Screening for atrial fibrillation in Canadian pharmacies: an economic evaluation
Bibliographic record
Abstract
BACKGROUND: Screening for undiagnosed atrial fibrillation may lead to treatment with oral anticoagulation therapy, which can decrease the risk of ischemic stroke. The objective of this study was to conduct an economic evaluation of the Program for the Identification of 'Actionable' Atrial Fibrillation in the Pharmacy Setting (PIAAF-Pharmacy), which screened 1145 participants aged 65 years or more at 30 community pharmacies in Ontario and Alberta between October 2014 and April 2015. METHODS: We used a 2-part decision model to evaluate the short- and long-term costs and quality-adjusted life-years (QALYs) of a pharmacy screening program for atrial fibrillation compared to no screening. Data from the PIAAF-Pharmacy study were used for the short-term model, and the relevant literature was used to extrapolate the benefits of the PIAAF-Pharmacy study in the long-term model. Costs and QALYs were calculated from a payer perspective over a lifetime horizon and were discounted at 1.5%/year. RESULTS: Screening for atrial fibrillation in pharmacies was associated with higher costs ($26) and more QALYs (0.0035) compared to no screening, yielding an incremental cost per QALY gained of $7480. Univariate and probabilistic sensitivity analyses confirmed that screening for atrial fibrillation in a pharmacy setting was a cost-effective strategy. INTERPRETATION: Our results support screening for atrial fibrillation in Canadian pharmacies. Given this finding, efforts should be made by provincial governments and pharmacies to implement such programs in Canada. The addition of atrial fibrillation screening alongside screening and management of other cardiovascular conditions may help to reduce the burden of stroke.
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 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 | 0.017 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".