Up-to-Date on Preventive Care Services Under Affordable Care Act
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The utilization of preventive care services has been less than optimal. As part of an effort to address this, the Affordable Care Act (ACA) mandated that private health insurance plans cover evidence-based preventive services. OBJECTIVES: To evaluate whether the provisions of ACA have increased being up-to-date on recommended preventive care services among privately insured individuals aged 18-64. RESEARCH DESIGN: Multivariate linear regression models were used to examine trends in prevalence of being up-to-date on selected preventive services, diagnosis of health conditions, and health expenditures between pre-ACA (2007-2010) and post-ACA (2011-2014). Adjusted difference-in-difference analyses were used to estimate changes in those outcomes in the privately insured that differed from changes in the uninsured (control group). RESULTS: After the passage of ACA, up-to-date rates of routine checkup (2.7%; 95% confidence interval, 0.8%-4.7%; P=0.007) and flu vaccination (5.9%; 95% confidence interval, 4.2%-7.6%; P<0.001) increased among those with private insurance, as compared with the control group. Changes in blood pressure check, cholesterol check and cancer screening (pap smear test, mammography, and colorectal cancer screening) were not associated with the ACA. Prevalence in diagnosis of health conditions remained constant. Slower uptrends in adjusted total health care expenditures and downtrends in adjusted out-of-pocket costs were observed during the study period. CONCLUSIONS: The provisions of the ACA have resulted in trivial increases in being up-to-date on selected preventive care services. Additional efforts may be required to take full advantage of the elimination of cost-sharing under the ACA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it