Exploring discrepancies between pharmacists’ perceived and actual roles towards optimising care in patients prescribed direct oral anticoagulants: a survey
Bibliographic record
Abstract
Abstract Background Pharmacists are among the most accessible healthcare professionals, and scopes of practice are evolving. There is a paucity of literature evaluating community pharmacists’ degree of comfort with managing high‐risk medications, including anticoagulants. Aim To describe discrepancies between perceived and actual roles in care optimisation of patients prescribed direct oral anticoagulants (DOACs), as well as the level of collaboration between pharmacists and other healthcare providers, and barriers to action among pharmacists. Methods Community‐based pharmacists in Alberta, Canada, were surveyed to evaluate perceived and actual roles, collaboration and barriers. Discrepancies between perceived and actual roles were compared for individual items, and total scores were calculated. Results In all, 177 (5%) pharmacists responded to the survey. Perceived role scores were high, and actual role scores were generally lower (median scores 42/52 vs 61/65). Actual role items with the lowest scores were: knowledge of the patient's medical conditions and indication for DOAC; provision of information about the condition being treated with a DOAC; review pertinent laboratory tests at initial prescription fill and refill; and follow‐up on adherence and side‐effects. Discrepancy rates between perceived and actual roles were low. There was moderate correlation between perceived and actual role scores (Spearman's ρ = 0.512, p < 0.001). Responders reported a high degree of collaboration with physicians. Several system‐ and organisation‐level barriers were identified, although overall barrier burden was low. Conclusion Community‐based pharmacists perceived a significant role for pharmacists in optimising DOACs for patients, and higher perceived role scores were associated with greater action in actual roles. Removing system‐level barriers, and improving communication with prescribers about indications for DOACs, should be prioritised to enhance the role of the pharmacist.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".