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Record W2073878107 · doi:10.1108/13660750310474508

Clinical quality improvement project: finding a repeatable approach for improving STAT lab testing

2003· article· en· W2073878107 on OpenAlexaffabout
Lynette Lutes, Sarvesh Logsetty, Jan McGuinness, Joan M. Carlson

Bibliographic record

VenueLeadership in Health Services · 2003
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsStollery Children's HospitalUniversity of Alberta Hospital
Fundersnot available
KeywordsQuality managementQuality (philosophy)Process managementDisseminationMedicineProcess (computing)Project teamMedical educationOperations managementKnowledge managementBusinessEngineeringComputer science

Abstract

fetched live from OpenAlex

Explores the development of a clinical quality improvement pilot project at the University of Alberta Hospital and Stollery Children’s Hospital which aimed to establish a team of individuals that could disseminate a culture of quality improvement and develop a framework for a quality process that could be replicated and repeated. Outcomes of the clinical pilot project included improved performance as well as opportunities to learn some key lessons around team membership and involvement.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.132
metaresearch head score (Gemma)0.162
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.132
Threshold uncertainty score0.698

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1320.162
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0070.007
Scholarly communication0.0070.005
Open science0.0060.013
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0040.001

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 head0.546
GPT teacher head0.533
Teacher spread0.013 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2003
Admission routes2
Has abstractyes

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