Effect of hospital ownership status and payment structure on the adoption and use of drug-eluting stents for percutaneous coronary interventions
Bibliographic record
Abstract
BACKGROUND: The impact of the use of drug-eluting stents in percutaneous coronary intervention (PCI) on cardiac care is still uncertain. We examined the influence of systemic factors, such as hospital ownership status, organizational characteristics and payment structure, on the use of drug-eluting stents in PCI and the effect on cardiac surgery volume. METHODS: We conducted a cross-sectional analysis of drug-eluting stent use in 12 993 patients undergoing PCI with stenting (drug-eluting or bare-metal) and time-series regression analyses of the monthly number of cardiac surgery and PCI procedures performed using data collected from 1998 to 2004 at 13 public and private hospitals in the Emilia-Romagna region of Italy. RESULTS: Public hospitals used drug-eluting stents more selectively than private hospitals, targeting the new device to patients at high risk of adverse events. The time-series regression analyses showed that the number of PCI procedures performed per year increased during this period, both in public (slope coefficient 36.4, 95% confidence interval [CI] 30.2 to 43.1) and private centres (slope coefficient 6.4, 95% CI 3.1 to 9.2 ). Concurrently, there was a reduction in the number of isolated coronary artery bypass graft (CABG) surgeries, although the degree of change was higher in public than in private hospitals (coefficient -16.1 v. -6.2 respectively ). The number of CABG procedures associated with valve surgery decreased in public hospitals (coefficient -5.0, 95% CI -6.1 to -3.8) but increased in private hospitals (coefficient 4.1, 95% CI 2.0 to 6.1). INTERPRETATION: Public and private hospitals behaved differently in adopting drug-eluting stents and in using PCI with drug-eluting stents as a substitute for surgical revascularization.
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".