Exploring the Impact of a Remote Monitoring System for Palliative and End-of-Life Care (CARE-PAC): Mixed Methods Feasibility Study
Notice bibliographique
Résumé
BACKGROUND: In the United Kingdom, access to and the quality of palliative and end-of-life care (PEOLC) vary widely. In the final months of life, many patients face avoidable accident and emergency (A&E) visits and hospital admissions, driven by gaps in out-of-hours support and poorly coordinated care. This not only increases stress for patients and carers but also places avoidable strain and cost on the National Health Service (NHS). There is an urgent need for more compassionate, person-centered models that support people to remain at home, improve their quality of life (QoL), and reduce unnecessary use of acute services. OBJECTIVE: This study aimed to explore the usability, user experiences, and impact of the digital dyadic remote monitoring Care and Support System for Patients and Carers (CARE-PAC) for patients in the last year of life, their informal carers, and health professionals involved in their care. METHODS: Patients and informal carers were recruited to use CARE-PAC for up to 12 weeks. A mixed methods approach was used. Quantitative methods included the use of validated QoL scales and the System Usability Scale (SUS). Paired QoL and usability data were analyzed using the Wilcoxon (Pratt) signed-rank test, while unpaired usability data were analyzed using the Wilcoxon rank-sum test. Qualitative methods involved short catch-up calls, in-depth interviews, and focus groups conducted using topic guides informed by the domains of the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework. Data were analyzed thematically. RESULTS: CARE-PAC was implemented across 5 UK clinical sites with 26 participants (13 patient-carer dyads). No significant changes were observed in patients' total QoL scores; however, significant improvements were seen in the "overall QoL" and "social" domains, alongside a significant decline in the "physical" domain. Carers showed no significant changes across total or domain-specific QoL scores. Usability was rated highly by patients (mean 87.9, SD 12.4) and carers (mean 94.7, SD 3.8), indicating an excellent user experience. Health care professionals (HCPs) reported lower usability scores (mean 63.6, SD 15.6), falling below average but above the threshold for poor usability. Thematic analysis of qualitative data gathered via catch-up calls (all patient-carer dyads), in-depth interviews (2 patients-2 carers), and 4 focus groups/1 interview (12 HCPs) identified 4 key themes: impact on care experiences, reflections and satisfaction, implementation challenges, and future directions. CONCLUSIONS: CARE-PAC is a usable, feasible, and acceptable remote monitoring and support system for patients in the last year of life, their carers, and HCPs. It enables real-time identification of needs and has shown positive impacts on the QoL of both patients and carers. These findings support the need for further research to evaluate its effectiveness at scale and explore pathways for wider implementation in PEOLC.
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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 | 0,029 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».