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Record W2098917240 · doi:10.1136/qshc.2009.035147

Tracing the foundations of a conceptual framework for a patient safety ontology

2010· article· en· W2098917240 on OpenAlexafffund
W. B. Runciman, G. Ross Baker, Philippe Michel, Susan Dovey, Richard Lilford, Natasja Koitzsch Jensen, Rhona Flin, William B. Weeks, Pierre Lewalle, Itziar Larizgoitia, David Bates

Bibliographic record

VenueBMJ Quality & Safety · 2010
Typearticle
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsUniversity of Toronto
FundersNational Health and Medical Research CouncilMedical Research CouncilFaculty of Medicine, McGill UniversityBrigham and Women's Hospital
KeywordsPatient safetyOntologyHealth careQuality (philosophy)MedicineConceptual frameworkComputer scienceKnowledge managementData scienceProcess managementEngineeringSociology

Abstract

fetched live from OpenAlex

BACKGROUND: In work for the World Alliance for Patient Safety on research methods and measures and on defining key concepts for an International Patient Safety Classification (ICPS), it became apparent that there was a need to try to understand how the meaning of patient safety and underlying concepts relate to the existing safety and quality frameworks commonly used in healthcare. OBJECTIVES: To unfold the concept of patient safety and how it relates to safety and quality frameworks commonly used in healthcare and to trace the evolution of the ICPS framework as a basis of the electronic capture of the component elements of patient safety. CONCLUSION: The ICPS conceptual framework for patient safety has its origins in existing frameworks and an international consultation process. Although its 10 classes and their semantic relationships may be used as a reference model for different disciplines, it must remain dynamic in the ever-changing world of healthcare. By expanding the ICPS by examining data from all available sources, and ensuring rigorous compliance with the latest principles of informatics, a deeper interdisciplinary approach will progressively be developed to address the complex, refractory problem of reducing healthcare-associated harm.

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)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.162
GPT teacher head0.517
Teacher spread0.356 · 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 designTheoretical or conceptual
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

Citations30
Published2010
Admission routes2
Has abstractyes

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