An Update on the Development and Feasibility Assessment of Canadian Quality Indicators for Atrial Fibrillation and Atrial Flutter
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: In 2010, the Canadian Cardiovascular Society Atrial Fibrillation/Atrial Flutter (AF/AFL) quality indicator (QI) working group was established to develop QIs and assess feasibility of measurement. After extensive review, 3 priority QIs were selected. However, none were measurable at a national level. METHODS: The working group reconvened in 2017 to review the relevance of previously proposed QIs, identify opportunities to develop new QIs, and propose an initial strategy for measuring and reporting. RESULTS: Two additional priority QIs were added to the previous 3: proportion of patients with nonvalvular (NV) AF/AFL sorted by stroke risk stratum and annual rate of hospitalization for a new heart failure diagnosis. An environmental scan was undertaken to determine the potential of existing databases to provide national and provincial estimates. On the basis of validated administrative codes, the Canadian Institute for Health Information discharge abstract database can be used for inpatients. In collaboration with the Canadian Primary Care Sentinel Surveillance Network, 2 of the 5 QIs can be assessed in outpatients (patients with NVAF/AFL sorted by stroke risk stratum and high risk for stroke NVAF/AFL receiving oral anticoagulation). Stroke prevention therapy can be further measured in selected provinces with linked databases including prescriptions. CONCLUSIONS: This first step could provide a better initial understanding of the quality of AF/AFL care in Canada, but important gaps in the meaningful measurement of QIs remain. The AF/AFL QI working group has limited capacity to make progress without national level leadership and the resources to support data aggregation, data analysis, and pan-Canadian reporting.
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.
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 | 0.000 |
| 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 it