Virtual Dermatology and the COVID-19 Pandemic in a Resource-Limited Country Such as Nepal
Notice bibliographique
Résumé
Background The COVID-19 pandemic has caused nationwide lockdown, which led to the disruption of health services. Despite being a rising health care modality in Nepal, virtual dermatology services became an effective tool to provide dermatologic care through web-based consultations throughout the country. Therefore, we assessed the implementation of teledermatology services at our center to provide uninterrupted health services across the country during the pandemic. Objective This study aimed to evaluate the clinicodemographic profile of patients using teledermatology services and patient acceptance of this service. Methods A retrospective, single-center, observational study was carried out. Clinicodemographic data from the patients using teledermatology services were obtained and analyzed. A set of questionnaires regarding patients’ acceptance of teledermatology services were administered to the patients through a survey via telephone calls, and the obtained data were interpreted. Results A total of 122 teleconsultations were carried out within the country. The mean age of patients was 33.48 (SD 17.89) years. Of these 122 patients, 79 (64.8%) were from outside and 43 (35.2%) were from inside the city where the institute is located. The average distance from the institute to the patients’ residence was approximately 144.84 (SD 157.20) km, and the mean travel time was approximately 385.31 (SD 889.52) minutes. In total, 89 patients could be contacted, of whom 81 (91%) found the service easy to use, 75 (84.3%) were able to express their problems in a manner similar to that during direct visits, 49 (55.05 %) thought that the teleconsultation was the same as an in-person visit, 80 (89.9%) were satisfied, and 85 (95.5%) agreed to use teledermatology services in the future. Superficial fungal infection was the most common diagnosis (24.6 %). Newly registered patients were more satisfied than follow-up patients (96.36% vs 79.41%, respectively; P=.01). Conclusions This study highlights the importance of virtual dermatology services to deliver dermatologic care during the pandemic in Nepal. In the future, this program has a promising role in providing health care services to meet the medical needs of patients. Conflicts of Interest None declared.
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 | 0,000 | 0,000 |
| 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 | 0,000 | 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 ».