Lessons Learned From a Retrospective Analysis of Medicolegal Risks for Physicians Treated Adolescents and Young Adults With Medical Complexity
Bibliographic record
Abstract
PURPOSE: Adolescent and young adult patients occupy a clinically transitional space between pediatric and adult care. Youth with chronic conditions and special healthcare needs may have trouble accessing and receiving appropriate care in this transition, which may lead to patient safety issues and medicolegal risks for physicians. The objectives of this article were to explore patient safety issues and identify medicolegal risks for physicians. METHODS: A national repository was retrospectively searched for medicolegal cases (MLCs) involving complaints from youth. The study included MLCs closed at the Canadian Medical Protective Association between 2013 and 2022 involving youth. The study participants were adolescents and young adults aged ≥ 15 and ≤ 21 years with medical complexity. The frequencies and proportions of patient safety events and medicolegal risks for physicians were calculated by exploring factors that contributed to each incident using established frameworks. RESULTS: A total of 182 eligible MLCs were identified. Of 206 involved physicians, 55 were psychiatrists. The most common reasons for patient complaints were deficient assessment, diagnostic error, and communication breakdown with the patient and/or family. More than half of the cases were related to a harmful incident. Peer experts reviewed the cases and identified factors such as a deficient assessment, a failure to perform a test or intervention, failure to refer the patient, and insufficient provider knowledge/skill as contributing to the patient safety event. DISCUSSION: The impact of our findings is to identify gaps in care delivery to youth that can inform practitioners of ways to mitigate the gaps and improve patient care and health outcomes.
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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 | 0.017 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".