Needs Assessment: Towards a More Responsive Canadian Society of Nephrology Annual General Meeting (CSN AGM) Program
Notice bibliographique
Résumé
BACKGROUND: A critical feature of any continuing medical education (CME) program is the inclusion of a needs assessment for its target audience. This assessment must identify both perceived and unperceived needs, so as to best capture the entire spectrum of learning opportunities for the group. OBJECTIVE: We describe the process developed by the Canadian Society of Nephrology (CSN) to enhance the educational effectiveness of its Annual General Meeting program. DESIGN: The design of this study is the analysis of a survey questionnaire and of the Canadian Organ Replacement Registry (CORR) database. PARTICIPANTS: We surveyed members of the CSN and analyzed patient data from CORR aggregated by center. MEASUREMENTS: We tabulated votes in the survey by topic. We assessed the extent to which centers achieved CSN guideline targets on the clinical management of patients on dialysis. METHODS: Perceived needs: a CSN panel constructed a list of topics, which was amplified by the inclusion of topics based on members' text responses to open-ended questions during previous iterations of this process. CSN members specified their top five choices, using an online survey instrument. Unperceived needs: an expert panel determined achievable thresholds for a number of quality metrics associated with dialysis. The quality metrics were identified from CSN guidelines. Using patient data in the CORR database, we generated center-specific performance estimates for each quality metric and constructed ratios comparing the performance of each center with the achievable threshold. We triangulated the results of the two assessments. RESULTS: The response rate for the perceived needs assessment survey was 16 %. This assessment identified "Primary and Secondary Glomerulonephritis" as the non-dialysis topics and "Infectious Complications of Dialysis Access" and "Volume Status and Hypertension on Dialysis" as the dialysis topics with the highest perceived learning needs. In the unperceived needs assessment, "Vascular Access Type" and "Vascular Access Monitoring" were identified as having the highest learning needs. Triangulation identified "Vascular Access Type" and "Vascular Access Monitoring" as high needs topics. LIMITATIONS: Perceived needs assessment: Some topics were much more general than others, which could have led to over-selection. The response rate of 16 % limits the robustness of generalization to the membership as a whole or to all meeting attendees. Unperceived needs assessment: The assessment was limited by the data that CORR actually collects; many aspects of general nephrology practice, including glomerulonephritis, are not covered. The level of evidence underlying the various guidelines was variable, and in some cases, poor. A validated approach to data analysis in this area is lacking. CONCLUSIONS: To our knowledge, this is the first published example of a needs assessment for a nephrology CME event that considers both the perceived and unperceived needs of the membership. The results of this exercise are currently being used to assist in the development of a more responsive CME program.
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 | 0,106 | 0,122 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,008 | 0,004 |
| Études des sciences et des technologies | 0,007 | 0,003 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,006 | 0,010 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 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 ».