Factors Associated with Medico-Legal Events Resulting from Attempted Suicide by Patients in Care: Facteurs associés aux événements médico-légaux résultant de tentatives de suicide de patients en soins.
Bibliographic record
Abstract
ObjectivesThis study provides an overview of the key medico-legal issues associated with attempted or completed suicide in Canada. Specifically, we identify factors that were criticized and found to contribute to medico-legal risk in these cases.MethodsA national repository was retrospectively searched for cases involving patients who attempted or completed suicide while under the care of a physician. The study included cases closed at the Canadian Medical Protective Association between 2013 and 2023. The study involved in- and outpatients who attempted or completed suicide. The frequencies and proportions of patient safety events and medico-legal risks for physicians were calculated by exploring factors that contributed to each incident.ResultsA total of 378 cases were identified, involving 460 physicians. The majority of patients in these cases experienced a healthcare-related harm (224/378, 59%). Psychiatrists were involved in 61% (231/378) of cases. The most common reasons for patient/family complaints were deficient assessments, diagnostic errors, and communication breakdowns with the patient or their family. The most common contributing factors identified by peer experts were deficient assessments of a suicidal patient and inadequate documentation.ConclusionsThis study addressed the gap in the published literature of healthcare-related contributing risk factors associated with a patient safety incident from Canadian medico-legal cases. The most common omissions identified by peer experts were comprehensive assessment and clear documentation. Physicians treating suicidal patients may reduce their medico-legal risk by completing and documenting thorough and timely suicide risk assessments.Plain Language Summary TitleInvestigation of factors leading to physicians' legal risks when their patients attempted suicide.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".