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Record W2110373765 · doi:10.12927/cjnl.2011.22464

Towards a National Report Card in Nursing: A Knowledge Synthesis

2011· article· en· W2110373765 on OpenAlex

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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNursing leadership · 2011
Typearticle
Languageen
FieldNursing
TopicNursing Diagnosis and Documentation
Canadian institutionsUniversity Health NetworkUniversity of TorontoOntario Shores Centre for Mental Health SciencesMinistry of Health and Long Term Care
FundersHealth CanadaUniversity of Toronto
KeywordsReport cardNursingNursing researchPsychologyMedicine

Abstract

fetched live from OpenAlex

this paper is an abridged version of a knowledge synthesis undertaken to inform the proceedings of a collaborative forum of nurse leaders convened under the auspices of health Canada, the academy of Canadian Executive Nurses, the Canadian Nurses association and Canada health infoway for the purpose of discussing the development of a nursing report card for Canada. the synthesis summarized the state of the science in the measurement of nursing-sensitive outcomes and the utilization of nursing report cards -information that informed forum participants' dialogue and planning. this condensed version of the synthesis focuses on initiatives related to outcomes and performance monitoring in nursing, including specific indicators and reporting systems and the development, implementation and utilization of nursing report cards. origins of outcomes/performance monitoring Efforts to identify nursing's contribution to high-quality care and to conduct research into patient outcomes date back to Nightingale However, the systematic collection of data to assess outcomes did not gain widespread attention until the late 1970s, when concerns about quality of care prompted the development of the Universal Minimum Health Data Set, which was followed shortly thereafter by the Uniform Hospital Discharge Data Set These data sets facilitated consistency in data collection among healthcare organizations by prescribing the data elements to be gathered. The aggregated data informed the assessment of care quality in hospitals and provided discharge information about patients.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.719
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.273
GPT teacher head0.372
Teacher spread0.099 · 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