The Impact of a Multidisciplinary Information Technology–Supported Program on Blood Pressure Control in Primary Care
Bibliographic record
Abstract
BACKGROUND: Hypertension is a leading mortality risk factor yet inadequately controlled in most affected subjects. Effective programs to address this problem are lacking. We hypothesized that an information technology-supported management program could help improve blood pressure (BP) control. METHODS AND RESULTS: This randomized controlled trial included 223 primary care hypertensive subjects with mean 24-hour BP >130/80 and daytime BP >135/85 mm Hg measured with ambulatory monitoring (ABPM). Intervention subjects received a BP monitor and access to an information technology-supported adherence and BP monitoring system providing nurses, pharmacists, and physicians with monthly reports. Control subjects received usual care. The mean (+/-SD) follow-up was 348 (+/-78) and 349 (+/-84) days in the intervention and control group, respectively. The primary end point of the change in the mean 24-hour ambulatory BP was consistently greater in intervention subjects for both systolic (-11.9 versus -7.1 mm Hg; P<0.001) and diastolic BP (-6.6 versus -4.5 mm Hg; P=0.007). The proportion of subjects that achieved Canadian Guideline target BP (46.0% versus 28.6%) was also greater in the intervention group (P=0.006). We observed similar BP declines for ABPM and self-recorded home BP suggesting the latter could be an alternative for confirming BP control. The intervention was associated with more physician-driven antihypertensive dose adjustments or changes in agents (P=0.03), more antihypertensive classes at study end (P=0.007), and a trend toward improved adherence measured by prescription refills (P=0.07). CONCLUSIONS: This multidisciplinary information technology-supported program that provided feedback to patients and healthcare providers significantly improved blood pressure levels in a primary care setting.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".