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Enregistrement W3212627357 · doi:10.1182/blood-2021-152021

The Use of Virtual Care in Patients with Hematologic Malignancies - a Scoping Review

2021· review· en· W3212627357 sur OpenAlexaff
Adam Suleman, Abi Vijenthira, Alejandro Berlín, Anca Prica, Danielle Rodin

Notice bibliographique

RevueBlood · 2021
Typereview
Langueen
DomaineMedicine
ThématiqueTelemedicine and Telehealth Implementation
Établissements canadiensUniversity Health NetworkPrincess Margaret Cancer CentreUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMedicineMEDLINECINAHLPopulationHealth careIntensive care medicineNursingPsychological intervention

Résumé

récupéré en direct d'OpenAlex

Abstract Background: The use of virtual care, defined as providing healthcare in ways other than in-person visits, dramatically increased during the COVID-19 pandemic to minimize infection risk and maintain care provision. However, the majority of studies evaluating the use of virtual care in oncology have focused on patients with solid tumor malignancies. Patients with hematologic malignancies represent a unique population related to their underlying malignancy and treatment, but the extent to which virtual care has been successfully integrated into clinical practice is unknown. As the demand for incorporating virtual care into routine clinical practice grows, understanding how to safely and effectively use virtual care in this specific patient population is essential. Methods: A scoping review was conducted to describe the use of virtual care in the management of patients with hematologic malignancies and to examine physician- and patient-reported outcomes based on its use. A comprehensive search strategy was used to identify articles on the use of virtual modalities (digital applications, phone visits, or video visits) to deliver routine clinical care to patients with hematologic malignancies published in English between January 2000 and April 2021 in the following databases: PubMed, Medline, EMBASE, CINAHL and Scopus. No restrictions were applied to the phase of care (surveillance, active treatment, and or survivorship). A combination of search terms to encompass hematologic malignancies and virtual care was used. Screening and data abstraction were performed by two independent reviewers (AS, AV) and conflicts were adjudicated by two additional reviewers (DR, AP). Data were extracted to assess the study design, population, setting, patient characteristics, virtual care methodology and study results. Results: A total of 350 abstracts were screened and 60 studies underwent full-text review. Of these, 15 studies met inclusion criteria (13 retrospective studies, 1 prospective pilot study, and 1 randomized controlled trial). The majority of papers were published from 2020 onward (Figure 1). Three studies found that app-based tools were effective in monitoring patient symptoms and triggering alerts which resulting in sooner follow-up if indicated. One app-based tool was also used in a resource limited country during the COVID-19 pandemic to allow for communication between hematologists and their patients. Four studies described the use of phone-based interventions for new consults and follow-up visits. Phone visits for used even in high-risk patients (for example, in 29 out of 50 patients with chronic graft-versus-host disease after allogeneic stem cell transplant). Five studies found that videoconferencing, with both physicians and oncology nurses, was highly rated by patients. Emerging themes included high levels of patient satisfaction across all domains of virtual care. Provider satisfaction scores were rated lower than patient scores, with concerns about technical issues leading to challenges with virtual care. Four studies found that virtual care allowed providers to promptly respond to patient concerns, specifically when patients were experiencing side-effects or had questions about their treatment. One study also suggested a decreased risk of death when telemedicine was used to monitor symptoms in patients with diffuse large B-cell lymphoma. There were no data addressing the impact of virtual care on costs or resource utilization. Conclusion: The use of virtual care in patients with hematologic malignancies appears to be feasible, even in high-risk populations. Patients were highly satisfied with virtual care, although providers had some challenges related to the specific technologies. More research is needed to evaluate the optimal method of integrating virtual care, informed by a wider range of patient-related outcomes, as well as the downstream consequences of this integration for patient, providers, and health systems. Figure 1 Figure 1. Disclosures Prica: Astra-Zeneca: Honoraria; Kite Gilead: Honoraria.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,011
score de la tête « metaresearch » (Gemma)0,065
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,019
Score d'incertitude au seuil0,060

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0110,065
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0040,004
Bibliométrie0,0190,020
Études des sciences et des technologies0,0010,001
Communication savante0,0040,003
Science ouverte0,0020,002
Intégrité de la recherche0,0020,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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.

Tête enseignante Opus0,088
Tête enseignante GPT0,381
Écart entre enseignants0,292 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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