Mobile health school screening and telemedicine referral to improve access to specialty care in rural Alaska: a cluster- randomised controlled trial
Notice bibliographique
Résumé
BACKGROUND: School-based programmes, including hearing screening, provide essential preventive services for rural children. However, minimal evidence on screening methodologies, loss to follow-up, and scarcity of specialists for subsequent care compound rural health disparities. We hypothesised telemedicine specialty referral would improve time to follow-up for school hearing screening compared with standard primary care referral. METHODS: In this cluster-randomised controlled trial conducted in 15 rural Alaskan communities, USA, we randomised communities to telemedicine specialty referral (intervention) or standard primary care referral (control) for school hearing screening. All children (K-12; aged 4-21 years) enrolled in Bering Straight School District were eligible. Community randomisation occurred within four strata using location and school size. Participants were masked to group allocation until screening day, and assessors were masked throughout data collection. Screening occurred annually, and children who screened positive for possible hearing loss or ear disease were monitored for 9 months from the screening date for follow-up. Primary outcome was the time to follow-up after a positive hearing screen; analysis was by intention to treat. The trial was registered with ClinicalTrials.gov, NCT03309553. FINDINGS: We recruited participants between Oct 10, 2017, and March 28, 2019. 15 communities were randomised: eight (750 children) to telemedicine referral and seven (731 children) to primary care referral. 790 (53·3%) of 1481 children screened positive in at least one study year: 391 (52∤1%) in the telemedicine referral communities and 399 (50∤4%) in the primary care referral communities. Of children referred, 268 (68·5%) in the telemedicine referral communities and 128 (32·1%) in primary care referral communities received follow-up within 9 months. Among children who received follow-up, mean time to follow-up was 41·5 days (SD 55·7) in the telemedicine referral communities and 92·0 days (75·8) in the primary care referral communities (adjusted event-time ratio 17·6 [95% CI 6·8-45·3] for all referred children). There were no adverse events. INTERPRETATION: Telemedicine specialty referral significantly improved the time to follow-up after hearing screening in Alaska. Telemedicine might apply to other preventive school-based services to improve access to specialty care for rural children. FUNDING: Patient-Centered Outcomes Research Institute.
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 | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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 ».