Identifying Feasible and Impactful Approaches to Implementing Telehealth in Rural Washington Communities: Group Concept Mapping Study
Notice bibliographique
Résumé
Background The expansion of telehealth use during the COVID-19 pandemic increased access to health care services for many US residents. This is particularly true for provider-to-patient telehealth communication. In rural communities, telehealth can increase access to health care services that would otherwise be limited due to geographic and distance barriers. The adoption of telehealth in rural communities, however, has been hindered by technology barriers, lack of community awareness, and lack of provider buy-in. The purpose of this study was to explore community-identified approaches to improving telehealth access in rural North Central Washington. Objective The aim of this study was to identify, group, and rate approaches to expanding and integrating telehealth in rural communities in North Central Washington. Methods We used group concept mapping, a participant-engaged, mixed method approach, to explore participant perspectives and preferences. Purposively sampled participants were community leaders and stakeholders in rural North Central Washington. Participants brainstormed strategies for implementing and expanding community telehealth access in their community and sorted them into conceptually similar groups. Strategies were then rated by participants in terms of potential impact, feasibility, and the cost of implementation. Quantitative analyses included multidimensional scaling and hierarchical cluster analysis to produce a cluster map and pattern match graph for interpreting the community members’ ideas and preferences. Results Participant brainstorming yielded 70 strategies for implementing telehealth in rural North Central Washington. Strategies were individually sorted into groups (point map stress value 0.21), producing a 6-cluster solution. The clusters were “Community infrastructure,” “Ensuring access to telehealth technology,” “Technology infrastructure for telehealth,” “Training/awareness of telehealth,” “State- and policy-level considerations,” and “Health care systems engagement and delivery.” Participants rated “Training/awareness of telehealth” and “Health care systems engagement and delivery” to be highly impactful and feasible approaches. The “Training/awareness of telehealth” cluster included strategies such as educating community members that telehealth is an easy, reliable, convenient, and private way to access health care and providing community training on how to access health care remotely. The latter cluster, “Health care systems engagement and delivery,” included approaches that were ranked as highly feasible and impactful, such as engaging with clinics and providers on overcoming barriers to implementing telehealth services or ensuring that local health clinic staff is on board with telehealth as an alternative platform to provide services. Conclusions Strategies identified and rated by participants incorporate the importance of community engagement in telehealth implementation, including educating community members about telehealth and engaging with community health clinics to facilitate use by providers. Community partners in North Central Washington will use these findings, along with additional community survey data, broadband speed test data, and provider input, to increase access to telehealth in their rural and remote communities. Conflicts of Interest None declared.
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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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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 | 0,001 |
| 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 ».