A Survey to Assess the Educational Needs of Clinicians in Maternal Hematology
Notice bibliographique
Résumé
Introduction With advancement in medical knowledge and comprehensive care more women with hematological disorders are proceeding with pregnancy. These women have unique needs during the perinatal period, where the intersection of the Hematological disease and pregnancy can mutually impact each other, resulting in significant morbidity and even mortality. Hematologists, Internal Medicine (IM) physicians and Obstetricians are increasingly faced with the complex care of these women. The aim of this study is to assess the learning needs of these stakeholders in the care of pregnant women with hematological conditions to direct the development of educational activities. Methods We conducted a cross-sectional study using a self-administered electronic questionnaire sent to Hematologists, Obstetricians, Maternal-Fetal Medicine (MFM) Specialists and IM Specialists across Canada. The study was approved by the Research Ethics Board of Sinai Health System in Toronto, Ontario. The questionnaire assessed physician characteristics, physicians' previous educational experiences in Maternal Hematology, self-assessment of knowledge and confidence in managing pregnancy in these women, and preferences for further learning activities in Maternal Hematology. The questionnaire was pilot tested by two hematology resident physicians and two MFM fellow physicians at the University of Toronto and modifications were made to the survey based on this feedback. The survey was administered electronically in English in collaboration with the Canadian Hematology Society and Canadian MFM program directors, using an online survey-distributing website, Survey Monkey™. Participation was voluntary and anonymous. Data were exported into Excel (Microsoft, Redmond, Washington, USA) for statistical analysis. Following overall descriptive analyses (frequencies and proportions), responses were further tabulated by participant specialty. Results The survey was administered from December 2019 to March 2020. 97 participants responded to the survey, and 82 (84.5%) completed it. The 15 (15.5%) incomplete surveys (completion of less than 25% of the questionnaire), were excluded from analysis. Respondents included 17 (20.7 %) MFM specialists, 21 (25.6%) Obstetricians, 34 (41.5%) hematologists and five (6.1 %) IM physicians. Half of respondents had < 5 years of practice (52.6%%) and there was a similar distribution of respondents with 5-10 years (12.8%) and 11-15 years (12.8%) in practice. Most respondents were female (69.6%). Overall, 38% of respondents described the quality of their prior educational experiences as 'very useful' or 'extremely useful'. Approximately half of the respondents rated their knowledge of Maternal Hematology as intermediate, 25% as beginner and 25% as advanced. The majority of Hematologists and IM specialists (64%) considered their knowledge in Maternal Hematology as 'intermediate'; specialists in Obstetrics and MFM were divided with 30.8% considering their knowledge at the 'beginner' level and 38.5% at the 'intermediate' level. Only 3.7% of respondents described their knowledge level as 'expert'. Most respondents in Obstetrics and MFM (84.2%) considered knowledge of how to diagnose venous thromboembolism during pregnancy as 'extremely important followed by knowledge of thromboprophylaxis (63.2%) and therapeutic anticoagulation during pregnancy (63.2%) (Figure 1). Amongst Hematology and IM physicians, thrombotic microangiopathy was rated by the greatest proportion of respondents (59%) as being "extremely important". For the format of educational activity, three quarters of the respondents preferred a blended learning program, which would include a combination of face-to-face teaching and technology-enhanced learning activities. Respondents predominantly (76.2%) agreed that learning collaboratively with other specialties in a combined Maternal Hematology program would be helpful. Conclusion These results suggest that an interdisciplinary learning program involving collaboration across relevant subspecialties would be preferred by participants for the teaching and learning of Maternal Hematology. A program involving blended (in-person and technology-enhanced) learning modalities was viewed favorably by participants, and should aim to incorporate various topics, which may be prioritized differently amongst specific subspecialties. Disclosures Malinowski: Alexion: Other: Advisory board; Alexion: Honoraria. Shehata:Ferring: Honoraria.
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 | 0,004 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».