MétaCan
Menu
Back to cohort
Record W4416758940 · doi:10.2196/88333

Good Clinical Practice Guidance for Line Materials, Filtration, and Light Protection in Intravenous Medication Administration: Modified Delphi Consensus Study

2025· preprint· en· W4416758940 on OpenAlexvenueno aff
Andrew Dickman, Penelope Tuffin, Rania Al-Jaber, Mona El-Harmeel., Irene Taladriz-Sender, Adam Sutherland, James Waterson, Robert Terkola

Bibliographic record

VenueJMIR Human Factors · 2025
Typepreprint
Languageen
FieldEngineering
TopicIntravenous Infusion Technology and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsDelphi methodPatient safetyDelphiPharmacistBest practiceHarmMEDLINEAdministration (probate law)Health care

Abstract

fetched live from OpenAlex

BACKGROUND There is an unmet need for reliable medication stability information to avoid suboptimal administration of intravenous medications, which may lead to reduced efficacy of therapy and potential patient harm through medication degradation or incompatibilities that cause vascular access issues. OBJECTIVE This study aimed to develop evidence-informed guidance for pharmacists and nurses on the use of administration line materials, in-line filtration, and light protection during storage and intravenous administration of medications commonly used in critical care and oncology. METHODS An initial list of 181 medications was compiled in consultation with pharmacist stakeholders from critical care and oncology specialties. A modified Delphi study was conducted over 3 rounds with a panel of 8 expert pharmacists selected for their clinical expertise, professional experience, and geographic location to ensure representation of diverse health care settings and medication administration practices. Panelists anonymously ranked statements on a 5-point Likert scale developed from a review of the literature with respect to the requirement for a specific administration line material for each medication; the need for, and type of, filtration required during administration; and the need for light protection during storage and administration of medications. After each round, items achieving 80% consensus were finalized. Those that did not achieve consensus were carried forward to the next round. This iterative approach allowed panelists to reconsider their ratings based on emerging group consensus and additional evidence shared by panelists between rounds. RESULTS A total of 1044 administration and storage requirements were assessed for a final list of 174 medications. In round 1, consensus was reached for 613 (58.7%) statements, with every statement being addressed and scored by the panelists. Panelists provided additional evidence sources for their decisions, and these were distributed to all panel members for round 2. All items were addressed and scored by the panelists. By the conclusion of round 3, consensus had been achieved for 697 (66.8%) statements, with all items being addressed and scored by the panelists. CONCLUSIONS This study developed consensus-based recommendations for the selection of administration line materials, the use of in-line filtration, and light protection for the administration and storage of a range of medications administered intravenously. The guidance will aid medication stability and efficacy and promote good clinical practice; it currently underpins a prototype bedside app for correct intravenous administration line selection for nursing and pharmacy staff in critical care and oncology units.

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)0.235
metaresearch head score (Gemma)0.231
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.943

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2350.231
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0060.004
Science and technology studies0.0050.005
Scholarly communication0.0040.006
Open science0.0040.011
Research integrity0.0040.004
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 head0.045
GPT teacher head0.351
Teacher spread0.306 · 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.

Study designQualitative
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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Human FactorsSame topicIntravenous Infusion Technology and SafetyFrench-language works237,207