Medico-Legal Cases Involving Cardiologists and Cardiac Test Underuse or Overuse
Bibliographic record
Abstract
BACKGROUND: Evidence-based campaigns are available to support appropriate diagnostic testing in cardiology, but medico-legal concerns can impede implementation. METHODS: We conducted a retrospective descriptive analysis of medico-legal cases (civil legal, regulatory authority, hospital matters) involving cardiologists in Canada. For eligibility, cases must have closed at the Canadian Medical Protective Association between January 1, 2009 and December 31, 2018. We defined test underuse and overuse using criticisms in the medico-legal record from peer experts, regulatory authorities, or hospitals. We used a contributing factors framework and descriptive statistics for analysis. RESULTS: From 2009 to 2018, the Canadian Medical Protective Association closed 60,598 cases with 368 (0.6%) involving a cardiologist. Within those cases, there was no criticism of cardiac diagnostic test overuse and 15 cases (4.1%) with criticism of underuse (tests not ordered, not expedited, delayed). In 12 of 15 cases of underuse (80.0%), the patient experienced severe harm or death. Of 8 civil legal cases, 6 were decided in favour of the plaintiff (75.0%) and 2 were dismissed by consent before proceeding to trial (25.0%). Decisions on regulatory authority matters did not favour the cardiologist (7 of 7 cases). In all cases of underuse, there was need for focused testing to investigate new or worsening symptoms. The most common contributing factors included clinical decision-making, situational awareness, and communication with teams and patients. CONCLUSIONS: Medico-legal cases involving cardiologists and the overuse or underuse of cardiac diagnostic tests were extremely rare in Canada, despite the potential for harm. The criticisms of cardiac diagnostic test underuse related to issues with diagnosing symptomatic patients.
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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 | 0.019 | 0.166 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".