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Record W2398349135

Improving medication administration systems: an evaluation study.

2006· article· en· W2398349135 on OpenAlexaff
Jocelyn Bennett, Lee Anne Harper-Femson, Jody L. Tone, Yasmin Rajmohamed

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsPharmacyMedicinePatient safetyMedical emergencyFocus groupNursingHealth careHealthcare systemPharmacistBusiness
DOInot available

Abstract

fetched live from OpenAlex

Medication errors are a universal health-care concern, and improving medication administration systems is important to enhance safety. The purpose of this study was to compare the effectiveness of an existing unit dose system using a medication cart to a new system where medications are decentralized to a locked cupboard at the patient's bedside. Quantitative and qualitative approaches were used to determine the effectiveness and efficiency of the medication administration systems. Data was collected using time studies to evaluate the efficiency of the two systems. This data included medication errors, missing doses and interruptions occurring during the medication preparation and administration process. Focus groups were conducted with nurses, pharmacists and pharmacy technicians to better understand the impact of changing systems. Study results demonstrated benefits associated with decentralizing the medication distribution to the bedside, including nurses spending more time with patients, nurses investing less time preparing and distributing medication and fewer interruptions for nurses as they prepared and distributed medication. Nurses and pharmacists associated the new system with enhanced patient safety and work satisfaction.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.337
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 head0.127
GPT teacher head0.412
Teacher spread0.285 · 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

Citations29
Published2006
Admission routes1
Has abstractyes

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