Remote Health Monitoring with Wearable Devices: Investigating the Current Literature, Barriers, Facilitators, and Future Application
Notice bibliographique
Résumé
Subject: Issues within healthcare systems across the globe came to the forefront during the COVID-19 pandemic, emphasizing the inefficiency of traditional in-person healthcare visits. Inperson visits are expensive, episodic, and inaccessible for some patients, which impacts patient care quality. Healthcare system strain is obvious in seriously overcrowded Canadian emergency departments. A possible solution to these problems is remote health monitoring using wearable devices, which involves continuous collection of biometric data outside of the clinical setting. Remote health monitoring may increase healthcare accessibility and reduce hospital readmissions, healthcare costs, and clinician burnout. This thesis synthesizes knowledge from the emerging and promising field of remote health monitoring, highlighting evidence gaps and providing a foundation for implementing remote health monitoring in healthcare systems. Methods: This thesis aims to understand the current literature, barriers and facilitators, and future application of remote health monitoring with wearable devices. Chapter 1 is a scoping review on wearable devices for remote health monitoring in non-hospital settings, mapping currently available evidence and highlighting knowledge gaps to direct future research. Four electronic databases were searched: CINAHL, Scopus, Embase, and MEDLINE up to August 5, 2024, with a focus on studies that included clinically relevant outcomes. Chapter 2 is a scoping review that assessed physician attitudes towards wearable devices for remote health monitoring to understand key stakeholder perspectives on integrating these devices into patient care. MEDLINE, EMBASE, CINAHL, Scopus, and ProQuest Dissertations and Theses Global were searched up to October 5, 2023. Physician attitude data was analysed using an inductive qualitative content analysis approach. Chapter 3 is an exploration of how emergency department patients use primary care, telehealth and technology in a healthcare context to decide about using emergency care. Patients in the emergency department waiting room at the Northeast Community Health Centre, Edmonton, Alberta, Canada were briefly surveyed on these topics. Conclusions: Chapter 1 identified 80 studies that met eligibility criteria, and most used wearable devices to monitor changes in chronic disease, rather than to identify new diseases. There was an absence of randomized controlled trials in this review, and included studies had a diverse range of methodologies, calling for standardization in future work so that studies can be compared. Chapter 2 included 13 studies that met eligibility criteria, investigating physician attitudes towards remote health monitoring with wearable devices. An analysis of physician attitudes revealed a balanced number of benefits and concerns for this stakeholder group, including potential benefits of improved clinical decision making and patient engagement, and concerns about financial cost and the cost of training healthcare providers. These barriers and facilitators need to be considered in future studies and when implementing remote health monitoring with wearable devices in healthcare systems. Chapter 3 includes data from 50 emergency department patients, showing that although patients reported a history of using primary care, telehealth, and technology in a healthcare context, a small proportion used these resources prior to their current emergency department visit. Age differences existed for telehealth use and smartphone ownership, but not for use of smart devices (smartphones and/or smartwatches) to make health decisions. Results support the potential benefits of remote health monitoring with wearable devices to assist patients with healthcare access decisions, possibly reducing unnecessary emergency department visits. This thesis contributes to our knowledge about remote health monitoring with wearable devices, highlighting knowledge gaps, identifying barriers and facilitators to implementation, and providing evidence around the potential use of this technology with emergency department patients to reduce strain on acute care. These findings have implications for future research, particularly calling for more randomized controlled trials to affirm the clinical effectiveness of remote health monitoring with wearable devices. Valuable information on the barriers and facilitators of translating this technology into practice should be considered when this transition takes place. Remote health monitoring with wearables can increase healthcare service accessibility and individualized care, potentially alleviating strain on emergency departments. This thesis adds to current literature on wearable devices for remote health monitoring, providing a foundation for uptake in clinical practice, that may lead to increased accessibility and efficiency in relation to healthcare system operations.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,022 | 0,059 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,005 | 0,008 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,005 | 0,007 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».