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Association of Intensive Care Unit Patient-to-Clinician Ratios with Mortality Across Two U.S. Health Systems

2025· article· en· W4410230134 on OpenAlexafffund
Hayley B. Gershengorn, George L. Anesi, Deena Kelly Costa, Erich Dress, Amy Dzierba, Robert Fowler, Andrew A. Kramer, Danny Lizano, Damon C. Scales, Allan Garland, Hannah Wunsch

Bibliographic record

VenueAnnals of the American Thoracic Society · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsHealth Sciences CentreUniversity of ManitobaSunnybrook Health Science CentreSunnybrook HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchLeonard Davis Institute of Health Economics, University of PennsylvaniaNational Heart, Lung, and Blood InstituteChildren's Hospital Research Institute of ManitobaManitoba Medical Service Foundation
KeywordsMedicineAssociation (psychology)Emergency medicineMEDLINEIntensive care medicine

Abstract

fetched live from OpenAlex

Abstract Rationale The association of interprofessional team member workload with intensive care unit (ICU) outcomes is understudied. Objectives To evaluate the association of patient-to-intensivist ratio (PIR), patient-to-respiratory therapist ratio (PRTR), and patient–to–clinical pharmacist ratio (PpharmR) with hospital mortality. Methods We conducted a retrospective study of adults admitted from the emergency department to an ICU with acute respiratory failure or sepsis within two U.S. healthcare systems (2013–2018). Our primary exposures were patient-to-clinician ratios (PIR, PRTR, and PpharmR) averaged over the ICU stay; our primary outcome was hospital mortality. We used multivariable mixed-effects regression, with patient-to-clinician ratios modeled as restricted cubic splines (four knots). We primarily considered each exposure separately, then included all ratios together. Results Our cohort included 45,036 patients (mean age, 66.0 [standard deviation, 16.6] years; 23,420 [52.0%] men) across 27 ICUs within 24 hospitals. Of these, 29,326 (65.1%) had acute respiratory failure, 32,434 (72.0%) had sepsis, and 9,675 (21.5%) died in the hospital. The average PIR was 9.3 (standard deviation, 3.6), and the average PRTR was 7.9 (standard deviation, 3.2); the average PpharmR was 15.0 (standard deviation, 5.5) among patients (n = 8,950 of 45,036) in ICUs with clinical pharmacists (n = 8 of 27). We found no significant association between average daily PIR (Wald test for all spline terms: P = 0.24) or PRTR (P = 0.18) and hospital mortality in the full cohort; similarly, among patients in ICUs with pharmacists, no significant association of PpharmR with mortality was observed (P = 0.08). Models including ratios together yielded similar null results. Conclusions We did not identify an association of any average daily patient-to-clinician ratio with hospital mortality for U.S. ICU patients with sepsis or respiratory failure.

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)0.005
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.160
GPT teacher head0.451
Teacher spread0.291 · 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".

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Citations1
Published2025
Admission routes2
Has abstractyes

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