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Record W2588631680 · doi:10.1097/ncq.0000000000000250

Implementation of Interdisciplinary Rapid Rounds in Observation Units

2017· article· en· W2588631680 on OpenAlexaff
Lindsey Ryan, Stephanie Scott, Willa Fields

Bibliographic record

VenueJournal of Nursing Care Quality · 2017
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsFields Institute for Research in Mathematical Sciences
Fundersnot available
KeywordsPhonePatient satisfactionPsychological interventionPatient dischargeProcess (computing)Patient careMEDLINEPsychologyNursingMedical emergencyMedical educationOperations managementProcess managementMedicineBusinessComputer scienceEngineering

Abstract

fetched live from OpenAlex

Lack of collaboration and communication can lead to medical errors, increased length of stay, and diminished patient satisfaction. The purpose of this project was to improve nurse efficiency, interdisciplinary communication and collaboration, and patient satisfaction with the discharge process through Rapid Rounds. The results demonstrated that interdisciplinary communication and collaboration improved coordination of care, as evidenced by improved Press Ganey percentile rankings for readiness for discharge and speed of the discharge process, increased pharmaceutical interventions, and fewer phone calls to physicians.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.236

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.170
GPT teacher head0.549
Teacher spread0.379 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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