Neurosurgery residency program in Yogyakarta, Indonesia: improving neurosurgical care distribution to reduce inequality
Bibliographic record
Abstract
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."
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".