Changes in cardiovascular care provision after the Affordable Care Act.
Bibliographic record
Abstract
OBJECTIVES: Physicians are gatekeepers to preventive care recommended by the US Preventive Services Task Force (USPSTF). We aimed to determine whether the Affordable Care Act (ACA) was associated with changes in physicians' provision of preventive cardiovascular services, focusing primarily on patients with employer-sponsored health plans. STUDY DESIGN: Quasi-experimental, difference-in-differences (DID) approach. METHODS: We analyzed National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey data from 2006 to 2013. Using a quasi-experimental DID approach with multivariate logistic models, we compared trends in preventive cardiovascular services delivered during physician visits among target and control populations prior to the ACA's provisions. RESULTS: The ACA was associated with an increase in use of diabetes screening (3.9% in 2006-2010 [third quarter] to 7.6% in 2010 [fourth quarter]-2013; DID, +3.5 per 100 visits; 95% CI, 1.1-5.9), tobacco use screening in adults (64.4% in 2006-2010 to 74.5% in 2010-2013; DID, +11.6 per 100 visits; 95% CI, 4.8-18.3), aspirin therapy in men (11.1% in 2006-2010 to 13.5% in 2010-2013; DID, +2.9 per 100 visits; 95% CI, 1.1-4.6), and hypertension screening (73.2% in 2006-2010 to 76.4% in 2010-2013; DID, +9.9 per 100 visits; 95% CI, 2.8-16.9). CONCLUSIONS: Provision of cardiovascular preventive care increased for some USPSTF-recommended services following enactment of the ACA, with evidence of a sex disparity in aspirin use. Other complementary policy approaches may further enhance uptake of evidence-based clinical preventive services.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".