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Record W3045308217 · doi:10.1177/0840470420938067

Breaking down the silos: Transcatheter aortic valve implant versus open heart surgery

2020· article· en· W3045308217 on OpenAlexaff
Hamid Sadri

Bibliographic record

VenueHealthcare Management Forum · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicEfficiency Analysis Using DEA
Canadian institutionsMedtronic (Canada)
Fundersnot available
KeywordsAortic valve replacementMedicineStenosisImplantCardiologyInternal medicineSurgery

Abstract

fetched live from OpenAlex

Budget silos innate to hospital global funding schemes tend to inhibit the adoption of innovative clinical practices. In contrast, budget fluidity can encourage initiatives that align with the Quadruple Aim. This article calculated the budget impact of Surgical Aortic Valve Replacement (SAVR) and Transcatheter Valve Implant (TAVI) in high-risk aortic stenosis to demonstrate the value of a full-cost accounting approach. The budget impact of TAVI was $4,000 more than SAVR ($52,576 vs $48,578). However, the cost of managing SAVR adverse events was higher than TAVI ($17,718 vs. $11,754) over 1 year. A scenario analysis demonstrated that the total cost of care for a cohort of 100 patients at baseline ratio of 30% TAVI versus 70% SAVR was similar to a future scenario, with reverse proportions. While TAVI may seem expensive upfront, when considered as a surgical department budget item, the overall cost to the hospital is comparable to the SAVR.

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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.

Opus teacher head0.172
GPT teacher head0.405
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2020
Admission routes1
Has abstractyes

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