Neurosurgery residency program in Yogyakarta, Indonesia: improving neurosurgical care distribution to reduce inequality
Notice bibliographique
Résumé
OBJECTIVE: Educating future neurosurgeons is of paramount importance, and there are many aspects that must be addressed within the process. One of the essential issues is the disproportion in neurosurgical care, especially in low- and middle-income countries (LMICs). As stated in their report "Global Surgery 2030," The Lancet Commission on Global Surgery has emphasized that the availability of adequate neurosurgical care does not match the burden of neurosurgical disease. A strong partnership with the local and national government is very desirable to improve the way everyone addresses this issue. In addition, international collaborative effort is absolutely essential for the transfer of knowledge and technology from a developed country to an LMIC. This paper shows what the authors have done in Yogyakarta to build an educational model that helps to improve neurosurgical care distribution in Indonesia and reduce the inequity between provinces. METHODS: The authors gathered data about the number of neurosurgical procedures that were performed in the sister hospital by using data collected by their residents. Information about the distribution of neurosurgeons in Indonesia was adapted from the Indonesian Society of Neurological Surgeons. RESULTS: The data show that there remains a huge disparity in terms of distribution of neurosurgeons in Indonesia. To tackle the issue, the authors have been able to develop a model of collaboration that can be applied not only to the educational purpose but also for establishing neurosurgical services throughout Indonesia. Currently they have signed a memorandum of understanding with four sister hospitals, while an agreement with one sister hospital has come to an end. There were more than 400 neurosurgical procedures, ranging from infection to trauma, treated by the authors' team posted outside of Yogyakarta. CONCLUSIONS: Indonesia has a high level of inequality in neurological surgery care. This model of collaboration, which focuses on the development of healthcare providers, universities, and related stakeholders, might be essential in reducing such a disparity. By using this model, the authors hope they can be involved in achieving the vision of The Lancet Commission on Global Surgery, which is "universal access to safe, affordable surgical and anesthesia care when needed."
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| 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 ».