Optimizing Electronic Consultation Between Primary Care Providers and Psychiatrists: Mixed-Methods Study
Notice bibliographique
Résumé
BACKGROUND: The use of electronic consultation (e-consult) between primary care providers (PCPs) and psychiatrists has potential, given the high prevalence of mental health issues in primary care and problematic access to specialist care. Utilization and uptake, however, appears to be lower than would be expected. OBJECTIVE: This study aimed to examine actual utilization of e-consult between PCPs and psychiatrists and investigate the perceptions of PCPs about this form of psychiatric advice to inform how to optimize the utility and thereby the uptake of this service. METHODS: In this mixed-methods study, we conducted a chart review of psychiatry e-consults (N=37) over 2 platforms during early implementation in Ontario, Canada, as well as 3 group interviews and 1 individual interview with PCPs (N=10) with variable experience levels and from a range of practice settings. The chart review assessed response times and referral content including the type of request, referral attachments, and consultant responses. Interviews explored the perceptions of the PCPs about the uses and barriers of psychiatry e-consult. Thematic content analysis of interview data identified common themes as well as themes unique to different provider profiles (eg, experienced PCPs vs new PCPs and rural vs urban practice). On the basis of interpretation of the quantitative and qualitative findings, we developed recommendations for the optimization of psychiatry e-consultation services. RESULTS: During the study period, psychiatry e-consults comprised 3.66% (49/1339) of all e-consults submitted on the studied platforms. Among the e-consults reviewed, different psychiatric diagnoses were represented: 70% of requests (26/37) queried about medication safety or side effects, whereas 59% (22/37) asked about psychiatric symptom management. Moreover, 81% (30/37) of e-consults were answered within 24 hours, and 65% (24/37) were addressed in a single exchange. Themes from the interview data included psychiatry having a complexity that differentiates it from other specialties and may limit the utility of e-consult, other than for psychopharmacology advice. Variability in awareness exists in the way e-consultation could be used in psychiatry, with new PCPs feeling unsure about the appropriateness of a question. In general, new PCPs and PCPs practicing in rural areas were more receptive to psychiatry e-consult. PCPs viewed e-consult as an opportunity to collaborate and desired that it be integrated with other available services. Recommendations include the need for appropriate specialist staffing to address a wide range of requests, adequate education to referrers regarding the use of psychiatry e-consult, and the need to integrate psychiatry e-consult with other geographically relevant services, given the complexity of psychiatric issues. CONCLUSIONS: E-consult is a viable and timely way for PCPs to get much-needed psychiatric advice. For optimizing its utility and uptake, e-consult needs to be integrated into reliable care pathways with adequate referrer and consultant preparation.
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 | 0,033 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».