Providing surgical care in Somalia: A model of task shifting
Bibliographic record
Abstract
BACKGROUND: Somalia is one of the most political unstable countries in the world. Ongoing insecurity has forced an inconsistent medical response by the international community, with little data collection. This paper describes the "remote" model of surgical care by Medecins Sans Frontieres, in Guri-El, Somalia. The challenges of providing the necessary prerequisites for safe surgery are discussed as well as the successes and limitations of task shifting in this resource-limited context. METHODS: In January 2006, MSF opened a project in Guri-El located between Mogadishu and Galcayo. The objectives were to reduce mortality due to complications of pregnancy and childbirth and from violent and non-violent trauma. At the start of the program, expatriate surgeons and anesthesiologists established safe surgical practices and performed surgical procedures. After January 2008, expatriates were evacuated due to insecurity and surgical care has been provided by local Somalian doctors and nurses with periodic supervisory visits from expatriate staff. RESULTS: Between October 2006 and December 2009, 2086 operations were performed on 1602 patients. The majority (1049, 65%) were male and the median age was 22 (interquartile range, 17-30). 1460 (70%) of interventions were emergent. Trauma accounted for 76% (1585) of all surgical pathology; gunshot wounds accounted for 89% (584) of violent injuries. Operative mortality (0.5% of all surgical interventions) was not higher when Somalian staff provided care compared to when expatriate surgeons and anesthesiologists. CONCLUSIONS: The delivery of surgical care in any conflict-settings is difficult, but in situations where international support is limited, the challenges are more extreme. In this model, task shifting, or the provision of services by less trained cadres, was utilized and peri-operative mortality remained low demonstrating that safe surgical practices can be accomplished even without the presence of fully trained surgeon and anesthesiologists. If security improves in Somalia, on-site training by expatriate surgeons and anesthesiologists will be re-established. Until then, the best way MSF has found to support surgical care in Somalia is continue to support in a "remote" manner.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.017 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".