Technology-Enabled Remote Monitoring and Self-Management — Vision for Patient Empowerment Following Cardiac and Vascular Surgery: User Testing and Randomized Controlled Trial Protocol
Notice bibliographique
Résumé
BACKGROUND: Tens of thousands of cardiac and vascular surgeries (CaVS) are performed on seniors in Canada and the United Kingdom each year to improve survival, relieve disease symptoms, and improve health-related quality of life (HRQL). However, chronic postsurgical pain (CPSP), undetected or delayed detection of hemodynamic compromise, complications, and related poor functional status are major problems for substantial numbers of patients during the recovery process. To tackle this problem, we aim to refine and test the effectiveness of an eHealth-enabled service delivery intervention, TecHnology-Enabled remote monitoring and Self-MAnagemenT-VIsion for patient EmpoWerment following Cardiac and VasculaR surgery (THE SMArTVIEW, CoVeRed), which combines remote monitoring, education, and self-management training to optimize recovery outcomes and experience of seniors undergoing CaVS in Canada and the United Kingdom. OBJECTIVE: Our objectives are to (1) refine SMArTVIEW via high-fidelity user testing and (2) examine the effectiveness of SMArTVIEW via a randomized controlled trial (RCT). METHODS: CaVS patients and clinicians will engage in two cycles of focus groups and usability testing at each site; feedback will be elicited about expectations and experience of SMArTVIEW, in context. The data will be used to refine the SMArTVIEW eHealth delivery program. Upon transfer to the surgical ward (ie, post-intensive care unit [ICU]), 256 CaVS patients will be reassessed postoperatively and randomly allocated via an interactive Web randomization system to the intervention group or usual care. The SMArTVIEW intervention will run from surgical ward day 2 until 8 weeks following surgery. Outcome assessments will occur on postoperative day 30; at week 8; and at 3, 6, 9, and 12 months. The primary outcome is worst postop pain intensity upon movement in the previous 24 hours (Brief Pain Inventory-Short Form), averaged across the previous 14 days. Secondary outcomes include a composite of postoperative complications related to hemodynamic compromise-death, myocardial infarction, and nonfatal stroke- all-cause mortality and surgical site infections, functional status (Medical Outcomes Study Short Form-12), depressive symptoms (Geriatric Depression Scale), health service utilization-related costs (health service utilization data from the Institute for Clinical Evaluative Sciences data repository), and patient-level cost of recovery (Ambulatory Home Care Record). A linear mixed model will be used to assess the effects of the intervention on the primary outcome, with an a priori contrast of weekly average worst pain intensity upon movement to evaluate the primary endpoint of pain at 8 weeks postoperation. We will also examine the incremental cost of the intervention compared to usual care using a regression model to estimate the difference in expected health care costs between groups. RESULTS: Study start-up is underway and usability testing is scheduled to begin in the fall of 2016. CONCLUSIONS: Given our experience, dedicated industry partners, and related RCT infrastructure, we are confident we can make a lasting contribution to improving the care of seniors who undergo CaVS.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,012 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».