28 How is Postpartum Depression Currently Diagnosed and Managed? Insights from a Virtual Patient Simulation
Notice bibliographique
Résumé
Abstract Objectives The goal of this study was to determine physician performance in diagnosis and management of postpartum depression (PPD) and to provide needed education in the consequence free environment of a virtual patient simulation (VPS). Methods ∙ A continuing medical education activity was delivered via an online VPS learning platform that offers a lifelike clinical care experience with complete freedom of choice in clinical decision-making and expert personalized feedback to address learner’s practice gaps ∙ Physicians including psychiatrists, primary care physicians (PCPs), and obstetricians/gynecologists (ob/gyns) were presented with two cases of PPD designed to model the experience of actual practice by including use of electronic health records ∙ Following virtual interactions with patients, physicians were asked to make decisions regarding assessments, diagnoses, and pharmacologic therapies. The clinical decisions were analyzed using a sophisticated decision engine, and clinical guidance (CG) based on current evidence-based recommendations was provided in response to learners’ clinical decisions ∙ Impact of the education was measured by comparing participant decisions pre- and post-CG using a 2-tailed, paired t-test; P <.05 was considered statistically significant ∙ The activity launched on Medscape Education on April 26, 2018, and data were collected through to June 17,2018. Results ∙ From pre- to post-CG in the simulation, physicians were more likely to make evidence-based clinical decisions related to: ∙ Ordering appropriate baseline tests including tools/scales to screen for PPD: in case 1, psychiatrists (n=624) improved from 34% to 42% on average (P<.05); PCPs (n=197) improved from 38% to 48% on average (P<.05); and, ob/gyns (n=216) improved from 30% to 38% on average (P<.05) ∙ Diagnosing moderate-to-severe PPD: in case 2, psychiatrists (n=531) improved from 46% to 62% (P<.05); PCPs (n=154) improved from 43% to 55% (P<.05); and, ob/gyns (n=137) improved from 55% to 73% (P<.05) ∙ Ordering appropriate treatments for moderate-to-severe PPD such as selective serotonin-reuptake inhibitors: in case 2, psychiatrists (n=531) improved from 47% CG to 75% (P<.05); PCPs (n=154) improved from 55% to 74% (P<.05); and, ob/gyns (n=137) improved from 51% to 78% (P<.05) ∙ Interestingly, a small percentage of physicians (average of 5%) chose investigational agents for PPD which were in clinical trials pre-CG, and this increased to an average of 9% post-CG Conclusions Physicians who participated in VPS-based education significantly improved their clinical decision-making in PPD, particularly in selection of validated screening tools/scales, diagnosis, and pharmacologic treatments based on severity. Given that VPS immerses physicians in an authentic, practical learning experience matching the scope of clinical practice, this type of intervention can be used to determine clinical practice gaps and translate knowledge into practice. Funding Acknowledgements: The educational activity and outcomes measurement were funded through an independent educational grant from Sage Therapeutics, Inc.
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 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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| 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 ».