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Wearing identification wristbands: implications for newborn safety in maternity hospitals

2019· article· en· W2933367110 on OpenAlexaff
Raiana Soares de Sousa Silva, Sílvana Santiago da Rocha, Márcia Teles de Oliveira Gouvéia, Amanda Lúcia Barreto Dantas, José Diego Marques Santos, Nalma Alexandra Rocha de Carvalho

Bibliographic record

VenueEscola Anna Nery · 2019
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicinePublic hospitalNursingIdentification (biology)Medical recordSurgery

Abstract

fetched live from OpenAlex

ABSTRACT Objective: to analyze the wearing of identification wristbands in newborns admitted in a public maternity hospital, regarding patient safety. Method: descriptive study, of the survey type, carried out in a reference public maternity hospital, through observations and interviews. Two hundred and sixty newborns were included. Results: 15.4% of the newborns had no identification wristbands, and 18% of the wristbands had data that did not match with the medical records. 90.9% of the wristbands were easily accessible for checking; however, in 80.9% of the cases, the wristband was not checked before the nursing procedures, and the mother or caregiver was not instructed on wearing the wristband in 76.8% of respondents. Conclusion and implications for practice: there should be training of the nursing team and other health professionals on the placement and daily checking of wristbands, considering international protocols and recommendations regarding patient safety.

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)0.002
metaresearch head score (Gemma)0.012
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 score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.045
GPT teacher head0.423
Teacher spread0.378 · 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".

Quick stats

Citations12
Published2019
Admission routes1
Has abstractyes

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