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Record W4394065248 · doi:10.1093/ajhp/zxae100

Evaluation of pharmacy-supplied half and quarter tablets at an academic medical center

2024· article· en· W4394065248 on OpenAlexaboutno aff
Caitlyn Blake, Andrew Dwenger, Erin R. Fox

Bibliographic record

VenueAmerican Journal of Health-System Pharmacy · 2024
Typearticle
Languageen
FieldHealth Professions
TopicSafe Handling of Antineoplastic Drugs
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)PharmacyMedicineHealth careOrder entryMedical emergencyFamily medicineOperations managementEngineering

Abstract

fetched live from OpenAlex

PURPOSE: Manipulation of tablet medications to produce a customized dose is common practice, and splitting tablets may reduce the acquisition cost of the medication. However, cost savings may be diminished by the cost of the increased labor and repackaging materials needed when splitting tablets. Splitting tablets may also result in safety concerns if the final products are under (eg, reduced benefit) or over (eg, toxicity) the desired dosage. The purpose of this quality improvement project was to evaluate and recommend changes for all half- and quarter-tablet medications prepared and distributed from the inpatient pharmacy at University of Utah Health (U of U Health). SUMMARY: The evaluation included all half- and quarter-tablet medications prepared by pharmacy technicians for administration to patients admitted to U of U Health hospitals. A final list of 173 half- and quarter-tablet dosages was evaluated for opportunities to decrease the total number. On the basis of the developed criteria, 93 half- and quarter-tablet dosages (54%) were recommended to be removed from routine stock in the inpatient pharmacy. Systems remain in place to create customized half and quarter tablets if required for patient care. CONCLUSION: Reducing the number of medications for which half and quarter tablets are used may allow pharmacy technicians to prioritize other patient care tasks and potentially decrease waste.

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)0.017
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.091
GPT teacher head0.490
Teacher spread0.400 · 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 designOther design
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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Health-System PharmacySame topicSafe Handling of Antineoplastic DrugsFrench-language works237,207