Clinical and Nonclinical Correlates of Adherence to Prescribing Guidelines for Hypertension in a Large Managed Care Organization
Bibliographic record
Abstract
To examine correlates of guideline adherence in a population with access to health care and prescription drug benefits, the authors conducted a cross-sectional analysis among 5789 patients undergoing hypertension treatment with a single medication in a large New England managed care organization. Logistic regression was used to determine correlates of adherence, defined as use of diuretics or beta blocker as antihypertensive monotherapy during the 1-year study period. Women were more likely than men to receive guideline-adherent therapy (odds ratio [OR], 1.63; 95% confidence interval [CI], 1.45-1.85). Compared with patients covered by health maintenance organization plans, Medicare coverage was positively associated with guideline adherence (OR, 1.38; 95% CI, 1.13-1.69), but fee-for-service coverage was negatively associated (OR, 0.66; 95% CI, 0.48-0.91). Patient age was not a significant correlate of adherence to guidelines (OR, 1.01; 95% CI, 0.94-1.09). Understanding these observations may lead to strategies to improve guideline adherence and reduce health care disparities.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".