Selecting indicators for the quality of cardiac care at the health system level in Organization for Economic Co-operation and Development countries
Bibliographic record
Abstract
BACKGROUND: Cardiovascular (CV) diseases are major causes of morbidity and death in adults in the world. Major differences have been reported in the management strategies and the outcome of CV diseases within and between countries. To better understand and address these differences, there is a need for quantitative information on patient management, outcome, and prognosis. OBJECTIVE: This article describes the development of a set of quality indicators for cardiac care and summarizes work undertaken by the Cardiac Care Panel of the OECD Health Care Quality Indicators Project. METHODS: A list of 61 potential indicators was identified through a literature search, review of national measurement systems, and nomination from countries participating in the project. The Cardiac Care Panel then used a modified Delphi process developed originally by RAND to select indicators. Panel members individually rated each indicator on a scale of 1-9 for scientific soundness and importance. All indicators receiving scores of 7 or more for both importance and soundness were included in the final set. RESULTS: Seventeen cardiac indicators were selected for the final set of indicators from the following areas: acute coronary syndromes, cardiac interventions, secondary prevention, and congestive heart failure. CONCLUSIONS: The final set of 17 indicators selected by the Cardiac Care Panel constitutes a comprehensive set of measures for the most relevant domains of CV care. Nevertheless, gaps remain in the area of primary prevention and in particular in areas with rapidly changing technology and improving treatment options.
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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 | 0.005 | 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) | 0.000 | 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".