Trends and Contributing Factors in Medicolegal Cases Involving Spine Surgery
Bibliographic record
Abstract
STUDY DESIGN: Retrospective descriptive study. OBJECTIVE: The aim of this study was to describe closed medicolegal cases involving physicians and spine surgery in Canada from a trend and patient safety perspective. SUMMARY OF BACKGROUND DATA: Spine surgery is a source of medicolegal complaints against surgeons partly owing to the potential severity of associated complications. In previous medicolegal studies, researchers applied a medicolegal lens to their analyses without applying a quality improvement or patient safety lens. METHODS: The study comprised a 15-year medicolegal trend analysis and a 5-year contributing factors analysis of cases (civil legal and regulatory authority matters) from the Canadian Medical Protective Association (CMPA), representing an estimated 95% of physicians in Canada. Included cases were closed by the CMPA between 2004 and 2018 (trends) or 2014 and 2018 (contributing factors). We fit a linear trend line to the annual rates of spine surgery cases per 1000 physician-years of CMPA membership for physicians in a neurosurgery or orthopedic surgery specialty. We then applied an ANOVA type III sum of squares test to determine the statistical significance of the annualized change rate over time. For the contributing factors analysis, we reported descriptive statistics for patient and physician characteristics, patient harm, and peer expert criticisms in each case. RESULTS: Our trend analysis included 340 cases. Case rates decreased significantly at an annualized change rate of -4.7% (P = 0.0017). Our contributing factors analysis included 81 civil legal and 19 regulatory authority cases. Most patients experienced health care-related harm (89/100, 89.0%). Peer experts identified intraoperative injuries (29/89, 32.6%), diagnostic errors (14/89, 15.7%), and wrong site surgeries (16/89, 18.0%) as the top patient safety indicators. The top factor contributing to medicolegal risk was physician clinical decision-making. CONCLUSION AND RELEVANCE: Although case rates decreased, patient harm was attributable to health care in the majority of recently closed cases. Therefore, crucial opportunities remain to enhance patient safety in spine surgery.Level of Evidence: 4.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.006 | 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".