A practice facilitation-guided intervention in primary care settings to reduce cardiovascular disease risk: a cost analysis
Bibliographic record
Abstract
BACKGROUND: A stepped-wedge, cluster randomized controlled trial assessed the effectiveness of practice facilitation (PF) for adoption of guidelines for prevention and treatment of cardiovascular disease risk factors. This study estimated the associated cost of PF for guideline adoption in small, private primary care practices. METHODS: The cost analysis included categories for start-up costs, intervention costs, and practice staff costs for the implemented PF-guided intervention. We estimated the total 1-year costs to operate the program and calculated the mean and range of the cost-per-practice by quarter of the intervention. We estimated the lower and upper bounds for all salary expenses, rounding to the nearest $100. RESULTS: Total 1-year intervention costs for all 261 practices ranged from $7,900,000 to $10,200,000, with program and practice salaries comprising $6,600,000-$8,400,000 of the total. Start-up costs were a small proportion (3%) of the total 1-year costs. Excluding start-up costs, quarter 1 cost-per-practice was the most expensive at $20,400-$26,700, and quarter 4 was the least expensive at about $10,000. Practice staff time (compared with program staff time) was the majority of the staffing costs at 75-84%. CONCLUSIONS: The PF strategy costs approximately $10,000 per practice per quarter for program and practice costs, once implemented and running at highest efficiency. Whether this program is "worth it" to the decision-maker depends on the relative costs and effectiveness of their other options for improving cardiovascular risk reduction. TRIAL REGISTRATION: This study is retrospectively registered on January 5, 2016, at www.clinicaltrials.gov as NCT02646488 .
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.010 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".