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Record W2289770970 · doi:10.1093/labmed/lmv006

Phlebotomy Cycle Time Related to Phlebotomist Experience and/or Hospital Location

2015· article· en· W2289770970 on OpenAlexaffabout
Karie Jones, C. Lemaire, Christopher Naugler

Bibliographic record

VenueLaboratory Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsUniversity of CalgaryCalgary Laboratory Services
Fundersnot available
KeywordsPhlebotomyMedicineEmergency medicineMedical emergencySurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Little information is available regarding expected phlebotomy cycle time (total time needed to draw a blood specimen) in inpatient settings. Examining this variable in 4 hospitals in Calgary, Alberta, Canada, we determined the distribution of phlebotomy cycle times and compared this by hospital and by phlebotomist experience. METHODS: Between April 2014 and August 2014, we observed phlebotomy timing at 4 adult acute care hospital locations. Phlebotomists were stratified into 3 experience levels: 0 to 2 years, 2 to 5 years, and more than 5 years. We observed a total of 110 different phlebotomists. RESULTS: We observed no statistical difference between experience levels (P = .07) or hospital location (P = .44) on mean phlebotomy cycle time. CONCLUSIONS: The mean (SD) phlebotomy cycle time was 259 (52) seconds per patient for normal phlebotomy procedures. If expected minimum and maximum phlebotomy times are defined as mean +/- 2 SD, the expected cycle time range is 196 to 404 seconds.

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)0.001
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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.039
GPT teacher head0.343
Teacher spread0.304 · 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

Citations2
Published2015
Admission routes2
Has abstractyes

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