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Record W2170427869 · doi:10.1310/hpj4407-584

Reevaluation of Emergency Drug Management in a Tertiary Care Mother-Child Hospital

2009· article· en· W2170427869 on OpenAlexaff
Jean‐François Bussières, Karin Scharr, Christopher Marquis, Sophie Saindon, Baruch Toledano, Lydia DiLiddo, Sylvie Charrette

Bibliographic record

VenueHospital Pharmacy · 2009
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineMedical emergencyResuscitationIntensivistEmergency departmentEmergency medicineIntensive careNursingIntensive care medicine

Abstract

fetched live from OpenAlex

Purpose To evaluate the management of emergency drugs in a mother-child teaching hospital. Methods A physical inventory of all the resuscitation carts, emergency carts, and emergency boxes was taken. Fifteen compliance criteria were established to evaluate partial trays of emergency medications. The contents of full and partial emergency medication trays and boxes were revised, and an improved process was implemented based on a review of the literature. The research team included 2 pharmacists, 1 anesthetist, 1 intensivist, 1 emergency doctor, 1 nurse, and 1 research assistant. Results Before the harmonization process, there were 11 full resuscitation carts with 48 items and 30 partial emergency carts with an average item count of 15.4 ± standard deviation 4.4, as well as 16 pediatric boxes and 3 emergency boxes in pediatrics and obstetrics, respectively. During the evaluation process, 1,911 distribution units were checked, 2.5% of which had expired. Following the process there were 14 identical resuscitation carts with 43 items and 25 emergency carts with 21 items. Conclusion There are few examples of steps that can be taken to evaluate and update the management of emergency medications in health care facilities. This evaluative study outlines an approach that entailed taking a physical inventory, evaluating the process, and improving the management model within a tertiary care university hospital center. A review of the new process will be performed in 12 months' time.

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)0.004
metaresearch head score (Gemma)0.016
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 score0.022
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.321
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 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

Citations4
Published2009
Admission routes1
Has abstractyes

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