Lessons learned from Canadian family physicians deprescribing medications in older adults – a five-year retrospective review of medico-legal cases
Bibliographic record
Abstract
BACKGROUND: Medication-related safety incidents are more common in older adults than in younger populations. Medication review and optimization, including deprescribing, are essential components of strategies to reduce medication-related harm. Deprescribing aims to minimize therapeutic burden by reducing medications that no longer provide net clinical benefit or by substituting safer alternatives. Herein we sought to use a national pan-Canadian repository of medico-legal cases to identify opportunities for improving deprescribing practices in primary care for older adults. METHODS: We conducted a five-year retrospective review (2018–2022) of closed Canadian medico-legal cases relating to deprescribing involving family medicine physicians and patients age 65 or older. We analysed cases related to deprescribing and created composite case examples to illustrate both areas for improvement and examples of appropriate care despite the receipt of a complaint or civil legal action (collectively, medico-legal cases). RESULTS: We identified 31 medico-legal cases, of which 29 had undergone expert review. Experts identified areas of improvement related to deprescribing including conducting assessments to determine appropriateness of deprescribing, using a multidisciplinary approach to create a safe tapering plan that includes monitoring and follow-up, establishing clear communication with patients and their authorized substitute decision-makers, and documenting clearly and appropriately. Although experts often explicitly identified these elements as present, they were critical of the deprescribing-related care in half of cases. CONCLUSIONS: Medico-legal cases highlight several key areas for improving deprescribing in primary care, particularly around comprehensive patient assessment to inform deprescribing decision-making and clear communication of treatment plans with relevant decision-makers. The cases also demonstrate that the process of deprescribing and the patient-physician relationship is complex and that complaints can occur even when physicians are safely deprescribing.
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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 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.020 | 0.022 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".