The Physician Anesthesia Workforce in Canada From 1996 to 2018: A Longitudinal Analysis of Health Administrative Data
Notice bibliographique
Résumé
BACKGROUND: A robust anesthesia workforce is essential to the provision of safe surgical, obstetrical, and critical care but information describing the physician anesthesia workforce and volume of clinical services delivered in Canada is limited. This study examines the Canadian physician anesthesia workforce, exploring trends in physician characteristics and activity levels over time. Practice patterns of specialist anesthesiologists and family physician anesthetists (FPAs) working in urban and rural communities were of particular interest. METHODS: Physicians who provided anesthesia care between 1996 and 2018 were identified using health administrative data from the Canadian Institute of Health Information (CIHI). In addition, data from the Canadian Post-MD Education Registry (CAPER) were used to characterize physicians pursuing postgraduate anesthesia training (1996-2019). Descriptive analyses of physician demographics, training, location, specialty designations, and volume of clinical services were undertaken. RESULTS: Between 1996 and 2018, the anesthesia workforce grew 1.8-fold to 3681 physicians, including 536 FPAs. Over the same time, nerve block services increased 7-fold, and payments for other anesthesia services increased 5-fold. The average age of the anesthesiology workforce increased by 2.3 years and the annual retirement rate was 3%. The workforce has become more gender balanced but remains predominantly male (73% in 2018). The proportion of physicians who were trained internationally (about 30%; 38% in rural areas) remained stable (and higher than that in the overall physician workforce). FPAs provided most anesthesia care in rural Canada and their attrition rate was generally 2- to 3-fold higher than specialists. Physicians in the rural anesthesia workforce provided anesthesia services more intensively over time. Relatively few FPAs who left the anesthesia workforce entered full retirement and they instead contributed other medical services to their communities. CONCLUSIONS: This study provides foundational information regarding anesthesia workforce capacity over a 22-year period, including insights into demographics, locations of practice, and clinical volumes. The results do not quantify the gap between service capacity and need; however, they support the need for a national workforce strategy to achieve equitable access to sustainable anesthesia services in Canada, particularly for rural communities.
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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 | 0,003 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,004 | 0,014 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».