Pediatric Primary Care Providers’ Perspectives on Telehealth Platforms to Support Care for Transgender and Gender-Diverse Youths: Exploratory Qualitative Study
Notice bibliographique
Résumé
BACKGROUND: Access to gender-affirming care services for transgender and gender-diverse youths is limited, in part because this care is currently provided primarily by specialists. Telehealth platforms that enable primary care providers (PCPs) to receive education from and consult specialists may help improve the access to such services. However, little is known about PCPs' preferences regarding receiving this support. OBJECTIVE: This study aimed to explore pediatric PCPs' perspectives regarding optimal ways to provide telehealth-based support to facilitate gender-affirming care provision in the primary care setting. METHODS: PCPs who had previously requested support from the Seattle Children's Gender Clinic were recruited to participate in semistructured, 1-hour web-based interviews. Overall, 3 specialist-to-PCP telehealth modalities (tele-education, electronic consultation, and telephonic consultation) were described, and the participants were invited to share their perspectives on the benefits and drawbacks of each modality, which modality would be the most effective, and the most important characteristics or outcomes of a successful platform. Interviews were transcribed and analyzed using a reflexive thematic analysis framework. RESULTS: The interviews were completed with 15 pediatric PCPs. The benefits of the tele-education platform were developing a network with other PCPs to facilitate shared learning, receiving comprehensive didactic and case-based education, having scheduled education sessions, and increasing provider confidence. The drawbacks were requiring a substantial time commitment and not allowing for real-time, patient-specific consultation. The benefits of the electronic consultation platform were convenient and efficient communication, documentation in the electronic health record, the ability to bill for provider time, and sufficient time to synthesize information. The drawbacks of this platform were electronic health record-related difficulties, text-based communication challenges, inability to receive an answer in real time, forced conversations with patients about billing, and limitations for providers who lack baseline knowledge. With respect to telephonic consultation, the benefits were having a dialogue with a specialist, receiving compensation for PCP's time, and helping with high acuity or complex cases. The drawbacks were challenges associated with using the phone for communication, the limited expertise of the responding providers, and the lack of utility for nonemergent issues. Regarding the most effective platform, the responses were mixed, with 27% (4/15) preferring the electronic consultation, 27% (4/15) preferring tele-education, 20% (3/15) preferring telephonic consultation, and the remaining 27% (4/15) suggesting a hybrid of the 3 models. CONCLUSIONS: A diverse suite of telehealth-based training and consultation services must be developed to meet the needs of PCPs with different levels of experience and training in gender-affirming care. Beyond the widely used telephonic consultation model, electronic consultation and tele-education may provide important alternative training and consultation opportunities to facilitate greater PCP independence and promote wider access to gender-affirming care.
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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 | 0,013 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,007 | 0,005 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 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 ».