Abstract P156: Long-Term Blood Pressure Outcomes and Costs Associated With a Barber-Pharmacist Hypertension Intervention: 10-Year Simulation of the Los Angeles Barber Trial
Bibliographic record
Abstract
Background: Barber-pharmacist blood pressure (BP) management reduced systolic BP >20 mm Hg compared to education alone over one year in Non-Hispanic (NH) black men with uncontrolled hypertension (HTN) in the Los Angeles BARBER (LA-BARBER) Trial. Long-term BP outcomes and costs of this intervention are unknown. Objective: Simulate 10-year BP outcomes and intervention and medication costs of a one-year barber-pharmacist HTN intervention followed by usual care compared to usual care alone. Methods: We simulated 1000 LA BARBER-eligible NH black men sampled from the National Health and Nutrition Examination Survey. We used a discrete event simulation version of the validated BP Control Model to predict BP outcomes over 10 years. Model inputs were derived from published literature, national sources, LA-BARBER individual participant data, and interviews with LA-BARBER intervention pharmacists. Medication and intervention (clinical care, travel, and administrative time) costs were calculated from a 2018 US payer perspective and discounted 3% annually. Primary outcomes were percent with BP <130/80 mm Hg, medication and intervention costs, and the cost per patient with BP controlled. We used 100 probabilistic model iterations to examine parameter uncertainty. Results: Our calibrated model accurately reproduced baseline characteristics and predicted 1-year BP outcomes of the LA-BARBER study (mean age 54 years, baseline BP 153/91 mm Hg, 69% predicted 1-year BP control with the barber-pharmacist HTN intervention). Over 10 years, 64% of patients (95% uncertainty interval [UI] 61%-67%) were predicted to achieve BP control with the barber-pharmacist HTN intervention compared to 38% (95% UI 26%-48%) with usual care. Projected intervention and medication costs were $8084 (95% UI $7664-$8598) with the barber-pharmacist intervention compared to $4183 ($3514-$4768) with usual care costing $15,000 per controlled patient gained. Conclusions: Medication and intervention costs for a barber-pharmacist HTN intervention were about double usual care, but it achieved substantially higher BP control rates. Ongoing research will examine if this strategy meets traditional cost-effectiveness thresholds (e.g.,<$100,000 per quality-adjusted life year).
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".