Bibliographic record
Abstract
OBJECTIVE To determine if there is improvement in medication management when pharmacists and family physicians collaborate to prescribe medication renewals requested by fax. DESIGN Prospective, non-randomized controlled trial. SETTING W est Winds Primary Health Centre, an interdisciplinary health centre that includes an academic family medicine practice, located in Saskatoon, Sask. PARTICIPANTS All patients whose pharmacies faxed the health centre requesting prescription renewals between October 2007 and February 2008 were selected to participate in the study. INTERVENTIONS Medication renewal requests were forwarded to the pharmacist (who works in the clinic part-time) on days when he was working (intervention group). The pharmacist assessed drug-therapy issues that might preclude safe and effective prescribing of the medication. The pharmacist and physician then made a collaborative decision to authorize the requested medication or to request additional interventions first (eg, perform laboratory tests). When the pharmacist was not working, the physicians managed the renewal requests independently (control group). MAIN OUTCOME MEASURES Medication renewals authorized with no recommendations, medication-related problems identified, new monitoring tests ordered, and new appointments scheduled with health providers. RESULTS A total of 181 renewal requests were included (94 in the control group and 87 in the intervention group). The control group had significantly more requests authorized with no recommendations (75.5% vs 52.9%, P = .001). Those in the intervention group had significantly more medication-related problems identified (26 vs 10, P = .031); medication changes made (24 vs 10, P = .044); and new appointments scheduled with their family physicians (31 vs 21, P = .049). CONCLUSION There is an improvement in medication management when a pharmacist collaborates with family physicians to prescribe medication renewals. The collaborative model created significantly more activity with each renewal request (ie, identification of medication-related problems, medication changes, and new appointments), which reflects an improvement in the process of care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".