Team-based care for improving hypertension management among outpatients (TBC-HTA): study protocol for a pragmatic randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Blood pressure (BP) is poorly controlled among a large proportion of hypertensive outpatients. Innovative models of care are therefore needed to improve BP control. The Team-Based Care for improving Hypertension management (TBC-HTA) study aims to evaluate the effect of a team-based care (TBC) interprofessional intervention, involving nurses, community pharmacists and physicians, on BP control of hypertensive outpatients compared to usual care in routine clinical practice. METHODS/DESIGN: The TBC-HTA study is a pragmatic randomized controlled study with a 6-month follow-up which tests a TBC interprofessionnal intervention conducted among uncontrolled treated hypertensive outpatients in two ambulatory clinics and among seven nearby community pharmacies in Lausanne and Geneva, Switzerland. A total of 110 patients are being recruited and randomized to TBC (TBC: N = 55) or usual care group (UC: N = 55). Patients allocated to the TBC group receive the TBC intervention conducted by an interprofessional team, involving an ambulatory clinic nurse, a community pharmacist and a physician. A nurse and a community pharmacist meet patients every 6 weeks to measure BP, to assess lifestyle, to estimate medication adherence, and to provide education to the patient about disease, treatment and lifestyle. After each visit, the nurse and pharmacist write a summary report with recommendations related to medication adherence, lifestyle, and changes in therapy. The physician then adjusts antihypertensive therapy accordingly. Patients in the UC group receive usual routine care without sessions with a nurse and a pharmacist. The primary outcome is the difference in daytime ambulatory BP between TBC and UC patients at 6-month of follow-up. Secondary outcomes include patients' and healthcare professionals' satisfaction with the TBC intervention and BP control at 12 months (6 months after the end of the intervention). DISCUSSION: This ongoing study aims to evaluate the effect of a newly developed team-based care intervention engaging different healthcare professionals on BP control in a primary care setting in Switzerland. The results will inform policymakers on implementable strategies for routine clinical practice. TRIAL REGISTRATION: ClinicalTrials.gov registration: NCT02511093 . Retrospectively registered on 28 July 2015.
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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 | 0.030 | 0.029 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.017 | 0.007 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.072 | 0.011 |
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".