Cost-Effectiveness Analysis of Total Hip Arthroplasty Performed by a Canadian Short-Stay Surgical Team in Ecuador
Bibliographic record
Abstract
BACKGROUND: Few charitable overseas surgical missions produce cost-effectiveness analyses of their work. METHODS: We compared the pre- and postoperative health status for 157 total hip arthroplasty (THA) patients operated on from 2007 to 2011 attended by an annual Canadian orthopedic mission to Ecuador to determine the quality-adjusted life years (QALYs) gained. The costs of each mission are known. The cost per surgery was divided by the average lifetime QALYs gained to estimate an incremental cost-effectiveness ratio (ICER) in Canadian dollars per QALY. RESULTS: The average lifetime QALYs (95% CI) gained were 1.46 (1.4-1.5), 2.5 (2.4-2.6), and 2.9 (2.7-3.1) for unilateral, bilateral, and staged (two THAs in different years) operations, respectively. The ICERs were $4,442 for unilateral, $2,939 for bilateral, and $4392 for staged procedures. Seventy percent of the mission budget was spent on the transport and accommodation of volunteers. CONCLUSION: THA by a Canadian short-stay surgical team was highly cost-effective, according to criteria from the National Institute for Health and Care Excellence and the World Health Organization. We encourage other international missions to provide similar cost-effectiveness data to enable better comparison between mission types and between mission and nonmission care.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".