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Record W2122096060 · doi:10.5430/jha.v3n5p39

Shift-to-shift handoff: A comparison between two methods of conveying essential information in a University Hospital in North-eastern Italy

2014· article· en· W2122096060 on OpenAlexvenueno aff
Rosanna Quattrin, Laura Calligaris, C Londero, Enrico Zalateu, Silvio Brusaferro

Bibliographic record

VenueJournal of Hospital Administration · 2014
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsHandoverMedicineCitationShift workPatient safetyUnit (ring theory)Paradigm shiftIntervention (counseling)Medical emergencyNursingOperations managementHealth carePsychologyComputer scienceTelecommunicationsEngineeringLibrary science

Abstract

fetched live from OpenAlex

Objective: The present study focuses on effective communication among nurses during a shift-to-shift handoff. Methods: The completeness of data conveyed during the shift-to-shift handoff was compared in two University Hospital Units, before and after the introduction of a pre-printed sheet summarizing the most important patients’ piece of information. The study took place in a University Hospital located in North-eastern Italy. In the first study phase 111 single patient’s handoffs were analyzed: 52 in Operative Unit 1 (OU1) and 59 in Operative Unit 1 (OU2). In the second phase of the study 39 handoffs were considered: 19 in the OU1 and 20 in the OU2. The intervention consisted of the introduction of a pre-printed semi structured sheet summarizing the patients’ information. The main outcome measures were the patients’ information written on the form and the data available for consultation by colleagues on the next work shift. Results: The four categories of items that most significantly increased after the introduction of the semi-structured form were respectively: neurological status, vital signs, pain assessment and wound care. However, none of the items that showed a reduction in citation, both for single OU and overall, were significant. Conclusions: This study shows how the introduction of a pre-printed form forces the operators to hold in consideration important critical values of a patient, thus bettering the quality and safety of the handoffs.

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 score0.009
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.324
Teacher spread0.310 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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