Abstract B104: Identifying gaps in equitable cancer care: insights from US-based oncology professionals engaged in continuing medical education
Notice bibliographique
Résumé
Abstract Introduction: A previous evaluation of a five-part accredited continuing medical education (CME) designed to inspire action for equitable cancer care amongst US-based multidisciplinary oncology care team members, showed significant improvements in relevant knowledge and confidence (pre to post activity). This study aimed to revisit the data collected in the scope of this project to identify remaining challenges in ensuring equitable cancer care is delivered to all patients, with underlying gaps in knowledge, confidence and attitude that may be addressed through future CME. Methods: A secondary analysis of data was performed on quantitative (case-based multiple-choice) responses collected from US-based HCPs who completed at least one of the five accredited CME activities that were part of the program titled “Addressing Racial Disparities in Cancer Care”. Questions assessed learners’ knowledge, confidence, and attitudes after exposure to the CME. Crosstabulations with chi-square statistical tests compared quantitative responses by sub-group. The analysis focused on post-CME data to identify remaining educational gaps, with the aim of informing the development of future CME programs. Results: The five-part CME education reached 1151 unique HCPs involved in cancer care, with activity participation varying between n=103 to n=433. The profession/specialty sub-group most represented in aggregated responses across the five-part CME were registered nurses specialized in hematology/oncology (n=575/1145, 50%). Across US regions, respondents were mostly located in South US (n=446/1150, 39%). A challenge in helping patients navigate socio- economic barriers to oncology care was found, with the following four related gaps affecting a portion of respondents post-CME exposure: 1) misconception that the most important determinant of treatment adherence is a patient’s perceived treatment efficacy rather than optimal patient-provider communication (n=57/400, 14%), 2) sub-optimal knowledge of the impact of a patient’s community and/or partner on influencing their treatment-seeking behavior (n=31/97, 32%), 3) sub-optimal knowledge of necessary steps to address the root cause of a patients’ missed appointments (n=36/227, 16%), 4) sub-optimal confidence in addressing a patients’ personal circumstances limiting their access to cancer-care (n=424/1151, 37%). Conclusions: This study identified remaining gaps in knowledge, confidence and attitude among US-based HCPs post-exposure to a CME activity aimed at promoting equitable cancer care. Considering these gaps were observed post-education, the actual proportion of US-based HCPs affected is likely underestimated. Future continuing learning initiatives aimed at addressing cancer care disparities in the US should consider targeting gaps identified in this study by challenging learners to re-consider their knowledge, beliefs and confidence in best approaches to navigating the socio-economic barriers hindering patients from seeking cancer care (e.g., via adaptive learning, peer-to-peer learning). Citation Format: Monica Augustyniak, Karen Eldridge, Jayne Gurtler, Benyam Muluneh, Amy DePue, Julia Rodriguez-O'Donnell, Stacy Atkinson, Sophie Péloquin, Ann Murphy, Patrice Lazure. Identifying gaps in equitable cancer care: insights from US-based oncology professionals engaged in continuing medical education [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B104.
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 | 0,007 | 0,022 |
| 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 | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».