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Effect of interhospital transfer on resource utilization and outcomes at a tertiary care referral center*

2007· article· en· W2013713933 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.

Bibliographic record

VenueCritical Care Medicine · 2007
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsRPM International (Canada)
Fundersnot available
KeywordsMedicineIntensive care unitEmergency medicineReferralAPACHE IITertiary referral hospitalPsychological interventionAcute careObservational studyCohortHealth careRetrospective cohort studyIntensive care medicineInternal medicineFamily medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Mortality and length of stay are two outcome variables commonly used as benchmarks in rating the performance of medical centers. Acceptance of transfer patients has been shown to affect both outcomes and the costs of health care. Our objective was to compare observed and predicted lengths of stay, observed and predicted mortality, and resource consumption between patients directly admitted and those transferred to the intensive care unit (ICU) of a large academic medical center. DESIGN: Observational cohort study. SETTING: Mixed medical/surgical ICU of a university hospital. PATIENTS: A total of 4,569 consecutive patients admitted to a tertiary care ICU from April 1, 1997, to March 30, 2000. INTERVENTIONS: None. MEASUREMENTS: Acute Physiology and Chronic Health Evaluation (APACHE) III score, actual and predicted ICU and hospital lengths of stay, actual and predicted ICU and hospital mortality, and costs per admission. MAIN RESULTS: Crude comparison of directly admitted and transfer patients revealed that transfer patients had significantly higher APACHE III scores (mean, 60.5 vs. 49.7, p < .001), ICU mortality (14% vs. 8%, p < .001), and hospital mortality (22% vs. 14%, p < .001). Transfer patients also had longer ICU lengths of stay (mean, 6.0 vs. 3.8 days, p < .001) and hospital lengths of stay (mean, 20 vs. 15.9 days, p < .001). Stratified by disease severity using the APACHE III model, there was no difference in either ICU or hospital mortality between the two populations. However, in the transfer group with the lowest predicted mortality of 0-20%, ICU and hospital lengths of stay were significantly higher. In crude cost analysis, transfer patients' costs were $9,600 higher per ICU admission compared with nontransfer patients (95% confidence interval, $6,000-$13,400). Risk stratification revealed that the higher per-patient cost was entirely confined to the transfer patients with the lowest predicted mortality. CONCLUSIONS: Patients transferred to a tertiary care ICU are generally more severely ill and consume more resources. However, they have similar adjusted mortality outcomes when compared with directly admitted patients. The difference in resource consumption is mainly attributable to the group of patients in the lowest predicted risk bracket.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.163
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.025
GPT teacher head0.361
Teacher spread0.336 · 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