Initial Pharmacist Experience with the Ontario-Based MedsCheck Program
Bibliographic record
Abstract
Background: On April 1, 2007, community pharmacists in Ontario began providing a new medication review service called MedsCheck. MedsCheck is intended to help patients better understand their medication therapy, ensure that medications are being taken as prescribed and establish a medication history. This study explored the initial experiences with MedsCheck and identified barriers to and facilitators of the implementation of the service. Methods: This was a sequential, explanatory, mixed-methods study. Community pharmacists practising in Hamilton, Ontario, completed a semi-structured mailed survey. A subsample of participants also participated in a semi-structured telephone interview. Results: A total of 88 pharmacists returned the survey and 13 participated in an interview. Respondents reported that it took an average of 30 minutes (standard deviation 11.2; range 10–60 minutes) to complete a MedsCheck. Barriers to providing the service included lack of time, physical space and patient awareness of and interest in the service. Facilitators included pharmacist overlap coverage, scheduling reviews during slower times, personally inviting patients to participate, reducing paperwork and using electronic or paper-based tools. Discussion: The MedsCheck program was well received. However, numerous barriers to its implementation were identified, most notably lack of time and a workflow that is not conducive to an appointment-based, 30-minute service. Further research suggests this time estimate may be low. Changes within the pharmacy could improve the implementation of this service. Conclusion: This study provided information on how to facilitate the implementation of MedsCheck. The results of this study can help pharmacists to improve the delivery of MedsCheck or similar services in community pharmacies.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".