Bibliographic record
Abstract
OBJECTIVES: Acute myocardial infarction (AMI) 'report cards' are being developed using administrative databases in many jurisdictions, but little is known about their acceptance by and their usefulness to the medical community. The purpose of this study was to determine the impact of the publication of Cardiovascular Health and Services in Ontario: An ICES Atlas (Naylor CD, Slaughter P. (eds), 1999, Toronto: ICES), the first report featuring hospital-specific AMI performance measures to be published in Canada. DESIGN: We conducted a mail survey of physicians at Ontario hospitals to determine their views on the usefulness of various atlas performance measures for assessing and improving quality of care, the types of quality initiatives launched at their hospital in response to the atlas, and their views on the concept and limitations of reporting hospital-specific AMI mortality data. RESULTS: Respondents to the survey indicated that information on process of care measures such as post-infarction beta-blocker and angiotensin-converting enzyme (ACE) inhibitor use, and cardiac procedure waiting times were the most useful, and outcomes data (e.g. 30-day and 1-year risk-adjusted AMI mortality rates) the least useful of the multiple performance measures published in the atlas (P = 0.0385). Fifty-four percent of respondents reported launching one or more quality of care initiatives at their hospital in response to the atlas. The majority of respondents (65%) indicated that they support the public release of hospital-specific AMI mortality data, although many had concerns about potential miscoding in administrative databases and the adequacy of risk-adjustment methods. CONCLUSION: The publication of the first AMI report card in Canada stimulated quality of care initiatives at many Ontario hospitals. Inclusion of performance measures other than mortality in health care report cards may lead to greater acceptance and use by the medical community.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".