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Record W2130331477

Multiple intravenous infusions phase 1b: practice and training scan.

2012· article· en· W2130331477 on OpenAlexaboutno aff
Andrea Cassano-Piché, Mark Fan, Shirley Sabovitch, Caterina Masino, AC Easty

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldEngineering
TopicIntravenous Infusion Technology and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsIntravenous InfusionsMedicineFood and drug administrationPatient safetyHarmAdministration (probate law)Intravenous drugMedical emergencyEmergency medicineAnesthesiaFamily medicinePsychologyHealth carePolitical science
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Minimal research has been conducted into the potential patient safety issues related to administering multiple intravenous (IV) infusions to a single patient. Previous research has highlighted that there are a number of related safety risks. In Phase 1a of this study, an analysis of 2 national incident-reporting databases (Institute for Safe Medical Practices Canada and United States Food and Drug Administration MAUDE) found that a high percentage of incidents associated with the administration of multiple IV infusions resulted in patient harm. OBJECTIVES: The primary objectives of Phase 1b of this study were to identify safety issues with the potential to cause patient harm stemming from the administration of multiple IV infusions; and to identify how nurses are being educated on key principles required to safely administer multiple IV infusions. DATA SOURCES AND REVIEW METHODS: A field study was conducted at 12 hospital clinical units (sites) across Ontario, and telephone interviews were conducted with program coordinators or instructors from both the Ontario baccalaureate nursing degree programs and the Ontario postgraduate Critical Care Nursing Certificate programs. Data were analyzed using Rasmussen's 1997 Risk Management Framework and a Health Care Failure Modes and Effects Analysis. RESULTS: Twenty-two primary patient safety issues were identified with the potential to directly cause patient harm. Seventeen of these (critical issues) were categorized into 6 themes. A cause-consequence tree was established to outline all possible contributing factors for each critical issue. Clinical recommendations were identified for immediate distribution to, and implementation by, Ontario hospitals. Future investigation efforts were planned for Phase 2 of the study. LIMITATIONS: This exploratory field study identifies the potential for errors, but does not describe the direct observation of such errors, except in a few cases where errors were observed. Not all issues are known in advance, and the frequency of errors is too low to be observed in the time allotted and with the limited sample of observations. CONCLUSIONS: The administration of multiple IV infusions to a single patient is a complex task with many potential associated patient safety risks. Improvements to infusion and infusion-related technology, education standards, clinical best practice guidelines, hospital policies, and unit work practices are required to reduce the risk potential. This report makes several recommendations to Ontario hospitals so that they can develop an awareness of the issues highlighted in this report and minimize some of the risks. Further investigation of mitigating strategies is required and will be undertaken in Phase 2 of this research.

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)0.004
metaresearch head score (Gemma)0.017
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: Other · Consensus signal: none
Teacher disagreement score0.292
Threshold uncertainty score0.581

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.008
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.003

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 head0.019
GPT teacher head0.226
Teacher spread0.207 · 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
GenreOther

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

Citations33
Published2012
Admission routes1
Has abstractyes

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