Integrating Patient-Centered Electronic Health Record Communication Training into Resident Onboarding: Curriculum Development and Post-Implementation Survey Among Housestaff
Notice bibliographique
Résumé
BACKGROUND: Electronic health record (EHR) use can enhance or undermine the ability of providers to deliver effective, humanistic patient-centered care. Given patient-centered care has been found to positively impact patient health outcomes, it is critical to provide formal education on patient-centered EHR communication skills. Unfortunately, despite increasing worldwide EHR adoption, few institutions educate trainees on EHR communication best practices. OBJECTIVE: The goal of this research was to develop and deliver mandatory patient-centered EHR training to all incoming housestaff at the University of Chicago. METHODS: We developed a brief patient-centered EHR use curriculum highlighting best practices based on a literature search. Training was embedded into required EHR onboarding for all incoming housestaff (interns, residents, and fellows) at the University of Chicago in 2015 and was delivered by institutional Clinical Applications Trainers. An 11-item posttraining survey consisting of ten 5-point Likert scale questions and 1 open-ended question was administered. Responses at the high end of the scale were grouped to dichotomize data. RESULTS: All 158 of the incoming 2015 postgraduate trainees participated in training and completed surveys (158/158, 100.0%). Just over half (86/158, 54.4%) were interns and the remaining were residents and fellows (72/158, 45.6%). One-fifth of respondents (32/158, 20.2%) were primary care trainees (defined as internal medicine, pediatric, and medicine-pediatric trainees), and the remaining 79.7% (126/158) were surgical or specialty trainees. Self-perceived pre- versus posttraining knowledge of barriers, best practices, and ability to implement patient-centered EHR skills significantly increased (3.1 vs 3.9, P<.001 for all). Most felt training was effective (90.5%), should be required (86.7%), and would change future practice as a result (70.9%). The only significant difference between intern and resident/fellow responses was prior knowledge of patient-centered EHR use barriers; interns endorsed higher prior knowledge than resident peers (3.27 vs 2.94 respectively, P=.03). Response comparison of specialty or surgical trainees (n=126) to primary care trainees (n=32) showed no significant differences in prior knowledge of barriers (3.09 vs 3.22, P=.50), of best practices (3.08 vs 2.94, P=.37), or prior ability to implement best practices (3.11 vs 2.84, P=.15). Primary care trainees had larger increases posttraining than surgical/specialty peers in knowledge of barriers (0.8 vs 0.7, P=.62), best practices (1.1 vs 0.8, P=.08), and ability to implement best practices (1.1 vs 0.7, P=.07), although none reached statistical significance. Primary care trainees also rated training as more effective (4.34 vs 4.09, P=.03) and felt training should be required (4.34 vs 4.09, P=.10) and would change their future practice as a result (4.13 vs 3.73, P=.02). CONCLUSIONS: Embedding EHR communication skills training into required institutional EHR training is a novel and effective way to teach key EHR skills to trainees. Such training may help ground trainees in best practices and contribute to cultivating an institutional culture of humanistic, patient-centered EHR use.
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 | 0,006 | 0,002 |
| 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 | 0,002 | 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 ».