The aging anesthesiologist: a narrative review and suggested strategies
Notice bibliographique
Résumé
PURPOSE: To address an aging anesthesia workforce, we review the relevant changes and implications associated with age in order to stimulate discussion at the individual, local, and national levels regarding appropriate changes in practice aimed at protecting patient safety. PRINCIPAL FINDINGS: In a 2013 survey of Canadian Anesthesiologists, 22% were aged 55-64 yr, 7% were aged 65-74 yr, and 3% were older than 74 yr. Clinical abilities decline with age, making older anesthesiologists more likely than their younger colleagues to be associated with adverse patient events. Anesthesiologists older than 65 yr in Ontario, Quebec, and British Columbia had 50% more cases involving litigation and almost twice the number of cases involving severe patient injury compared with anesthesiologists younger than 51 yr of age. In the absence of overt deterioration in skills, decisions about reducing activities and retirement are left largely to individuals despite their limited ability to self-assess competence. This state of affairs may contribute to the increased incidence of adverse events and poor patient outcomes. CONCLUSIONS: Provincial regulatory bodies have peer assessment programs to evaluate physicians at random, following a complaint, and at certain ages, but all have limitations. Simulation has been used widely for training and assessment in the aviation industry as well as in automobile driving exams. Simulation can assess crisis recognition and management, which is crucial in anesthesiology and not well assessed by other methods, and could assist elderly anesthesiologists during the pre-retirement phase of their careers. A standardized schedule for winding down would have advantages for physicians, their department, and their patients. A suggested schedule might include no further on-call duties for those aged 60 yr and older, no further high-acuity cases for those aged 65 yr and older, and retirement from operating room (OR) clinical practice (with possible continuation of non-OR clinical or other non-clinical activities, if desired) at age 70 yr. These timelines could be extended with satisfactory performance in annual simulation sessions involving assessment and practice in crisis management.
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 | 0,007 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,005 |
| 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 ».