Medication therapy problems detected at community pharmacy INR checks
Bibliographic record
Abstract
Background: Despite the shift towards direct-acting anticoagulants, warfarin remains widely used in Canada and is traditionally managed by family physicians through laboratory-based international normalized ratio (INR) testing. The Community Pharmacy Anticoagulation Management Service (CPAMS) in Nova Scotia represents an innovative approach, enabling community pharmacists to conduct point-of-care (POC) INR testing and manage warfarin therapy. A potential benefit of this approach is the opportunity to identify non-warfarin medication therapy problems (nwMTPs) during routine visits. Method: We conducted a prospective, multicentre, observational study across 40 community pharmacies in Nova Scotia, part of CPAMS's second phase. Pharmacists documented nwMTPs identified in patients with atrial fibrillation during routine POC INR visits using the Qualtrics Insight Platform, categorizing them by indication, effectiveness, safety, or adherence, alongside corresponding interventions. Results: Over 6 months, 43 nwMTPs were submitted from 13 unique pharmacies. There were 3404 POC INR tests in patients with atrial fibrillation, yielding an estimated nwMTP detection rate of 1.26 (95% CI, 0.69 to 2.32) per 100 INR tests. The most common nwMTP category was "Indication," primarily requiring additional therapy. Pharmacists frequently intervened by recommending medication adjustments or providing patient education. Discussion: The findings highlight a modest, yet potentially significant role of pharmacists in detecting and managing diverse MTPs during focused warfarin management assessments. The predominance of indication-related problems underscores unmet therapeutic needs in patients on warfarin. Conclusion: This study illustrates the potential of pharmacist-led POC INR testing in community settings to identify and address nwMTPs, contributing to comprehensive patient 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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".