Provider and Older Patient Responses to Rapid Expansion of Telehealth in an Urban Cancer Center: Mixed Methods Critical Incident Evaluation
Notice bibliographique
Résumé
Background Synchronous video visits (“telehealth”) were rapidly adopted by many cancer centers across the nation to facilitate provision of care during the COVID-19 pandemic; however, in many cases, there was little time to comprehensively assess patient and provider needs related to this rollout. In addition, attitudes toward telehealth use among older patients with cancer, who may face increased vulnerability to inequities in access to care due to limited digital literacy, were largely unknown at that time. Objective The objectives of this concurrent mixed methods study were to (1) assess stakeholder experiences with telehealth since its rollout during the COVID-19 pandemic at an urban comprehensive cancer center and (2) solicit suggestions to optimize workflow and enhance telehealth implementation beyond the pandemic. Methods We conducted surveys and critical incident interviews with providers, staff, and older patients (aged ≥60 years) from a comprehensive cancer center in a large urban area. Data collection occurred from December 2020 to November 2021. We analyzed survey data using descriptive statistics and qualitative data using deductive and inductive thematic content analysis facilitated by NVivo 12.0 (QSR Australia). Results We completed a total of 106 provider or staff surveys, 128 patient surveys, 20 provider or staff interviews, and 14 patient interviews. While the majority (70.7%) of surveyed providers and staff agreed or strongly agreed that the technology used to support telehealth visits at Simmons fit well within their clinical workflow, several suggestions were offered to enhance telehealth implementation, including conducting proactive, systematic training and technical assistance; making appointment scheduling and rooms flexible for in-person or telehealth conversion in real time to streamline workflow; expanding availability of telehealth to supportive care services and physically frail patients; and increasing provider engagement via telehealth meetings and conferences. Less than a third (30.8%) of providers or staff agreed or strongly agreed that the institution did a good job of preparing patients for their first telehealth encounter, and patients reported experiencing challenges with joining video visits (29%) and understanding the telehealth process (28%). Participants suggested several strategies to assist patients with limited digital literacy, including offering video tutorials of the connection process, creating “fake appointments” to practice web-based connections, and hiring a digital navigator to assist with technical difficulties and setup of the web-based portal. Despite challenges, a majority of surveyed patients (65.7%) and providers or staff (76.9%) intend to continue using telehealth after the COVID-19 pandemic passes. Conclusions Use of telehealth for cancer care was received positively by older patients and providers or staff. Taking targeted steps to support enhanced implementation post pandemic could reduce barriers to care, including among older adults and other populations with limited digital literacy, thereby promoting greater equity of access to telehealth and the potential benefits it offers.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 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 ».