Using electronic consultations to identify hematology education needs in primary care
Notice bibliographique
Résumé
Abstract BackgroundTopics covered in primary care Continuing Professional Development (CPD) activities often do not reflect the real-world learning needs of physicians, leading to dissatisfaction and poor engagement. Few studies have rigorously evaluated the learning needs of primary care physicians (PCPs) as they relate to hematology. One way to objectively assess these needs is through analysis of questions submitted by PCPs to hematologists via an electronic consultation (eConsult) platform.The Champlain BASE eConsult service is a secure, web-based platform that allows PCPs to communicate directly with specialists for patient care advice. We analyzed the content of hematology eConsults to objectively assess PCP learning needs. These insights could be used to inform the planning and development of future hematology CPD activities. MethodsWe conducted a retrospective cross-sectional study of questions submitted by PCPs to hematologists between January 2018 and December 2022 on the Champlain BASE™ eConsult Service in Ottawa, Ontario, Canada. One hundred eConsults per year were randomly selected, for a total convenience sample size of 500 eConsults. Demographic data, including age and sex of patients, occupation of PCP (family doctor vs nurse practitioner), and response time taken by the hematologist, were collected and summarized. Questions were classified by content area and question type using the International Classification for Primary Care, version 3 (ICPC-3) framework. A subset of eConsults was analyzed in triplicate to ensure consistency, and discrepancies were resolved by consensus. We used descriptive statistics to identify the most common content areas and question types asked by PCPs to hematologists and summarized them in an ordered list by frequency. ResultsA total of 453 eConsults (90.6%) were initiated by physicians, and 47 (9.4%) were initiated by nurse practitioners. The average age of patients was 57.5 years (range 18.7 – 101.2 years), and 61.6% were female. A total of 743 unique questions were identified in the 500 eConsults, with more than one question being asked in almost half of all eConsults (42.2%). The average time taken by hematologists to answer an eConsult was 15.1 +/- 8.4 minutes.The most common content categories pertained to monoclonal gammopathy of undetermined significance (MGUS) (11.2%), anemia (8.6%), polycythemia (7.0%), elevated ferritin (6.8%), thrombocytopenia (6.5%), and lymphocytosis (6.1%). The most common type of questions asked by PCPs pertained to diagnosis, with 54.4% focusing on the recognition of specific signs and symptoms. This was followed by questions related to management, including appropriate referral pathways (16.4%) and condition-specific treatment strategies (14.5%). Conclusion The most common PCP knowledge gaps identified by this study pertained to MGUS, anemia, and polycythemia. Analysis of eConsult data can objectively identify PCP knowledge gaps, which can in turn inform the development of hematology-specific CPD curricula for PCPs.
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 | 0,001 | 0,001 |
| 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 ».