Improving outcomes through the development of quality indicators in renal cell cancer.
Notice bibliographique
Résumé
422 Background: Optimal quality of care is necessary for ideal outcomes, and quality indicators (QI) are increasingly being used to measure quality of care. In renal cell carcinoma (RCC), there is a paucity of information defining such optimal care. This is particularly important as care of RCC patients is becoming increasingly complicated with more options and requiring greater expertise. The goal of this study was to identify QI for RCC across the entire disease spectrum from presentation to palliation. Methods: A multidisciplinary expert panel (13 members) of medical and urologic oncologists from across Canada reviewed potential QI. These potential QI were identified from a systematic review of the literature. In addition, panel members were encouraged to suggest additional potential QI. A modified Delphi technique was utilized to select QI that were both relevant and practical to RCC; this technique incorporated 2 email questionnaires and 1 in-person meeting. Results: From 250 citations in the systematic review, 34 possible QI were identified; 24 additional potential QI were suggested by panel members. A final set of 23 QI were established by the expert panel. These were distributed across the RCC disease spectrum as follows (number of QI in parentheses): screening (1), diagnosis and prognosis (3), management of localized disease (7), surgical management of locally advanced or metastatic disease (3), systemic therapy (4), and follow-up (3). These 21 QI focused largely on the treatment of RCC. In addition, two QI related to survival outcomes (overall and progression-free) were selected. An example of a QI in localized disease is the proportion of patients undergoing partial nephrectomy for tumors < 4 cm. An example in advanced disease is the proportion of patients who are assessed by members of a multidisciplinary genitourinary cancer team. The final 23 QI selected will be presented in detail. Conclusions: A systematic, consensus-based approach was used to determine relevant QI in RCC care. These 23 QIs will provide a means of evaluating the quality of RCC care in an effort to improve outcomes for our patients. The next step will be to establish a means of measuring each of these QI based on defined or yet to be defined benchmarks.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,001 |
| 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 ».