The Evaluation of a Surgical Task-Sharing Program in South Sudan
Bibliographic record
Abstract
Five billion people lack access to surgery, with the highest burden being in sub-Saharan Africa. As the surgical workforce is crucial in closing this gap, the University of British Columbia collaborated with Médecins Sans Frontières to create and launch the Essential Surgical Skills (ESS) task-sharing program, which consists of online learning modules and hands-on surgical training. Our study aimed to evaluate this pilot program. This is a mixed-method prospective cohort study to evaluate the effectiveness of the ESS program in South Sudan. Quantitative data included patient outcomes (complications, re-operation, and mortality), surgical proficiency of the trainees (quiz, entrustable professional activity (EPA), and logbook data), and electronic surveys. We used semi-structured interviews to collect qualitative data. From July 2019 to February 2021, three trainees performed 385 operations. The most common procedures were skin graft (14.8%) and abscess drainage (9.6%). A total of 172 EPAs were completed, of which 136 (79%) demonstrated the independence of the trainees. During the training, surgical mortality (0.56% vs. 0.13%, p = 0.0541) and morbidity (17% vs. 12%, p = 0.1767) remained unchanged from the pretraining phase. Interviews and surveys revealed that surgical knowledge and interprofessional teamwork improved throughout the training. The program empowered trainees to develop surgical career paths and increased their local acceptance among patients and other healthcare providers. This study confirmed the feasibility of a surgical task-sharing program in South Sudan. This program evaluation will hopefully inform Ministries of Health and their partners for the development of a training pillar of National Surgical, Obstetric, and Anesthesia Plans in the sub-Saharan African region.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".