Integrated Management Program Advancing Community Treatment of Atrial Fibrillation (IMPACT-AF): A cluster randomized trial of a computerized clinical decision support tool
Bibliographic record
Abstract
BACKGROUND: Clinical decision support (CDS) tools designed to digest, filter, organize, and present health data are becoming essential in providing clinical and cost-effective care. Many are not rigorously evaluated for benefit before implementation. We assessed whether computerized CDS for primary care providers would improve atrial fibrillation (AF) management and outcomes as compared to usual care. METHODS: Overall, 203 primary care providers were recruited, randomized, and then cluster stratified by location (urban, rural) to usual care (n = 99) or CDS (n = 104). Providers recruited 1,145 adult patients with AF to participate. The intervention was access to an evidenced-based, point-of-care computerized CDS designed to support guideline-based AF management. The primary efficacy outcome was a composite of unplanned cardiovascular hospitalizations and AF-related emergency department visits; the primary safety outcome was major bleeding, both over 1 year. Patients were the units of intention-to-treat analysis. RESULTS: No significant effects on the primary efficacy (130 control, 118 CDS, hazard ratio: 0.98 [95% CI 0.71-1.37], P = .926) or safety (n = 7 usual care, n = 8 CDS, 1.3% total, P = .939) outcomes were observed at 12-months. CONCLUSIONS: IMPACT-AF rigorously assessed a CDS tool in a highly representative sample of primary care providers and their patients; however, no impact on outcomes was observed. Considering the proliferating use of CDS applications, this study highlights the need for efficacy assessments prior to adoption and clinical implementation.
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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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".