Medication reconciliation practices in ambulatory cancer care across Canada.
Bibliographic record
Abstract
248 Background: Substantial work has been done to implement medication reconciliation (MedRec) in the inpatient setting to reduce medical errors and drug discrepancies. However, this work has not extended to the ambulatory cancer setting, where care spans multiple providers and responsibility remains unclear. We undertook an environmental scan to understand current MedRec practices in ambulatory cancer care across Canada. Methods: Semi-structured telephone interviews were conducted with stakeholders from institutions across Canada during a 2-month period in 2019. Questionnaires were pre-circulated to participants to guide discussions. Questions probed participants on processes, policies, roles and responsibilities, definitions of target populations, information sources, and barriers and facilitators. Results: 21 of the 23 stakeholders contacted were interviewed, representing 9 of 10 Provinces. Most institutions had a process in place for collecting best possible medication history (BPMH; 81%); however, considerable variation in practice was noted and full MedRec was uncommon. Of those institutions with a process, BPMH was most often undertaken by a pharmacist or pharmacy tech (53%) using a comprehensive Provincial drug information system (65%) as a starting point, and targeted patients initiating systemic therapy (59%). Few institutions (22%) routinely collected performance measures evaluating the process or outcomes. Lack of resources (physical, human and financial), high patient volumes, and access to medication records from external institutions and community pharmacies were identified as significant barriers to routinely collecting BPMH. Understanding the value added, clinician buy-in, and patient education regarding the importance of bringing medication to the clinic were identified as facilitators. Leveraging patients to more actively participate in collection and maintenance of their own medication records was identified as an area for future work. Conclusions: While most centres were doing BPMH in some patients, MedRec was uncommon in the ambulatory cancer setting. Results indicate a lack of consensus regarding best practices for medication management in ambulatory cancer care.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".