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Quality assurance practices for point of care testing programs: Recommendations by the Canadian society of clinical chemists point of care testing interest group

2020· review· en· W3108574884 on OpenAlexaffabout
Allison A. Venner, Lori Beach, Jennifer Shea, Michael J. Knauer, Huang Yun, Angela W.S. Fung, James Dalton, Mathieu Provençal, Julie Shaw

Bibliographic record

VenueClinical Biochemistry · 2020
Typereview
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsCanadian Electricity AssociationOttawa Hospital
Fundersnot available
KeywordsPoint-of-care testingQuality assuranceMedicineQuality (philosophy)Medical physicsPatient careQuality managementTest (biology)Operations managementExternal quality assessmentNursingEngineeringPathologyManagement system

Abstract

fetched live from OpenAlex

Point of Care Testing (POCT) refers to clinical laboratory testing performed outside the central laboratory, nearer to the patient and sometimes at the patient bedside. The testing is usually performed by clinical staff, such as physicians or nurses, who are not laboratory trained. This document was developed by the POCT Interest group of the Canadian Society of Clinical Chemists (CSCC) as practical guidance for quality assurance practices related to POCT performed in hospital and outside hospital environments. The aspects of quality assurance addressed in this document include: (1) device selection, (2) initial device verification, (3) ongoing device verification, (4) ongoing quality assurance including reagent and quality control (QC) lot changes, and (5) quality management including operator and document management.

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)0.059
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.618
Threshold uncertainty score0.769

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0590.052
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0140.013
Science and technology studies0.0030.003
Scholarly communication0.0050.003
Open science0.0080.003
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0050.003

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 head0.443
GPT teacher head0.556
Teacher spread0.113 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations29
Published2020
Admission routes2
Has abstractyes

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