PP09 Use Of Real-World Evidence For Managing Health Technologies Throughout The Life Cycle Of Transcatheter Aortic Valve Interventions
Bibliographic record
Abstract
Introduction A Cardiology Evaluation Unit was established in 2004 within Québec’s Institut national d’excellence en santé et en services sociaux (INESSS) with a novel mandate to collect real-world evidence (RWE) to complement literature-based health technology assessment. In 2010 following publication of the seminal PARTNER trial, INESSS was mandated by the health ministry to review the evidence on transcatheter aortic valve intervention (TAVI) for patients with aortic stenosis. Herein we show how RWE was used to evaluate health system performance throughout the technology’s life cycle and inform organizational and clinical decisions. Methods Various products were diffused by INESSS over the years: a guidance (2012), an updated literature review (2017) and provincial standards (2017), in parallel with RWE reports covering TAVI use from 2013-2015, from 2013-2018, and a 2021 RWE report combined with administrative data covering transcatheter and surgical treatment of aortic stenosis from 2013-2019. Results Based on the guidance’s review of evidence, TAVI was initially recommended for patients considered at too high risk for the surgical approach, under the condition of continued evidence generation to address uncertainty. The subsequent literature review update highlighted that the indication for TAVI had been extended to patients at moderate surgical risk. INESSS produced standards in collaboration with clinical experts to optimize and harmonize the use of TAVI in designated centers. Evaluation of structures, processes and outcomes by INESSS continued until 2019, showing a continuous increase in the use of TAVI, improved short-term survival, and careful patient selection via a multidisciplinary process. RWE also highlighted the impact of TAVI on the overall organization of care for patients with aortic stenosis, as selection criteria further expanded to patients at lower surgical risk, raising important issues regarding patient selection processes, wait times, and longer-term outcomes. Conclusions TAVI clinical practice is constantly evolving and leads to changes in the management of aortic stenosis. RWE provided essential organizational and clinical input to inform clinical guidance and decision-making by Québec policy-makers, clinicians and patients.
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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 | 0.197 | 0.436 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.017 | 0.008 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".