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Record W2042873697 · doi:10.5430/jha.v4n2p78

Economies of scale in cardiac surgery

2015· article· en· W2042873697 on OpenAlexvenueno aff
Paul Lillrank, Atanu Chaudhuri, Paulus Torkki

Bibliographic record

VenueJournal of Hospital Administration · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsScale (ratio)Economies of scaleCardiac surgeryBusinessMedicineGeographySurgeryMarketingCartography

Abstract

fetched live from OpenAlex

Objective: The objective of this paper is to investigate the impact of scale of surgical units on the productivity of patient processes.Methods: The context, intervention, mechanism, output (CIMO) model of Evaluation research is used. The scale–performance mechanisms are examined through resource intensity and throughput time per patient. The productivity of Coronary Artery Bypass Graft (CABG) surgery in a very large and a smaller hospital are compared.Results: While the large hospital performed 5.1 times more CABG surgeries per year than the smaller hospital, in terms of total resource consumption per patient it was 13% less productive. The large hospital had a 5% efficiency advantage in Operating Theatres (OTs), but it was 30% less efficient in ward care.Conclusions: Economies of scale are not found at the patient process level. Operating policies seem to assume more importance than scale.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.218

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 head0.020
GPT teacher head0.268
Teacher spread0.249 · 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 teacher head, 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

Citations8
Published2015
Admission routes1
Has abstractyes

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