Adherence to process of care quality indicators after percutaneous coronary intervention in Ontario, Canada: a retrospective observational cohort study
Bibliographic record
Abstract
BACKGROUND: Public reporting of percutaneous coronary intervention (PCI) outcomes has been established in many jurisdictions to ensure optimal delivery of care. The majority of PCI report cards examine in-hospital mortality, but relatively little is known regarding the adherence to processes of care. METHODS: A modified Delphi panel comprising cardiovascular experts was assembled to develop a set of PCI quality indicators. Indicators such as prescription of aspirin, dual antiplatelet therapy, statins and smoking cessation counselling were identified to represent high-quality PCI care. Chart abstraction was performed at 13 PCI hospitals in Ontario, Canada from 2009 to 2010 with at least 200 PCI patients randomly selected from each hospital. RESULTS: Our study sample included 3041 patients, of whom 18% had stable coronary artery disease (CAD) and 82% had an acute coronary syndrome (ACS). Their mean age was 63±12.4 years and 29% of patients were female. Prior to PCI, 89% were prescribed aspirin, and after PCI 98.7% were prescribed aspirin, 95.1% were prescribed dual antiplatelet therapy for 12 months after drug-eluting stents, and 94.9% were prescribed statins. The lowest performing quality indicator was smoking cessation counselling, observed in only 42% of current and past smokers (18% in patients with stable CAD and 47% in ACS). CONCLUSIONS: Our study demonstrates high levels of adherence to most quality indicators for patients undergoing PCI procedures in Ontario. In conclusion, smoking cessation counselling was not consistently performed across hospitals and represents an opportunity for future quality improvement efforts.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".