Acceptability and Feasibility of a Prototype Regional Disaster Teleconsultation System for COVID-19 Pandemic Response: Pilot Field Test
Notice bibliographique
Résumé
Background: Disaster telehealth can be used to provide rapid access to remote specialty expertise and virtual surge capacity for overwhelmed local clinicians. The Regional Disaster Health Response System (RDHRS) is developing a disaster teleconsultation system for cross-jurisdictional care in the United States. In 2020, the Region 1 RDHRS provided Massachusetts hospitals access to disaster teleconsultation services with out-of-state critical care experts during the first wave of the COVID-19 pandemic response. Objective: We aimed to field-test (1) the acceptability and feasibility of using a prototype, web-based disaster teleconsultation platform with minimal-to-no user training and (2) the feasibility of deploying a national volunteer expert pool to access out-of-state expertise. Methods: This was a prospective, mixed methods, observational study. We recruited field clinicians from Massachusetts hospitals and out-of-state critical-care physicians as experts for a 2-week pilot (June 2020). Experts were trained to use a prototype platform, while field clinicians received a just-in-time tool. Field clinicians requested teleconsultations for hospitalized patients with COVID-19 (clinical call) or simulated patients (test call). We collected demographics, call performance data, and Telehealth Usability Questionnaire (TUQ) ratings to measure acceptability (primary outcome; total usability score ≥6 of 7) and feasibility (secondary outcome; interface, interaction quality, and reliability items), and interviewed participants. We report descriptive statistics and key themes using the Technology Acceptance Model framework. Results: Ten experts from 6 states and 17 field clinicians from 4 hospitals participated. All experts and 10 field clinicians completed postpilot questionnaires (74% response overall). Of these, 20% had previously used telemedicine in a disaster. In total, 50 test calls and no clinical calls were logged. Most (70%) made ≥1 call; 22% (95% CI 10%-34%) connected successfully. The median time to connect was 1.6 (IQR 3.2) minutes. Among field clinician respondents, 50% used smartphone devices, 40% hospital desktop computers, and 10% laptop computers to access RDHRS teleconsultation services. Calls failed due to platform routing errors (49%), hospital computers without cameras or microphones (10%), firewalls (8%), and expert notification failures (5%). The mean total usability score was 5.6 (SD 1.3). TUQ item scores were highest in usefulness (mean 6.0, SD 1.1) and ease-of-use (mean 6.0, SD 1.4), and lowest in reliability (mean 2.4, SD 1.4). Participants were comfortable using the platform. Those with difficulty identified discomfort with technology as the cause. All experts were willing to participate in a national expert registry and obtain emergency licensure, and most (80%) were willing to serve on a volunteer, unpaid basis. Conclusions: Clinicians found the prototype platform acceptable, but the workflow requires revision to reduce call failure and improve feasibility and reliability for future use with minimal-to-no training. Using familiar clinical workflows for emergency consultation and mobile devices with camera and microphone capabilities could improve call performance and reliability.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,015 | 0,031 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».