CCORT/CCS quality indicators for acute myocardial infarction care.
Bibliographic record
Abstract
BACKGROUND: Although quality indicators for the care of acute myocardial infarction (AMI) patients have been described for other countries, there are none specifically designed for the Canadian health care system. The authors' goal was to develop a set of Canadian quality indicators for AMI care. METHODS: A literature review identified existing quality indicators for AMI care. A list of potential indicators was assessed by a nine-member panel of clinicians from a variety of disciplines using a modified-Delphi panel process. After an initial round of rating the potential indicators, a series of indicators was identified for a second round of discussion at a national meeting. Further refinement of indicators occurred following a teleconference and review by external reviewers. RESULTS: To identify an AMI cohort, case definition criteria were developed, using a hospital discharge diagnosis for AMI of International Classification of Diseases-Ninth revision (ICD-9) code 410.x. Thirty-seven indicators for AMI care were established. Pharmacological process of care indicators included administration of acetylsalicylic acid, beta-blockers, angiotensin-converting enzyme inhibitors, thrombolytics and statins. Mortality and readmissions for AMI, unstable angina and congestive heart failure were recommended as outcome indicators. Nonpharmacological indicators included median length of stay in the emergency department, and median waiting times for cardiac catheterization, percutaneous coronary intervention and/or coronary artery bypass graft surgery. INTERPRETATION: A set of Canadian quality indicators for the care of AMI patients has been established. It is anticipated that these indicators will be useful to clinicians and researchers who want to measure and improve the quality of AMI patient care in Canada.
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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 | 0.012 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.014 | 0.021 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".