MétaCan
Menu
Back to cohort
Record W2126567777 · doi:10.12927/hcq..17662

Enhancing Patient Safety Through a Standardized Model of Physiologic Monitoring

2005· article· en· W2126567777 on OpenAlex
Mary-Anne Davies, Heather Tales

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealthcare Quarterly · 2005
Typearticle
Languageen
FieldMedicine
TopicHealthcare Technology and Patient Monitoring
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsStandardizationPatient safetyAnticipation (artificial intelligence)MedicineHealth careBest practiceMedical emergencyIntensive care medicineComputer sciencePolitical science

Abstract

fetched live from OpenAlex

The use of physiologic monitoring (e.g., cardiac monitoring) as an important component in providing safe patient care has escalated over the past two decades. It enables the clinician to detect physiologic changes in the patient's condition before they become clinically significant, thus allowing anticipation and prevention of adverse events. Issues and concerns regarding physiologic monitoring were raised throughout the London Health Sciences Centre (LHSC) leading to the approval of a project to develop a policy and guidelines for its use: the focus being standardization of processes and patient safety improvements. This article describes the underlying issues, the execution and results of the project, and its impact on patient safety within LHSC.

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.

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)0.000
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 score0.874
Threshold uncertainty score0.887

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.044
GPT teacher head0.341
Teacher spread0.297 · 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