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Record W2139171331 · doi:10.12927/hcq.2008.19649

Development of Canadian Safety Indicators for Medication Use

2008· article· en· W2139171331 on OpenAlexafffundabout
Rita Nigam, Neil J. MacKinnon, U David, Nicole R. Hartnell, Adrian R. Levy, Mary Ellen Gurnham, Tiffany Nguyen‐Vu

Bibliographic record

VenueHealthcare Quarterly · 2008
Typearticle
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsDalhousie University
FundersAssociation des pharmaciens du CanadaIWK Health CentreCanadian Patient Safety Institute
KeywordsDelphi methodPatient safetyMedicineHealth careBest practicePharmacyPerformance indicatorHealth administrationMedical emergencyNursingBusinessPublic healthMarketingComputer science

Abstract

fetched live from OpenAlex

Reports of preventable illness due to medication errors are widespread in Canada. However, quantifying the magnitude of the problem has been hampered by a lack of measurement tools. Canadian-specific indicators, or performance measures, of safe medication use do not exist. The objective of this study was to develop a set of Canadian consensus-based indicators for the safe use of medication for both in-patient and outpatient settings. A panel of 20 national experts was established from a convenience sample of experts representing medicine, nursing, pharmacy, research and decision-makers in hospitals and community settings across Canada. After creating a list of potential indicators from the literature, the final consensus set was chosen by the panel using a Delphi survey process via e-mail. After three rounds, consensus was obtained on 20 medication-use safety indicators: seven indicators were related to systems of care, five to prescribing/ordering, three to monitoring/assessment, three to medication administration, one to preparation and dispensing and one to purchasing/inventory management. Seventeen of the indicators measure a process of care (in contrast to health outcome); at least 10 have applications outside the in-patient setting. The resulting 20 medication-use safety indicators are diverse in scope and should be applicable in a variety of practice settings. These indicators may provide clinicians and decision-makers with valuable tools to assess the safety of medication-use systems.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.135
GPT teacher head0.398
Teacher spread0.264 · 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 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

Citations32
Published2008
Admission routes3
Has abstractyes

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