Implementation of processes of care to support transcatheter aortic valve replacement programs
Bibliographic record
Abstract
Transcatheter aortic valve replacement (TAVR) is increasingly accepted as a feasible and safe therapeutic alternative to open heart surgery in select patients. Procedural success and technological advances combined with favorable clinical outcomes and demonstrated prolonged survival are establishing TAVR as the standard of care in symptomatic patients who are at higher risk or not candidates for conventional surgery. The growing number of referrals and complexities of care of TAVR candidates warrants a program that ensures appropriate patient assessment and triage, establishes appropriate processes, and promotes continuity of care. To address these needs and prepare for the anticipated growth of transcatheter heart valve (THV) therapeutic options, the TAVR program at St. Paul's Hospital, Vancouver, Canada, implemented an electronic centralized and clinically managed referral and triage program, and a THV Nurse Coordinator position to support the program and patients, conduct a global functioning assessment, and provide clinical triage coordination, waitlist management, patient and family education and communication with clinicians. Interdisciplinary rounds assist in the selection of candidates, while a clinical data management system facilitates standardized documentation and quality assurance from referral to follow-up. The unique needs of TAVR patients and programs require the implementation of unique processes of care and tailored assessment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| 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 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".