Perspectives and experiences with telepharmacy among pharmacists in Canada: A cross-sectional survey
Bibliographic record
Abstract
Objective: This study aims to understand Canadian pharmacists' use, experiences, and perspectives of telepharmacy. Methods: We conducted a cross-sectional online survey. Individuals were eligible to participate if they were currently a registered, licensed pharmacist practicing in Canada. We collected perspectives of both telepharmacy users and non-users by creating a survey logic that asked specific and shared questions between the two groups. Data was analyzed using descriptive statistics including means and standard deviations (SD) for continuous variables and proportions for categorical variables. Results: Between October and December 2020, 136 pharmacists completed the survey, including 61 (52.6%) telepharmacy users and 55 (47.4%) non-users. Among those who use telepharmacy, the majority of participants (39, 72.2%) expressed that telepharmacy augmented their clinical practice and feel comfortable managing minor ailments using telepharmacy (41, 80.4%). Among non-users, 45 (84.9%) indicated that telepharmacy will augment their clinical practice and 48 (90.6%) would feel comfortable managing minor ailments using telepharmacy. Important considerations for successful implementation of telepharmacy for those who use telepharmacy included easier system implementation (29, 19.3%), better privacy & data protection (28, 18.7%) and simple to learn technology (23, 15.3%). Conclusion: Despite the growing recognition of benefits of telepharmacy, our findings suggest that utilization among pharmacists in Canada is still quite low. Nonetheless, our study identified areas of consideration for better integration of telepharmacy in pharmacy practice including optimizing workflow, addressing barriers, and providing training to pharmacy students.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".