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Record W4312517830 · doi:10.2106/jbjs.rvw.22.00082

Bundled Care in Elective Total Joint Replacement: Payment Models in Sweden, Canada, and the United States

2022· article· en· W4312517830 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJBJS Reviews · 2022
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsSinai Health SystemUniversity of Toronto
Fundersnot available
KeywordsReimbursementPaymentMedicineHealth careActuarial scienceQuality (philosophy)BusinessFinanceEconomics

Abstract

fetched live from OpenAlex

➢: Rising health-care expenditures and payer dissatisfaction with traditional models of reimbursement have driven an interest in alternative payment model initiatives. ➢: Bundled payments, an alternative payment model, have been introduced for total joint replacement in Sweden, the United States, and Canada to help to curb costs, with varying degrees of success. ➢: Outpatient total knee arthroplasty and total hip arthroplasty are becoming increasingly common and provide value for patients and payers, but have negatively impacted providers participating in bundled payment models due to considerable losses and decreased reimbursement. ➢: A fine balance exists between achieving cost savings for payers and enticing participation by providers in bundled payment models. ➢: The design of each model is key to payer, provider, and patient satisfaction and should feature comprehensive coverage for a full cycle of care whether it is in the inpatient or outpatient setting, is linked to quality and patient-reported outcomes, features appropriate risk adjustment, and sets limits on responsibility for unrelated complications and extreme outlier events.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.272
Teacher spread0.248 · 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