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Record W2329170210 · doi:10.2146/news140011

FDA backs manufacturer-produced patient information

2014· article· en· W2329170210 on OpenAlexaboutno aff
Kate Traynor

Bibliographic record

VenueAmerican Journal of Health-System Pharmacy · 2014
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsMedical prescriptionPharmacyPackage insertProduct (mathematics)MedicineOrder (exchange)Family medicineBusinessAdvertisingMedical emergencyNursingPharmacology

Abstract

fetched live from OpenAlex

After decades of debate over how best to provide patients with information about their medications at the point of dispensing, FDA wants to place the primary responsibility for the process in the hands of drug manufacturers. “We suggest that information about a manufactured product is best produced and tested by that manufacturer,” said Janet Woodcock, chief of FDA’s drugs division, during testimony on December 11 before the Senate Special Committee on Aging. Woodcock was referring to patient medication information (PMI). Examples of PMI include leaflets that are packaged along with mail-order prescription products or attached to the bag in which a patient’s medications are placed for pickup at a pharmacy. Manufacturer-produced PMI is used in the European Union, Canada, Japan, Australia, and New Zealand, Woodcock said. If implemented, FDA’s plan would replace the current U.S. system through which PMI is created in electronic form by ASHP and other providers of drug information and used by community pharmacies to generate leaflets for patients. FDA does not review or approve the leaflets, but their content and format are subject to FDA standards.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.959
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.003
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 head0.209
GPT teacher head0.505
Teacher spread0.296 · 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.

Study designNot applicable
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
Published2014
Admission routes1
Has abstractyes

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