Social disparities in the use of colonoscopy by primary care physicians in Ontario
Notice bibliographique
Résumé
BACKGROUND: It is unclear if all persons in Ontario have equal access to colonoscopy. This research was designed to describe long-term trends in the use of colonoscopy by primary care physicians (PCPs) in Ontario, and to determine whether PCP characteristics influence the use of colonoscopy. METHODS: We conducted a population-based retrospective study of PCPs in Ontario between the years 1996-2005. Using administrative data we identified a screen-eligible group of patients aged 50-74 years in Ontario. These patients were linked to the PCP who provided the most continuous care to them during each year. We determined the use of any colonoscopy among these patients. We calculated the rate of colonoscopy for each PCP as the number of patients undergoing colonoscopies per 100 screen eligible patients. Negative binomial regression was used to identify factors associated with the rate of colonoscopy, using generalized estimating equations to account for clustering of patients within PCPs. RESULTS: Between 7,955 and 8,419 PCPs in Ontario per year (median age 43 years) had at least 10 eligible patients in their practices. The use of colonoscopy by PCPs increased sharply in Ontario during the study period, from a median rate of 1.51 [inter quartile range (IQR) 0.57-2.62] per 100 screen eligible patients in 1996 to 4.71 (IQR 2.70-7.53) in 2005. There was substantial variation between PCPs in their use of colonoscopy. PCPs who were Canadian medical graduates and with more years of experience were more likely to use colonoscopy after adjusting for their patient characteristics. PCPs were more likely to use colonoscopy if their patient populations were predominantly women, older, had more illnesses, and if their patients resided in less marginalized neighborhoods (lower unemployment, fewer immigrants, higher income, higher education, and higher English/French fluency). CONCLUSIONS: There is substantial variation in the use of colonoscopy by PCPs, and this variation has increased as the overall use of colonoscopy increased over time. PCPs whose patients were more marginalized were less likely to use colonoscopy, suggesting that there are inequities in access.
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 | 0,000 | 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 | 0,000 |
| 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 ».