Trends in medico-legal cases against Canadian ophthalmologists: a 10-year retrospective review (2013–2022)
Bibliographic record
Abstract
OBJECTIVE: To investigate trends in medico-legal complaints against Canadian ophthalmologists over a ten-year period (2013-2022). METHODS: Retrospective review of closed legal, hospital, and regulatory cases involving ophthalmologists was conducted using data from the Canadian Medical Protective Association (CMPA). Cases were systematically coded by nurse analysts using the Canadian Classification of Health Interventions, ICD-10-CA, and a specific schema for contributing factors. Data analyses utilized SAS software (9.4) and Prism GraphPad (9.4.1). RESULTS: A total of 970 closed cases with sufficient data for analysis were identified, including 584 college complaints, 340 legal complaints, and 46 hospital complaints. Complainants were predominantly female (55.4%) and mostly aged 30-64. Of the 1021 ophthalmologists named, 210 faced multiple complaints, with 82% of complaints against those with over ten years of practice. The most common clinical presentations generating complaints were disorders of the lens (37.1%), disorders of the choroid and retina (17.3%), and disorders of refraction (14.9%). The most common complications cited in complaints included visual disturbances (22.0%) and retinal complications (13.8%). Peer expert concerns were noted in 540 cases (55.7%), with common issues being inadequate documentation (31.5%), consent processes (25.9%), and communication (20.6%). Approximately 50.9% of cases had unfavorable outcomes for CMPA members, though the most frequent unfavourable college outcome was "dismissed with concern". CONCLUSION: This review highlights gaps in Canadian ophthalmic care, empowering ophthalmologists to address these concerns. Future work will focus on detailed assessments of cases with peer expert concerns and developing specific recommendations for clinical practice.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.059 | 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".