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Record W4292630518

Communicate with me: Information Exchanges between Nurses.

2015· article· en· W4292630518 on OpenAlexaboutno aff

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsDocumentationFront lineNursingQuality (philosophy)Health carePatient careInformation exchangePatient safetyPsychologyMedicineMedical educationComputer science
DOInot available

Abstract

fetched live from OpenAlex

Patient safety and continuity of quality care are dependent on effective communication. Clinical nurse specialists at the Health Sciences Centre in Winnipeg were finding that when they sought out essential patient information from front-line nurses, they sometimes encountered gaps in knowledge about the patient. Having to acquire this information elsewhere was causing unnecessary delays in care. The authors, members of an advanced practice nurses group at the Health Sciences Centre in Winnipeg, undertook a quality improvement project to gain an understanding of the problems in information exchanges between nurses. Through interviews with front-line nurses on four units, they found that many factors contributed to the lack of knowledge nurses had about patients, such as inconsistent documentation, poorly defined plans of care and variable communication patterns. This project highlighted the need to develop a standardized handoff template to aid in information exchanges.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.182

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.055
GPT teacher head0.272
Teacher spread0.218 · 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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