Randomized Trial of the Effect of Pharmacist Prescribing on Improving Blood Pressure in the Community
Bibliographic record
Abstract
BACKGROUND: Hypertension control rates remain suboptimal. Pharmacists' scope of practice is evolving, and their position in the community may be ideal for improving hypertension care. We aimed to study the impact of pharmacist prescribing on blood pressure (BP) control in community-dwelling patients. METHODS AND RESULTS: We designed a patient-level, randomized, controlled trial, enrolling adults with above-target BP (as defined by Canadian guidelines) through community pharmacies, hospitals, or primary care teams in 23 communities in Alberta. Intervention group patients received an assessment of BP and cardiovascular risk, education on hypertension, prescribing of antihypertensive medications, laboratory monitoring, and monthly follow-up visits for 6 months (all by their pharmacist). Control group patients received a wallet card for BP recording, written hypertension information, and usual care from their pharmacist and physician. Primary outcome was the change in systolic BP at 6 months. A total of 248 patients (mean age, 64 years; 49% male) were enrolled. Baseline mean±SD systolic/diastolic BP was 150±14/84±11 mm Hg. The intervention group had a mean±SE reduction in systolic BP at 6 months of 18.3±1.2 compared with 11.8±1.9 mm Hg in the control group, an adjusted difference of 6.6±1.9 mm Hg (P=0.0006). The adjusted odds of patients achieving BP targets was 2.32 (95% confidence interval, 1.17-4.15 in favor of the intervention). CONCLUSIONS: Pharmacist prescribing for patients with hypertension resulted in a clinically important and statistically significant reduction in BP. Policy makers should consider an expanded role for pharmacists, including prescribing, to address the burden of hypertension. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00878566.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".