Telemedicine for Pediatric Nephrology: Perspectives on COVID-19, Future Practices, and Work Flow Changes
Notice bibliographique
Résumé
Although the use of telemedicine in rural areas has increased steadily over the years, its use was rapidly implemented during the onset of the coronavirus disease 2019 (COVID-19) crisis. Due to this rapid implementation, there is a lack of standardized work flows to assess and treat for various nephrotic conditions, symptoms, treatment modalities, and transition processes in the pediatric population. To provide a foundation/suggestion for future standardized work flows, the authors of this report have developed standardized work flows using the Delphi method. These work flows were informed based on results from cross-sectional surveys directed to patients and providers. Most patients and providers were satisfied, 87% and 71%, respectively, with their telemedicine visits. Common issues that were raised with the use of telemedicine included difficulty procuring physical laboratory results and a lack of personal warmth during telemedicine visits. The work flows created based on these suggestions will both enhance safety in treating patients and allow for the best possible care. Although the use of telemedicine in rural areas has increased steadily over the years, its use was rapidly implemented during the onset of the coronavirus disease 2019 (COVID-19) crisis. Due to this rapid implementation, there is a lack of standardized work flows to assess and treat for various nephrotic conditions, symptoms, treatment modalities, and transition processes in the pediatric population. To provide a foundation/suggestion for future standardized work flows, the authors of this report have developed standardized work flows using the Delphi method. These work flows were informed based on results from cross-sectional surveys directed to patients and providers. Most patients and providers were satisfied, 87% and 71%, respectively, with their telemedicine visits. Common issues that were raised with the use of telemedicine included difficulty procuring physical laboratory results and a lack of personal warmth during telemedicine visits. The work flows created based on these suggestions will both enhance safety in treating patients and allow for the best possible 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 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 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| 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 | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».