J Med Internet Res

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Background The sustainability of health and social care has led to an imperative to shift the balance of care to communities and support person-centered, integrated, preventive, comanaged, and sustainable care. The digital tool set can support this shift; however, it must extend beyond a clinical focus to include broader personal, social, and environmental needs, experiences, and outcomes. The existing digital health and care design and user requirements literature focuses mainly on specific digital products or design methods. There is little whole-system or whole-of-life consideration, which is crucial to enacting more significant transformations that span different groups and domains. Objective This study aimed to present a set of recurring user requirements and themes for comanaged digital health and care services derived from the body of co-design projects within a digital health and care program. This study aimed to enable people and organizations looking to reorient their approach to health and care research and delivery from a system-led and condition-specific approach to a more person-centric, whole-of-life model. Methods Participatory design formed the core methodological approach in underlying the design research, from which user requirements were derived. The process of surfacing requirements involved a selection framework for the identification of eligible projects and a structured review process to consolidate user requirements. Results This paper presents a set of 14 common user requirements that resulted from a review of co-design projects. The findings demonstrate overlapping and reinforcing sets of needs from citizens and care professionals related to how data are comanaged to improve care and outcomes. This paper discusses the alignment, contrasts, and gaps with broader, comparable literature. It highlights consensus around requirements for personal health storytelling, sharing data on care experiences and how this can support personalized guidance, visualize trends to support decision-making, and generally improve dialog between a citizen and care professionals. These findings identify gaps around how groups and networks of people engage, posing difficult questions for people designing support services as some of the user requirements are not easily met by organizations operating in silos. Conclusions This study proposes future recommendations for citizens as active, informed, and consenting partners using new forms of privacy-preserving digital infrastructure that puts the citizen in firm control. It is also recommended that these findings be used by people developing new digital services to ensure that they can start with knowledge of the broader user requirement context. This should inform domain-specific research and development questions and processes. Further work is needed to extend these common requirements to more explicitly consider the trust framework required when citizens comanage their data and care across a broad range of formal and informal actors. Consideration of how authority, delegation, and trust function between members of the public will be critical.

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“…Comanaged digital tools are now being studied, which use wearable data and patient-reported outcome measures to help clinical teams identify and respond to change [ 66 ].…”

Section: Resultsmentioning

confidence: 99%

User Requirements for Comanaged Digital Health and Care: Review

Chute¹,

French²,

Raman³

et al. 2022

J Med Internet Res

View full text Add to dashboard Cite

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“…Pulmonary Disease C08.381: The trial in ref. [41] aims to evaluate the adoption of a digital support service model for chronic obstructive pulmonary disease, focusing on ML analysis and predictive modeling, and uses a consented dataset for endpoint analysis and follow-up studies.…”

Section: Respiratory Tract Diseases (C08)mentioning

confidence: 99%

Machine Learning Models and Technologies for Evidence-Based Telehealth and Smart Care: A Review

Christopoulou

2024

BioMedInformatics

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Background: Over the past few years, clinical studies have utilized machine learning in telehealth and smart care for disease management, self-management, and managing health issues like pulmonary diseases, heart failure, diabetes screening, and intraoperative risks. However, a systematic review of machine learning’s use in evidence-based telehealth and smart care is lacking, as evidence-based practice aims to eliminate biases and subjective opinions. Methods: The author conducted a mixed methods review to explore machine learning applications in evidence-based telehealth and smart care. A systematic search of the literature was performed during 16 June 2023–27 June 2023 in Google Scholar, PubMed, and the clinical registry platform ClinicalTrials.gov. The author included articles in the review if they were implemented by evidence-based health informatics and concerned with telehealth and smart care technologies. Results: The author identifies 18 key studies (17 clinical trials) from 175 citations found in internet databases and categorizes them using problem-specific groupings, medical/health domains, machine learning models, algorithms, and techniques. Conclusions: Machine learning combined with the application of evidence-based practices in healthcare can enhance telehealth and smart care strategies by improving quality of personalized care, early detection of health-related problems, patient quality of life, patient-physician communication, resource efficiency and cost-effectiveness. However, this requires interdisciplinary expertise and collaboration among stakeholders, including clinicians, informaticians, and policymakers. Therefore, further research using clinicall studies, systematic reviews, analyses, and meta-analyses is required to fully exploit the potential of machine learning in this area.

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“…Presently, most COPD management strategies adopt a reactive approach, resulting in delays in identifying treatment opportunities and contributing to the quality gap in COPD care. 81 COPD management encompasses various interventions, such as smoking cessation, pulmonary rehabilitation, personal inhalation therapy, home oxygen therapy (where appropriate), and home noninvasive ventilation (when necessary). 62 Despite the availability of these treatments, there are significant obstacles to their implementation and delivery.…”

Section: Digital Health In Copd (Figure 1 )mentioning

confidence: 99%

Digital health in chronic obstructive pulmonary disease

Long

Chen

2023

Chronic Diseases and Translational Medicine

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Chronic obstructive pulmonary disease (COPD) can be prevented and treated through effective care, reducing exacerbations and hospitalizations. Early identification of individuals at high risk of COPD exacerbation is an opportunity for preventive measures. However, many patients struggle to follow their treatment plans because of a lack of knowledge about the disease, limited access to resources, and insufficient clinical support. The growth of digital health-which encompasses advancements in health information technology, artificial intelligence, telehealth, the Internet of Things, mobile health, wearable technology, and digital therapeutics-offers opportunities for improving the early diagnosis and management of COPD. This study reviewed the field of digital health in terms of COPD. The findings showed that despite significant advances in digital health, there are still obstacles impeding its effectiveness. Finally, we highlighted some of the major challenges and possibilities for developing and integrating digital health in COPD management. K E Y W O R D SCOPD management, chronic obstructive pulmonary disease, digital health Highlights• Digital health can support the early diagnosis and management of Chronic obstructive pulmonary disease, but there are still important challenges and opportunities to be addressed.

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Remote-Management of COPD: Evaluating the Implementation of Digital Innovation to Enable Routine Care (RECEIVER): the protocol for a feasibility and service adoption observational cohort study

Cited by 7 publications

References 23 publications

User Requirements for Comanaged Digital Health and Care: Review

User Requirements for Comanaged Digital Health and Care: Review

Machine Learning Models and Technologies for Evidence-Based Telehealth and Smart Care: A Review

Digital health in chronic obstructive pulmonary disease

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