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Record W4388217192 · doi:10.1136/bmjopen-2023-072744

Cost-effectiveness analysis of the Geriatric Fracture Center (GFC) concept: a prospective multicentre cohort study

2023· article· en· W4388217192 on OpenAlexaff
Alexander Joeris, Sheila Sprague, Michael Blauth, Markus Gosch, Pannida Wattanapanom, Rahat Jarayabhand, Martijn Poeze, Merng Koon Wong, Ernest Beng Kee Kwek, Johannes H. Hegeman, Carlos Perez-Uribarri, Enrique Guerado, Thomas Revak, Sebastian Zohner, David B. Joseph, Mark Phillips

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsImpactMcMaster University
Fundersnot available
KeywordsMedicineCohortQuality of life (healthcare)Prospective cohort studyCost-effectiveness analysisCohort studyGeriatricsQuality-adjusted life yearCost effectivenessCost–benefit analysisEmergency medicineGerontologySurgeryPsychiatryInternal medicineNursingRisk analysis (engineering)

Abstract

fetched live from OpenAlex

INTRODUCTION: Geriatric Fracture Centers (GFCs) are dedicated treatment units where care is tailored towards elderly patients who have suffered fragility fractures. The primary objective of this economic analysis was to determine the cost-utility of GFCs compared with usual care centres. METHODS: The primary analysis was a cost-utility analysis that measured the cost per incremental quality-adjusted life-year gained from treatment of hip fracture in GFCs compared with treatment in usual care centres from the societal perspective over a 1-year time horizon. The secondary analysis was a cost-utility analysis from a societal perspective over a lifetime time horizon. We evaluated these outcomes using a cost-utility analysis using data from a large multicentre prospective cohort study comparing GFCs versus usual care centres that took place in Austria, Spain, the USA, the Netherlands, Thailand and Singapore. RESULTS: GFCs may be cost-effective in the long term, while providing a more comprehensive care plan. Patients in usual care centre group were slightly older and had fewer comorbidities. For the 1-year analysis, the costs per patient were slightly lower in the GFC group (-$646.42), while the quality-adjusted life-years were higher in the usual care centre group (+0.034). The incremental cost-effectiveness ratio was $18 863.34 (US$/quality-adjusted life-year). The lifetime horizon analysis found that the costs per patient were lower in the GFC group (-$7210.35), while the quality-adjusted life-years were higher in the usual care centre group (+0.02). The incremental cost-effectiveness ratio was $320 678.77 (US$/quality-adjusted life-year). CONCLUSIONS: This analysis found that GFCs were associated with lower costs compared with usual care centres. The cost-savings were greater when the lifetime time horizon was considered. This comprehensive cost-effectiveness analysis, using data from an international prospective cohort study, found that GFC may be cost-effective in the long term, while providing a more comprehensive care plan. A greater number of major adverse events were reported at GFC, nevertheless a lower mortality rate associated with these adverse events at GFC. Due to the minor utility benefits, which may be a result of greater adverse event detection within the GFC group and much greater costs of usual care centres, the GFC may be cost-effective due to the large cost-savings it demonstrated over the lifetime time horizon, while potentially identifying and treating adverse events more effectively. These findings suggest that the GFC may be a cost-effective option over the lifetime of a geriatric patient with hip fracture, although future research is needed to further validate these findings. LEVEL OF EVIDENCE: Economic, level 2. TRIAL REGISTRATION NUMBER: NCT02297581.

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)0.011
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.024
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.008
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.051
GPT teacher head0.423
Teacher spread0.372 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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