Safety and Outcomes in Plastic Surgery Medical Tourism: A Review of 2324 Patients and 7141 Procedures
Bibliographic record
Abstract
Background: Medical tourism for cosmetic surgery is expanding due to demand for high-quality, safe, and affordable procedures. This study built on prior research by analyzing a larger cohort of plastic surgery patients in Colombia, a leading destination for international patients seeking superior quality, service, and value. We presented the largest review to date on safety and outcomes in plastic surgery medical tourism, comparing our results with benchmark publications from board-certified plastic surgeons in the United States. Methods: A retrospective observational study was conducted on 2324 international patients (7141 procedures) who underwent cosmetic surgery at a private practice in Cartagena, Colombia, from 2013 to 2024. Patient demographics, procedures, and surgical sites were recorded. Postoperative outcomes were analyzed using medical charts of 1363 patients (4244 procedures) treated from 2020 to 2024. Results: Patient demographics and procedure trends align with data from the International Society of Aesthetic Plastic Surgery. Eighty-nine percent of patients traveled from the United States or Canada, and the majority were well-educated professionals. The overall complication rate was 6.2% per patient (2.2% per procedure), which compares favorably with published benchmarks from board-certified plastic surgeons in the United States. Conclusions: Plastic surgery medical tourism, when performed in high-volume, well-regulated centers, can achieve outcomes equivalent to leading practices in the United States, reinforcing its viability as a safe and effective option for international patients. A center of excellence model and strict safety protocols contributed to these favorable outcomes.
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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 | 0.004 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".