Hospital-Level Implementation Barriers, Facilitators, and Willingness to Use a New Regional Disaster Teleconsultation System: Cross-Sectional Survey Study
Notice bibliographique
Résumé
BACKGROUND: The Region 1 Disaster Health Response System project is developing new telehealth capabilities to provide rapid, temporary access to clinical experts across US jurisdictions to support regional disaster health response. OBJECTIVE: To guide future implementation, we identified hospital-level barriers, facilitators, and willingness to use a novel regional peer-to-peer disaster teleconsultation system for disaster health response. METHODS: We used the National Emergency Department Inventory-USA database to identify all 189 hospital-based and freestanding emergency departments (EDs) in New England states. We digitally or telephonically surveyed emergency managers regarding notification systems used for large-scale no-notice emergency events, access to consultants in 6 disaster-relevant specialties, disaster credentialing requirements before system use, reliability and redundancy of internet or cellular service, and willingness to use a disaster teleconsultation system. We examined state-wise hospital and ED disaster response capability. RESULTS: Overall, 164 (87%) hospitals and EDs responded-126 (77%) completed telephone surveys. Most (n=148, 90%) receive emergency notifications from state-based systems. Forty (24%) hospitals and EDs lacked access to burn specialists; toxicologists, 30 (18%); radiation specialists, 25 (15%); and trauma specialists, 20 (12%). Among critical access hospitals (CAHs) or EDs with <10,000 annual visits (n=36), 92% received routine nondisaster telehealth services but lacked toxicologist (25%), burn (22%), and radiation (17%) specialist access. Most hospitals and EDs (n=115, 70%) require disaster credentialing of teleconsultants before system use. Among 113 hospitals and EDs with written disaster credentialing procedures, 28% expected completing disaster credentialing within 24 hours, and 55% within 25-72 hours, which varied by state. Most (n=154, 94%) reported adequate internet or cellular service for video-streaming; 81% maintained cellular service despite internet disruption. Fewer rural hospitals and EDs reported reliable internet or cellular service (19/22, 86% vs 135/142, 95%) and ability to maintain cellular service with internet disruption (11/19, 58% vs 113/135, 84%) than urban hospitals and EDs. Overall, 133 (81%) were somewhat or very likely to use a regional disaster teleconsultation system. Large-volume EDs (annual visits ≥40,000) were less likely to use the service than smaller ones; all CAHs and nearly all rural hospitals or freestanding EDs were likely to use disaster consultation services. Among hospitals and EDs somewhat or very unlikely to use the system (n=26), sufficient consultant access (69%) and reluctance to use new technology or systems (27%) were common barriers. Potential delays (19%), liability (19%), privacy (15%), and hospital information system security restrictions (15%) were infrequent concerns. CONCLUSIONS: Most New England hospitals and EDs have access to state emergency notification systems, telecommunication infrastructure, and willingness to use a new regional disaster teleconsultation system. System developers should focus on ways to improve telecommunication redundancy in rural areas and use low-bandwidth technology to maintain service availability to CAHs and rural hospitals and EDs. Policies and procedures to accelerate and standardize disaster credentialing are needed for implementation across jurisdictions.
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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 | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 ».