Virtual care beyond COVID-19: Patient and physician perspectives.
Notice bibliographique
Résumé
389 Background: The COVID-19 pandemic catalyzed rapid implementation of virtual care (VC), resulting in new opportunities to integrate technology and a need to evaluate patient and provider experiences. To inform sustainment beyond COVID-19, we evaluated perceptions of VC at a comprehensive cancer centre in Toronto, Canada. Methods: Physicians who provided VC during the pandemic, and patients with a valid email address on file and at least one visit with centre in the preceding 12 months were eligible to participate. Survey invitations were disseminated between May and July 2021 via email using a modified Dillman approach. The survey examined the implementation outcomes of acceptability, adoption, and appropriateness. Unadjusted associations between patient demographic variables and preference for in-person visits were evaluated using univariate logistic regression models. Results: 41% (100/246) of physicians and 15% (2,343/15,169) of patients completed the survey. The majority of patients were Caucasian (77%), college or university educated (78%), had solid malignancies (73%), and were in the follow-up phase (47%); 50% were male. The median age was 66 (IQR: 58-74). A greater proportion of patients expressed satisfaction with VC than providers (81% and 53%). Conversely, a greater proportion of providers felt that care delivered virtually was worse than care delivered in-person (45% vs 26%). Interestingly, many patients (69%) and physicians (40%) reported feeling they could maintain a good relationship through VC while at the same time reporting concerns that VC would detract from the human interaction they value as part of care (patients: 60%; providers: 82%). Patients expressed relatively equal preference for phone vs video visits (40% vs 31%), but indicated concerns about wait times for VC visits. The majority of physicians (37%) estimated that 10-29% of their practice would remain virtual post-COVID, however physicians expressed concerns with increased workload (72%), decreased efficiency (40%), and increased worry about missing relevant clinical information (61%). The majority of patients and physicians reported that VC was not appropriate for first consultations and discussions of prognosis, and most appropriate for long-term follow-up. Being born outside of Canada, primary language other than English, lower income, lower functional health literacy, and greater physical mobility were associated with preferring in-person over VC visits. Conclusions: Patients and physicians were satisfied with VC but expressed concerns with the impacts on care quality and experience and highlighted the need for guidelines on appropriate use. Providers expressed greater concerns with VC than patients. More research is needed to formally evaluate the impact of VC on quality performance and clinical outcomes as well as investigate the patient, disease and system factors that are associated with effective virtual cancer care.
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 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 | 0,003 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 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 ».